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Run » finance, how to create a financial forecast for a startup business plan.

Financial forecasting allows you to measure the progress of your new business by benchmarking performance against anticipated sales and costs.

When starting a new business, a financial forecast is an important tool for recruiting investors as well as for budgeting for your first months of operating. A financial forecast is used to predict the cash flow necessary to operate the company day-to-day and cover financial liabilities.

Many lenders and investors ask for a financial forecast as part of a business plan; however, with no sales under your belt, it can be tricky to estimate how much money you will need to cover your expenses. Here’s how to begin creating a financial forecast for a new business.

[Read more: Startup 2021: Business Plan Financials ]

Start with a sales forecast

A sales forecast attempts to predict what your monthly sales will be for up to 18 months after launching your business. Creating a sales forecast without any past results is a little difficult. In this case, many entrepreneurs make their predictions using industry trends, market analysis demonstrating the population of potential customers and consumer trends. A sales forecast shows investors and lenders that you have a solid understanding of your target market and a clear vision of who will buy your product or service.

A sales forecast typically breaks down monthly sales by unit and price point. Beyond year two of being in business, the sales forecast can be shown quarterly, instead of monthly. Most financial lenders and investors like to see a three-year sales forecast as part of your startup business plan.

Lower fixed costs mean less risk, which might be theoretical in business schools but are very concrete when you have rent and payroll checks to sign.

Tim Berry, president and founder of Palo Alto Software

Create an expenses budget

An expenses budget forecasts how much you anticipate spending during the first years of operating. This includes both your overhead costs and operating expenses — any financial spending that you anticipate during the course of running your business.

Most experts recommend breaking down your expenses forecast by fixed and variable costs. Fixed costs are things such as rent and payroll, while variable costs change depending on demand and sales — advertising and promotional expenses, for instance. Breaking down costs into these two categories can help you better budget and improve your profitability.

"Lower fixed costs mean less risk, which might be theoretical in business schools but are very concrete when you have rent and payroll checks to sign," Tim Berry, president and founder of Palo Alto Software, told Inc . "Most of your variable costs are in those direct costs that belong in your sales forecast, but there are also some variable expenses, like ads and rebates and such."

Project your break-even point

Together, your expenses budget and sales forecast paints a picture of your profitability. Your break-even projection is the date at which you believe your business will become profitable — when more money is earned than spent. Very few businesses are profitable overnight or even in their first year. Most businesses take two to three years to be profitable, but others take far longer: Tesla , for instance, took 18 years to see its first full-year profit.

Lenders and investors will be interested in your break-even point as a projection of when they can begin to recoup their investment. Likewise, your CFO or operations manager can make better decisions after measuring the company’s results against its forecasts.

[Read more: ​​ Startup 2021: Writing a Business Plan? Here’s How to Do It, Step by Step ]

Develop a cash flow projection

A cash flow statement (or projection, for a new business) shows the flow of dollars moving in and out of the business. This is based on the sales forecast, your balance sheet and other assumptions you’ve used to create your expenses projection.

“If you are starting a new business and do not have these historical financial statements, you start by projecting a cash-flow statement broken down into 12 months,” wrote Inc . The cash flow statement will include projected cash flows from operating, investing and financing your business activities.

Keep in mind that most business plans involve developing specific financial documents: income statements, pro formas and a balance sheet, for instance. These documents may be required by investors or lenders; financial projections can help inform the development of those statements and guide your business as it grows.

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How to write a sales forecast for a business plan

Table of Contents

What is a sales forecast?

Why do you need a sales forecast, how do you write a sales forecast, top-down or bottom-up, writing your sales forecast, calculating a sales forecast, how can countingup help manage your forecasting.

Sales forecasts are an important part of your business plan . If done correctly, they can give accurate projections of your business’ cash flow, and let you better prepare for the year ahead. They can also make it easier to find the right investors . While it’s easier for existing businesses with plenty of data, you can still calculate a sales forecast for a new business .

In this guide, we’ll explore:

• How can you manage your forecasting?

A sales forecast is a prediction of your business’ future revenue. In order to be an accurate prediction, the forecast is based on previous sales, current economic trends, and industry performance. Having a sales forecast is a useful tool, because it gives you a better idea of how to manage your business. 

Having a sales forecast is like using the past to have a peek into the future of your company. It might not be 100% accurate, but it can help you plan any future spending, or prevent any cash flow issues from occurring. 

You can also use your sales forecast to monitor your business’ progress. For instance, if your business regularly performs better than your forecast, it could be a sign that your business is continuing to grow. On the other hand, if your actual sales are frequently less than expected, this could be a sign that your business is struggling and needs adjustment. 

It’s important to remember that any projections you make aren’t guaranteed, there can be advantages and disadvantages of financial forecasting . 

Now we’ve run through why having a sales forecast can help you run your business, let’s look at how to write one. 

While there are two types of sales forecasting (top-down and bottom-up), one is a lot more accurate for small businesses than the other. A top-down forecast looks at the market as a whole and attributes a portion of the market to your business. 

A top-down approach may work for large businesses that already own a significant chunk of the market. When forecasting for a small business, it’s easy to overestimate your market share. For example, a 1% market share may not seem like a lot, but a small restaurant owning 1% of the £89.5 billion UK market is extremely unrealistic.

The alternative to top-down is bottom-up. A bottom-up sales forecast starts with existing company data (like customer or product information) and works up to revenue. Since this starts with the company, it’s easier to 

Your sales forecast is ultimately a prediction of your revenue over a set period. It considers the amount you think you’ll sell, and the cost of those sales. We’ve included how to calculate a sales forecast below.

A sales forecast consists of three separate values: revenue, cost of goods sold, and gross profit. For estimating values in the calculations below, it’s best to use any existing business data to be as accurate as possible. 

To calculate your predicted revenue:

• Make a list of your available goods and services
• Note the price of each of your goods and services
• Estimate the expected sales of each good or service
• Multiply the price by the estimated sales to get your estimated revenue
• Add them all together to get your total revenue

For example, if your food truck business sold pizzas at £10 and burgers at £5, you would multiply these values by how much you expected to sell. For calculating a weekly sales forecast, you might estimate selling 60 pizzas and 80 burgers. Your predicted revenue for that week would be £600 for pizzas and £400 for burgers — giving £1,000 total.

In order to figure out how much profit you’ll make, you also need to calculate your costs for those predicted sales. To calculate your predicted costs:

• Figure out how much each good or service will cost per unit
• Multiply each cost by the projected sales

Using the same example as above, assume a single pizza cost £3.50 to make and a burger cost £2. Using the estimated sales, the total cost for your pizzas (3.5 x 60) would be £210, and £160 for your burgers (2 x 80). Combining these two figures gives you a total cost of £370.

The last step is to work out your gross profit , and it’s a relatively simple calculation.

• Subtract the total predicted cost from your total predicted revenue

Continuing with the example above, your revenue (£1,000) minus your costs (£370), leaves you with a projected gross profit of £630 for the week. Using this estimate, you can then plan how much working capital your business should have access to. It’s important to remember that these are only estimates, and your actual values can be higher or lower than your forecast.

If you want your forecasts to be as accurate as possible, you need to refer to all of your business’ financial data. Since collecting and collating this data can be challenging, you may want to use financial management software like the Countingup app. 

When trying to calculate your sales forecasts, having an up-to-date log of your current sales can be hugely beneficial. By combining a business current account with accounting software, Countingup is the only software that provides real-time cash flow tracking. 

The Countingup app also provides business owners with access to automatically generated profit and loss statements. These can prove invaluable when trying to stay aware of all your business’ costs.

Start your three-month free trial today. Find out more here .

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A Comprehensive Guide: How to Forecast Revenues for Your Business Plan

Introduction:.

Forecasting revenues is a crucial aspect of developing a business plan. Accurate revenue projections not only attract investors but also provide a roadmap for sustainable growth and financial success. This article will provide you with a step-by-step guide to help you forecast revenues effectively. By following these strategies and best practices, you can make informed decisions, set realistic goals, and build a solid foundation for your business.

I. Understand Your Market and Customers:

Before you can forecast revenues, it's essential to gain a deep understanding of your target market and customers. Conduct market research to analyze trends, demand, and competition. Identify your target audience's needs, preferences, and purchasing behavior. This information will help you estimate the potential market size and assess the revenue potential for your products or services.

II. Break Down Revenue Streams:

Next, break down your revenue streams into specific categories. For example, if you have multiple products or services, create separate revenue streams for each. Consider the pricing structure, sales volume, and average transaction value for each category. This breakdown enables you to analyze and forecast revenues with greater accuracy.

III. Utilize Historical Data:

If you have been in business for some time, historical data can serve as a valuable resource for revenue forecasting. Analyze past financial records, sales data, and customer trends. Identify patterns, seasonal variations, and growth rates. Use this information as a baseline to project future revenues, accounting for any market changes or new product launches.

IV. Determine Key Assumptions:

Forecasting revenues involves making certain assumptions about your business and the market. Identify the key factors that will impact your revenue projections, such as market growth rates, pricing changes, or shifts in consumer behavior. Document these assumptions clearly, ensuring they are realistic and supported by data and market trends.

V. Use Multiple Forecasting Methods:

To enhance the accuracy of your revenue projections, employ various forecasting methods. Here are a few commonly used techniques:

a) Top-Down Approach:

Start with the overall market size, estimate your market share, and calculate revenues based on this share.

b) Bottom-Up Approach:

Begin with individual product or service sales projections and aggregate them to obtain total revenue estimates.

c) Time-Series Analysis:

Analyze historical sales data to identify patterns, trends, and seasonality. Apply statistical methods like moving averages or exponential smoothing to project future revenues.

d) Market Research and Surveys:

Conduct market surveys or customer interviews to gather insights on demand, price sensitivity, and purchasing behavior. Use this data to estimate market size and forecast revenues.

VI. Account for External Factors:

Consider external factors that could impact your revenue forecast, such as economic conditions, industry trends, regulatory changes, or technological advancements. Conduct a thorough analysis of these factors and assess their potential influence on your business. Adjust your revenue projections accordingly to reflect any anticipated challenges or opportunities.

VII. Monitor and Review:

Once you have developed your revenue forecast, it is crucial to continuously monitor and review its accuracy. Regularly compare your projections with actual revenue performance and adjust your forecast as needed. Use key performance indicators (KPIs) to track your progress and make informed decisions to drive revenue growth.

By following the steps outlined in this guide, you can enhance the accuracy and reliability of your revenue forecast for your business plan.

Here are a few additional tips to keep in mind:

Sensitivity Analysis:

Perform a sensitivity analysis by testing your revenue projections against various scenarios. This will help you understand the potential impact of changes in key variables such as pricing, market share, or economic conditions. It provides a more comprehensive view of the range of possible outcomes.

Seek Expert Advice:

If you're unsure about certain aspects of revenue forecasting or lack expertise in financial analysis, consider consulting with us. At businessplanprovider.com , we have professionals such as accountants, financial advisors, and industry experts. Their insights and guidance can add credibility to your revenue forecast.

Regularly Update Your Forecast:

Revenue forecasting is not a one-time exercise. As your business grows and market conditions evolve, it's crucial to update your forecast regularly. Review and revise your projections quarterly or annually, taking into account any new information or changes in your business environment.

Validate with Market Feedback:

Don't rely solely on internal data or assumptions. Seek feedback from potential customers, industry experts, or mentors to validate your revenue projections. Incorporate their insights into your forecast, as they can provide valuable perspectives and highlight blind spots.

Be Realistic and Conservative:

While it's important to set ambitious goals, it's equally crucial to be realistic and conservative in your revenue forecast. Investors and stakeholders appreciate a forecast that demonstrates a clear understanding of potential challenges and uncertainties. Avoid overestimating revenues, as it may lead to unrealistic expectations and undermine your credibility.

Remember that revenue forecasting is both an art and a science. It requires a blend of data analysis, market understanding, and informed decision-making. Be prepared to adjust your forecast as new information becomes available or market dynamics change.

Conclusion:

Forecasting revenues for your business plan requires a systematic and data-driven approach. By understanding your market and customers, utilizing historical data, making key assumptions, employing multiple forecasting methods, accounting for external factors, and continuously monitoring and reviewing your forecast, you can develop realistic revenue projections. Remember, revenue forecasting is an ongoing process that should be regularly updated to align with market changes and business growth. By accurately forecasting revenues, you can make informed strategies, allocate resources effectively, and attract investors and stakeholders who are confident in the potential of your business.

A well-structured and thoughtfully prepared revenue forecast will not only guide your business planning and decision-making but also demonstrate your professionalism and strategic thinking to potential investors. By following the steps and best practices outlined in this guide, you can develop a robust revenue forecast that will support the growth and success of your business. 

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The Importance of Revenue Forecasting in 2023

, Chief of Staff, Abacum

13 min read · Published: August 9, 2023

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🎯 Introduction

In today’s competitive business landscape, revenue forecasting plays a crucial role in the success and growth of any organization. By accurately predicting future revenue streams, businesses can make informed decisions, allocate resources effectively, and drive sustainable profitability.

In this article you will explore the importance of revenue forecasting, different forecasting models, a step-by-step guide to building your own model, and answers to common questions surrounding this essential business practice.

Understanding the Importance of Revenue Forecasting

Revenue forecasting plays a vital role in business planning, providing insights into future financial performance and helping organizations set realistic goals. By analyzing historical data, market trends, and other relevant factors, businesses can anticipate their revenue streams, identify potential risks, and optimize their sales strategies. Revenue forecasting serves as the foundation for financial planning, budgeting, and resource allocation, enabling companies to align their operations with their revenue targets.

One of the key reasons why revenue forecasting is crucial for businesses is that it allows them to assess their financial health and plan accordingly. By accurately predicting future revenue streams, organizations can make informed decisions about resource allocation, ensuring that they have the necessary funds to support their operations and growth initiatives. This helps businesses avoid cash flow problems and ensures that they are financially prepared for any challenges that may arise.

In addition to financial planning, revenue forecasting also plays a significant role in strategic decision-making. By understanding their expected revenue, businesses can assess the feasibility of new ventures and determine the potential return on investment. This information is invaluable when it comes to evaluating the viability of expanding into new markets, launching new products or services, or making any other strategic business decisions.

The Role of Revenue Forecasting in Business Planning

Revenue forecasting is an integral part of the business planning process. It helps organizations set achievable revenue targets and develop strategic initiatives to achieve those goals. By utilizing revenue forecasts, businesses can assess the feasibility of new ventures, make informed decisions about resource allocation, and create comprehensive financial projections for investors and stakeholders.

When it comes to setting revenue targets, organizations need to strike a balance between ambition and realism. Revenue forecasts help businesses determine what is achievable based on historical data, market trends, and other relevant factors. This ensures that the targets set are challenging yet attainable, motivating employees and driving the company towards success.

Moreover, revenue forecasting is not just limited to setting targets. It also helps businesses identify potential risks and opportunities. By analyzing historical data and market trends, organizations can identify patterns and make predictions about future revenue streams. This allows them to proactively address any potential challenges and capitalize on emerging opportunities, giving them a competitive edge in the market.

Benefits of Accurate Revenue Forecasting

An accurate revenue forecast provides numerous benefits for businesses of all sizes. By accurately predicting future revenue streams, organizations can optimize their inventory levels, streamline production processes, and adjust their pricing strategies. This ensures that businesses have the right amount of inventory to meet customer demand, minimizing excess inventory costs and avoiding stockouts.

Accurate revenue forecasting also enables businesses to make data-driven decisions about their pricing strategies. By understanding their expected revenue, organizations can assess the impact of different pricing scenarios and determine the optimal pricing strategy to maximize profitability. This helps businesses stay competitive in the market and attract customers while maintaining a healthy profit margin.

Additionally, accurate revenue forecasting allows businesses to identify potential cash flow challenges and take proactive measures to mitigate them. By understanding their expected revenue, organizations can anticipate periods of low cash flow and take steps to manage their expenses or secure additional funding. This helps businesses avoid cash flow problems and ensures that they can continue to operate smoothly even during challenging times.

Furthermore, accurate revenue forecasting enables companies to assess the impact of external factors, such as market conditions or regulatory changes, and make timely adjustments to their sales and marketing strategies. By monitoring market trends and analyzing their revenue forecasts, organizations can identify shifts in customer behavior or market dynamics and adapt their strategies accordingly. This flexibility allows businesses to stay agile and responsive in a rapidly changing business environment.

Exploring Different Revenue Forecasting Models

Various revenue forecasting models can help businesses predict sales and revenue streams more effectively. Each model offers unique insights and can be tailored to suit different industries and business needs.

Let’s explore some popular revenue forecasting models:

1. The Quota Capacity Model

The Quota Capacity Model focuses on the capacity of the sales team to achieve their sales targets. By analyzing historical sales data, individual sales quotas, and overall capacity, organizations can forecast future revenue based on their sales team’s performance. This model helps businesses understand their sales team’s capabilities, prioritize opportunities, and identify areas for improvement.

For example, a software company may use the Quota Capacity Model to assess the performance of its sales team. By analyzing past sales data, they can determine if their sales representatives are consistently meeting their quotas or if there are any patterns of underperformance. This information can help the company identify training needs, adjust sales targets, and allocate resources more effectively.

In addition, the Quota Capacity Model can also help businesses identify potential bottlenecks in their sales process. By analyzing the capacity of the sales team and comparing it to the demand for their product or service, organizations can identify if they have enough resources to meet customer demand. This can inform hiring decisions, expansion plans, and overall business strategy.

2. The ARR Snowball Model

The ARR Snowball Model is commonly used by subscription-based businesses to forecast their recurring revenue growth. It considers factors such as customer churn rate, average revenue per customer, and new customer acquisition. By tracking these metrics, businesses can project their future revenue growth and identify strategies to optimize customer retention and acquisition.

For instance, a subscription-based streaming service may use the ARR Snowball Model to forecast its revenue growth. By analyzing the churn rate (the rate at which customers cancel their subscriptions), the average revenue per customer, and the rate of acquiring new customers, the company can estimate its future revenue streams. This information can help the company develop strategies to reduce customer churn, increase average revenue per customer, and attract new customers through targeted marketing campaigns or product enhancements.

Moreover, the ARR Snowball Model can also assist businesses in identifying potential market opportunities. By analyzing customer acquisition rates and revenue growth in different market segments, organizations can identify which segments are performing well and where there is room for growth. This can guide businesses in allocating resources, targeting specific customer groups, and expanding into new markets.

3. The Sales Cycle to New Bookings Model

The Sales Cycle to New Bookings Model focuses on the sales pipeline and conversion rates at each stage of the sales cycle. By analyzing past performance and conversion rates, organizations can predict future revenue based on their sales pipeline. This model helps sales teams identify potential bottlenecks, optimize their sales processes, and improve forecasting accuracy.

For example, a manufacturing company may use the Sales Cycle to New Bookings Model to forecast its sales pipeline. By analyzing the time it takes for leads to convert into customers at each stage of the sales cycle, the company can estimate the number of new bookings they can expect in the future. This information can help the company identify potential bottlenecks in the sales process, such as long lead times or low conversion rates, and take corrective actions to improve efficiency and increase revenue.

In addition, the Sales Cycle to New Bookings Model can also provide valuable insights into customer behavior and preferences. By analyzing conversion rates and customer feedback at each stage of the sales cycle, organizations can identify patterns and trends that can inform marketing strategies, product development, and customer relationship management. This can lead to more targeted and effective sales efforts, resulting in increased revenue and customer satisfaction.

4. The Bookings, Billings, and Collections Model

The Bookings, Billings, and Collections Model provides a comprehensive view of revenue flow throughout the sales cycle. It considers factors such as bookings (orders placed), billings (invoices issued), and collections (cash collected). By tracking these metrics, businesses can anticipate their cash flow and identify potential gaps or delays in revenue collection.

For instance, a consulting firm may use the Bookings, Billings, and Collections Model to track its revenue flow. By analyzing the number of bookings (client engagements), the amount invoiced (billings), and the cash collected (collections), the firm can monitor its cash flow and identify any discrepancies or delays in payment. This information can help the firm manage its financial resources more effectively, negotiate payment terms with clients, and plan for future expenses.

Moreover, the Bookings, Billings, and Collections Model can also help businesses identify areas for process improvement. By analyzing the time it takes for bookings to turn into billings and collections, organizations can identify potential bottlenecks in their invoicing and payment processes. This can lead to streamlined operations, reduced payment delays, and improved cash flow management.

Step-by-Step Guide to Building a Revenue Forecasting Model

Building a revenue forecasting model requires careful analysis of historical data, market trends, and relevant business factors.

By following these steps, you can create an accurate revenue forecast for your organization:

Creating Assumptions for Customer Growth and Average ARR

To begin, assess your historical customer growth rate and average Annual Recurring Revenue (ARR). Utilize market research, industry benchmarks, and internal data to make informed assumptions about future customer growth and ARR. These assumptions will form the basis of your revenue forecast.

When analyzing historical customer growth, consider factors such as marketing efforts, customer acquisition strategies, and market conditions. Look for patterns and trends that can help you identify potential growth opportunities or challenges.

Additionally, when determining the average ARR, take into account pricing strategies, product enhancements, and customer feedback. Analyze how these factors have influenced the average revenue generated per customer over time.

By thoroughly understanding your customer growth and average ARR, you can make more accurate assumptions for your revenue forecast, which will ultimately help you make informed business decisions.

Learn more:

Calculating Net New Bookings for Accurate Revenue Projection

Next, calculate your Net New Bookings by considering new customer acquisition and upselling opportunities. Incorporate factors such as conversion rates, pricing changes, and market trends to estimate your future bookings accurately. This step will help you project your revenue streams in a realistic and achievable manner.

When analyzing new customer acquisition, evaluate your marketing and sales strategies. Identify the channels that have been most successful in attracting new customers and assess the effectiveness of your lead generation efforts. Consider the conversion rates at each stage of the sales funnel to estimate the number of new customers you can expect in the future.

Furthermore, when evaluating upselling opportunities, analyze customer behavior and purchasing patterns. Look for cross-selling or upselling opportunities within your existing customer base and determine the potential revenue impact of these strategies.

By incorporating these factors into your revenue projection, you can gain a more comprehensive understanding of your future revenue streams and make strategic decisions to drive growth.

Modeling Renewal Bookings for Revenue Continuity

Renewal bookings are crucial for maintaining revenue continuity in subscription-based businesses. Assess your historical renewal rates, customer satisfaction levels, and contract terms to model your future renewal bookings. By factoring in potential churn and renewal rates, you can accurately forecast your revenue streams and understand the impact of customer retention on your organization.

When analyzing historical renewal rates, consider the reasons why customers choose to renew or not renew their subscriptions. Look for patterns or commonalities among customers who have renewed and those who have churned. This analysis can help you identify areas for improvement and develop strategies to increase customer retention.

Additionally, evaluate customer satisfaction levels through surveys, feedback, and support interactions. Identify areas where you can enhance the customer experience and address any pain points that may contribute to customer churn.

By modeling your renewal bookings based on these factors, you can gain insights into the future revenue continuity of your business and implement strategies to improve customer retention.

Calculating Billings and Collections for Cash Flow Analysis

Lastly, calculate your billings and collections to analyze your cash flow. Consider factors such as payment terms, invoicing accuracy, and collection efficiency to forecast your cash flow accurately. By understanding your cash flow dynamics, you can proactively address potential challenges and optimize your financial operations.

When analyzing payment terms, assess the average time it takes for customers to pay their invoices. Consider any seasonal or industry-specific factors that may affect payment timelines. This analysis will help you estimate the timing of your cash inflows and outflows.

In terms of invoicing accuracy, evaluate your billing processes to ensure that invoices are generated correctly and promptly. Identify any bottlenecks or inefficiencies that may delay the invoicing process and impact your cash flow.

Furthermore, when assessing collection efficiency, analyze your collection practices and policies. Identify any overdue accounts or potential risks of non-payment. Develop strategies to improve collection rates and minimize the impact of late payments on your cash flow.

By accurately calculating your billings and collections, you can gain a deeper understanding of your cash flow dynamics and make informed decisions to optimize your financial operations.

Taking Top-Line Planning to the Next Level

Revenue forecasting is a crucial aspect of understanding a business’s financial performance. It allows organizations to anticipate future revenue streams, identify potential challenges, and make informed decisions. However, to truly maximize the benefits of revenue forecasting, businesses can take their top-line planning to the next level by integrating it with other planning processes.

• One key area where integration can be immensely valuable is aligning revenue forecasts with operational plans. By connecting revenue projections with operational strategies, businesses can ensure that their resources and capabilities are aligned with their revenue goals. This alignment enables organizations to optimize their overall performance and drive sustainable growth.
• Another critical aspect of taking top-line planning to the next level is integrating revenue forecasting with marketing strategies. By understanding the projected revenue streams, businesses can tailor their marketing efforts to target specific customer segments, optimize pricing strategies, and identify opportunities for growth. This integration allows organizations to create a cohesive and effective marketing plan that aligns with their revenue goals.

Furthermore, integrating revenue forecasting with financial goals is essential for effective top-line planning. By aligning revenue projections with financial targets, businesses can better manage cash flows, plan investments, and make strategic financial decisions. This integration ensures that financial resources are allocated efficiently and effectively, maximizing the chances of achieving desired financial outcomes.

While integration is crucial, leveraging advanced analytics, predictive technologies, and real-time data can further enhance the accuracy and agility of revenue forecasting. Advanced analytics tools can analyze historical data, market trends, and customer behavior to generate more accurate revenue forecasts. Predictive technologies can help businesses anticipate future revenue streams based on various scenarios and assumptions. Real-time data integration allows organizations to monitor revenue performance continuously, identify deviations from forecasts, and make timely adjustments.

In conclusion, while revenue forecasting provides valuable insights into a business’s financial performance. It acts as a guide, enabling the prediction of future revenue streams, anticipating potential challenges, and supporting well-informed decision-making.

However, the true power of revenue forecasting emerges when it seamlessly integrates with other essential planning aspects. This is precisely where a solution like Abacum comes into play.

Abacum FP&A software empowers to discern what’s effective, what’s not, and how to take actionable steps to achieve desired outcomes. Connect with an Abacum FP&A consultant today to kickstart the conversation.

Answers to Common Revenue Forecasting Questions

How does excel’s suite of data analysis tools.

Excel is a widely used tool for revenue forecasting but when it comes to revenue forecasting, accuracy is key. Excel offers various data analysis tools that can help businesses make more informed projections. These tools include regression analysis, moving averages, and exponential smoothing. By leveraging these tools, businesses can analyze historical data, identify trends, and make predictions based on patterns.

In what ways can businesses leverage Excel’s formula optimization and custom formula creation capabilities?

Formula optimization is another important aspect of forecasting in Excel. By using the right formulas and functions, businesses can automate calculations and save time. Excel provides a wide range of formulas that can be used for revenue forecasting, such as SUM, AVERAGE, and IF, that can be used to perform complex calculations. Additionally, businesses can create custom formulas to suit their specific forecasting needs.

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How to Create a Sales Forecast

11 min. read

Updated October 27, 2023

Business owners are often afraid to forecast sales. But, you shouldn’t be. Because you can successfully forecast your own business’s sales.

You don’t have to be an MBA or CPA. It’s not about some magic right answer that you don’t know. It’s not about training you don’t have. It doesn’t take spreadsheet modeling (much less econometric modeling) to estimate units and price per unit for future sales. You just have to know your own business. 

Forecasting isn’t about seeing into the future

Sales forecasting is much easier than you think and much more useful than you imagine.

I was a vice president of a market research firm for several years, doing expensive forecasts, and I saw many times that there’s nothing better than the educated guess of somebody who knows the business well. All those sophisticated techniques depend on data from the past — and the past, by itself, isn’t the best predictor of the future. You are.

It’s not about guessing the future correctly. We’re human; we don’t do that well. Instead, it’s about setting down assumptions, expectations, drivers, tracking, and management. It’s about doing your job, not having precognitive powers. 

• Successful forecasting is driven by regular reviews

What really matters is that you review and revise your forecast regularly. Spending should be tied to sales, so the forecast helps you budget and manage. You measure the value of a sales forecast like you do anything in business, by its measurable business results.

That also means you should not back off from forecasting because you have a new product, or new business, without past data. Lay out the sales drivers and interdependencies, to connect the dots, so that as you review plan-versus-actual results every month, you can easily make course corrections.

If you think sales forecasting is hard, try running a business without a forecast. That’s much harder.

Your sales forecast is also the backbone of your business plan . People measure a business and its growth by sales, and your sales forecast sets the standard for  expenses , profits, and growth. The sales forecast is almost always going to be the first set of numbers you’ll track for plan versus actual use, even if you do no other numbers.

If nothing else, just forecast your sales, track plan-versus-actual results, and make corrections — that process alone, just the sales forecast and tracking is in itself already business planning. To get started on building your forecast follow these steps.

And if you run a subscription-based business, we have a guide dedicated to building a sales forecast for that business model.

• Step 1: Set up your lines of sales

Most forecasts show several distinct lines of sales. Ideally, your sales lines match your accounting, but not necessarily in the same level of detail.   

For example, a restaurant ought not to forecast sales for each item on the menu. Instead, it forecasts breakfasts, lunches, dinners, and drinks, summarized. And a bookstore ought not to forecast sales by book, and not even by topic or author, but rather by lines of sales such as hardcover, softcover, magazines, and maybe categories (such as fiction, non-fiction, travel, etc.) if that works.

Always try to set your streams to match your accounting, so you can look at the difference between the forecast and actual sales later. This is excellent for real business planning. It makes the heart of the process, the regular review, and revision, much easier. The point is better management.

For instance, in a bicycle retail store business plan, the owner works with five lines of sales, as shown in the illustration here.  

In this sample case, the revenue includes new bikes, repair, clothing, accessories, and a service contract. The bookkeeping for this retail store tracks sales in those same five categories.

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• Step 2: Forecast line by line

There are many ways to forecast a line of sales.

The method for each row depends on the business model

Among the main methods are:.

• Unit sales : My personal favorite. Sales = units times price. You set an average price and forecast the units. And of course, you can change projected pricing over time. This is my favorite for most businesses because it gives you two factors to act on with course corrections: unit sales, or price.
• Service units : Even though services don’t sell physical units, most sell billable units, such as billable hours for lawyers and accountants, or trips for transportations services, engagements for consultants, and so forth.
• Recurring charges : Subscriptions. For each month or year, it has to forecast new signups, existing monthly charges, and cancellations. Estimates depend on both new signups and cancellations, which is often called “churn.”
• Revenue only : For those who prefer to forecast revenue by the stream as just the money, without the extra information of breaking it into units and prices.

Most sales forecast rows are simple math

For a business plan, I recommend you make your sales forecast a detailed look at the next 12 months and then broadly cover two years after that. Here’s how to approach each method of line-by-line forecasting.

Start with units if you can

For unit sales, start by forecasting units month by month, as shown here below for the new bike’s line of sales in the bicycle shop plan:

I recommend looking at the visual as you forecast the units because most of us can see trends easier when we look at the line, as shown in the illustration, rather than just the numbers. You can also see the numbers in the forecast near the bottom. The first year, fiscal 2021 in this forecast, is the sum of those months.

Estimate price assumptions

With a simple revenue-only assumption, you do one row of units as shown in the above illustration, and you are done. The units are dollars, or whatever other currency you are using in your forecast. In this example, the new bicycle product will be sold for an average of $550.00. 

That’s a simplifying assumption, taking the average price, not the detailed price for each brand or line. Garrett, the shop owner, uses his past results to determine his actual average price for the most recent year. Then he rounds that estimate and adds his own judgment and educated guess on how that will change. 

Multiply price times units

Multiplying units times the revenue per unit generates the sales forecast for this row. So for example the $18,150 shown for October of 2020 is the product of 33 units times $550 each. And the $21,450 shown for the next month is the product of 39 units times $550 each. 

Subscription models are more complicated

Lately, a lot of businesses offer their buyers subscriptions, such as monthly packages, traditional or online newspapers, software, and even streaming services. All of these give a business recurring revenues, which is a big advantage. 

For subscriptions, you normally estimate new subscriptions per month and canceled subscriptions per month, and leave a calculation for the actual subscriptions charged. That’s a more complicated method, which demands more details. 

For that, you can refer to detailed discussions on subscription forecasting in How to Forecast Sales for a Subscription Business .

• But how do you know what numbers to put into your sales forecast?

The math may be simple, yes, but this is predicting the future, and humans don’t do that well. So, don’t try to guess the future accurately for months in advance.

Instead, aim for making clear assumptions and understanding what drives your sales, such as web traffic and conversions, in one example, or the direct sales pipeline and leads, in another. Review results every month, and revise your forecast. Your educated guesses become more accurate over time.

Experience in the field is a huge advantage

In a normal ongoing business, the business owner has ample experience with past sales. They may not know accounting or technical forecasting, but they know their business. They are aware of changes in the market, their own business’s promotions, and other factors that business owners should know. They are comfortable making educated guesses.

If you don’t personally have the experience, try to find information and make guesses based on the experience of an employee,  your mentor , or others you’ve spoken within your field.

Use past results as a guide

Use results from the recent past if your business has them. Start a forecast by putting last year’s numbers into next year’s forecast, and then focus on what might be different this year from next.

Do you have new opportunities that will make sales grow? New marketing activities, promotions? Then increase the forecast. New competition, and new problems? Nobody wants to forecast decreasing sales, but if that’s likely, you need to deal with it by cutting costs or changing your focus.

Look for drivers

To forecast sales for a new restaurant, first, draw a map of tables and chairs and then estimate how many meals per mealtime at capacity, and in the beginning. It’s not a random number; it’s a matter of how many people come in.

To forecast sales for a new mobile app, you might get data from the Apple and Android mobile app stores about average downloads for different apps. A good web search might also reveal some anecdotal evidence, blog posts, and news stories, about the ramp-up of existing apps that were successful.

Get those numbers and think about how your case might be different. Maybe you drive downloads with a website, so you can predict traffic from past experience and then assume a percentage of web visitors who will download the app.

• Estimate direct costs

Direct costs are also called the cost of goods sold (COGS) and per-unit costs. Direct costs are important because they help calculate gross margin, which is used as a basis for comparison in financial benchmarks, and are an instant measure (sales less direct costs) of your underlying profitability.

For example, I know from benchmarks that an average sporting goods store makes a 34 percent gross margin. That means that they spend $66 on average to buy the goods they sell for $100.

Not all businesses have direct costs. Service businesses supposedly don’t have direct costs, so they have a gross margin of 100 percent. That may be true for some professionals like accountants and lawyers, but a lot of services do have direct costs. For example, taxis have gasoline and maintenance. So do airlines.

A normal sales forecast includes units, price per unit, sales, direct cost per unit, and direct costs. The math is simple, with the direct costs per unit related to total direct costs the same way price per unit relates to total sales.

Multiply the units projected for any time period by the unit direct costs, and that gives you total direct costs. And here too, assume this view is just a cut-out, it flows to the right. In this example, Garrett the shop owner projected the direct costs of new bikes based on the assumption of 49 percent of sales.

Given the unit forecast estimate, the calculation of units times direct costs produces the forecast shown in the illustration below for direct costs for that product. So therefore the projected direct costs for new bikes in October is $8,894, which is 49% of the projected sales for that month, $18,150.

• Never forecast in a vacuum

Never think of your sales forecast in a vacuum. It flows from the strategic action plans with their assumptions,  milestones , and metrics. Your marketing milestones affect your sales. Your business offering milestones affect your sales.

When you change milestones—and you will, because all business plans change—you should change your sales forecast to match.

• Timing matters

Your sales are supposed to refer to when the ownership changes hands (for products) or when the service is performed (for services). It isn’t a sale when it’s ordered, or promised, or even when it’s contracted.

With proper  accrual accounting , it is a sale even if it hasn’t been paid for. With so-called cash-based accounting, by the way, it isn’t a sale until it’s paid for. Accrual is better because it gives you a more accurate picture, unless you’re very small and do all your business, both buying and selling, with cash only.

I know that seems simple, but it’s surprising how many people decide to do something different. The penalty for doing things differently is that then you don’t match the standard, and the bankers, analysts, and investors can’t tell what you meant.

This goes for direct costs, too. The direct costs in your monthly  profit and loss statement  are supposed to be just the costs associated with that month’s sales. Please notice how, in the examples above, the direct costs for the sample bicycle store are linked to the actual unit sales.

• Live with your assumptions

Sales forecasting is not about accurately guessing the future. It’s about laying out your assumptions so you can manage changes effectively as sales and direct costs come out different from what you expected. Use this to adjust your sales forecast and improve your business by making course corrections to deal with what is working and what isn’t.

I believe that even if you do nothing else, by the time you use a sales forecast and review plan versus actual results every month, you are already managing with a business plan . You can’t review actual results without looking at what happened, why, and what to do next.

See why 1.2 million entrepreneurs have written their business plans with LivePlan

Tim Berry is the founder and chairman of Palo Alto Software , a co-founder of Borland International, and a recognized expert in business planning. He has an MBA from Stanford and degrees with honors from the University of Oregon and the University of Notre Dame. Today, Tim dedicates most of his time to blogging, teaching and evangelizing for business planning.

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The Revenue Forecasting Guide and Best Forecasting Models

What is Revenue Forecasting?

Why is revenue forecasting important, create a realistic financial plan, anticipate a ramp-up in hires, the top 4 forecasting methods, straight-line forecasting method, moving average forecasting method, simple linear regression forecasting method, multiple linear regression forecasting method, the do’s and don’ts of revenue forecasting, do use data for your assumptions, don’t try to design the “ideal” forecast, do update your forecast frequently, don’t create your forecast all by yourself.

It all boils down to your business when it comes to revenue projections. Not only the future of your company but also the precise location, industry, and services you ultimately offer customers. You must create revenue predictions to evaluate your business's status going forward to establish an accurate budget equivalent to your company's annual strategy.

Revenue forecasting is the process of estimating future revenue based on past performance and current trends. Forecasting is necessary for any business plan because it provides direction for decision-making, including budgeting and resource allocation. Without accurate revenue projections, it would be difficult to make informed decisions about where to allocate resources to achieve desired. A revenue forecast, for example, might highlight where you're going at your current rate if you want to know how much money you'll make next month, quarter, or year.

Revenue forecasting is an essential tool for all businesses, regardless of size or industry.

There are several advantages to predicting your revenue. Revenue forecasting is all about putting your company in a position to face whatever the future may bring so that you're not caught off guard and can make the most informed decisions possible to develop your business.

Here are a few major reasons to forecast revenue.

Personal and business finances are both concerned with managing your money. Personal finance involves creating a budget based on your income. You know you can't spend more than $5,000 every month if you get paid $5,000 per month from your job. You can budget for everything from food to going out and other variable expenses as long as they are within your means.

However, a company's revenue is seldom consistent each month. Your income can vary depending on how much you sell, whether or not you have churning customers—if you're a subscription firm, and market conditions. It's tough to plan for daily operations like marketing or new expenditures like recruiting employees when you're not sure how much money you'll have coming in.

Forecasting allows you to bridge the gap between your projections and reality, particularly for operating costs. Your forecast provides a prediction of how much money you'll make in the following few months or years. This will help you forecast how much money you can set aside for marketing efforts, new employees, software purchases, and other spending that fluctuates over time.

I've already gone over new employees in the previous section, but it's worth mentioning it here. Hiring is distinctive because, unlike many other costs, it usually needs to be planned several months ahead, and your revenue significantly impacts your hiring choices.

When recruiting a new employee, you need to be sure that you'll be able to afford them long-term, not just in the near term. If your revenue forecast shows growth over the next year, you may feel more confident in being able to add members to your team.

While both are true, they aren't the whole picture. If your revenue projections drop or slow down, you may need to scale back on employee growth.

Discover both concepts, their importances and limitations as well as similarities and differences

The most common techniques financial analysts use to forecast a firm's future revenues, costs, and capital expenses are straight-line, moving average, simple linear regression, and multiple linear regression. While there are many different quantitative budget forecasting tools in use today, we'll focus on the top four methods: (1) straight line, (2) moving average, (3) simple linear regression," and (4) multiple linear regression.

When the growth rate remains consistent, this approach is frequently employed to get a simple picture of constant expansion at the same rate. It only uses basic arithmetic and past statistics. Ultimately, it gives predictions for future development that may help you with financial and budget goals.

An Example of Straight-Line Financial Forecasting

The growth rate of a restaurant chain has remained stable at 5% over the past three years. The business expects its expansion rate to continue at that level for the next two years. By adding 5% to this year's growth and 5% to the following year's and recording those results as the preceding year's growth plus one, the company may make reliable predictions about how many new workers it will need to hire in each of those years and how much additional payroll money they will require.

A moving average is a form of trend analysis that compares the current performance in shorter time periods to that of previous periods. It isn't utilized over longer durations, such as years, because it creates too much lag to be helpful in trend following.

Using this technique, an average of variables with significant movement, like stock prices, and values with frequent but slower changes, such as inventory levels during peak retail seasons, can be continuously updated.

In a nutshell, this strategy is used to look for underlying patterns that can be used to evaluate common financial measures such as revenues, earnings, sales growth, and stock prices. A downtrend is indicated by a dropping moving average, and a rising moving average shows an uptrend.

An Example of Moving Average Financial Forecasting

A retailer wants to figure out how much product if any, he needs to reorder from a wholesaler. Sales are doing well overall because it is the holiday season, but he needs to know which goods are rising in popularity. He produces a moving average for the week to tell him the trend and guide his inventory buy orders rather than trying to watch irregular upticks and declines in a particular product's sales each day or over a week.

The connection between a dependent and an independent variable is utilized to draw a trend line. An analysis using linear regression connects changes in an explanatory variable on the X-axis to changes in a dependent variable on the Y-axis. The relationship between the X and Y variables generates a graph line representing a trend that often swings upward or downward or remains stable.

An Example of Simple Linear Regression Financial Forecasting

Two factors crucial to every firm's success are sales and profits. If the trend line for sales (x-axis) and profits (y-axis) rises when used with simple linear regression, then everything is fine for the firm, and margins are robust. If sales are up while profits are down, something is wrong; perhaps there are increasing supply costs or tight margins. Despite this, if sales are down but profits are up, the product's value rises. This indicates that company costs/expenses have decreased and that the linear regression model is functioning well—when profits rise, margins improve as a percentage.

This method makes a forecast using more than two distinct variables. A model of the relationship between the main explanatory variables (parameters) and the dependent response variable is essentially created using much linear regression (MLR) (outcome).

An Example of Multiple Linear Regression

A trucking company executive wants to forecast gasoline prices for the following six months. The EIA Gasoline and Diesel Fuel Update, oil futures from a futures exchange, mileage from GPS fleet routing systems, traffic patterns from smart city open data platforms, and the number of trucks the company anticipates will be on the road during the period based on delivery orders are the independent variables used for this method. This list is provided for illustration reasons only; other factors may also impact the outcome.

In each scenario, all of the variables not only affect the outcome but are also independent of it. Based on the factors, this model makes predictions about the result, in this example, the anticipated gasoline prices for the time period.

Google Sheets FORECAST Function (+ Examples)

The Google Sheets FORECAST function predicts future values based on your data. Here’s how to use the FORECAST function step-by-step, with examples.

Let's look at some best practices for creating an accurate revenue forecast. Here are some dos and don'ts for revenue forecasting.

Data has probably been a recurring pattern in this article. Many entrepreneurs make the error of basing their income predictions on their most optimistic assumptions. The issue with that is that it may cause you to grossly overstate your sales figures, which might be disastrous for your company.

Making decisions based on those projections is just slightly worse than overestimating your revenue. Data is your friend!

There is no flawless forecast. It's impossible to anticipate precisely how much revenue you'll have in three months, let alone 1-2 years from now, even if you go over every detail with a fine-tooth comb.

Anything could happen between now and three months from now. Your entire industry could be affected by the emergence of a new rival. If your product becomes popular, you can experience an increase in sales. You run the risk of having prolonged flat growth. The idea is that commerce is fluid.

Revenue projections aren't intended to be accurate future forecasts. They're designed to provide you with direction so you can decide more wisely.

It is not the best use of your time to attempt to forecast every cent you make during the upcoming quarter over days or weeks. Instead, make every effort to make your prognosis as accurate as possible and then make changes as necessary.

The revenue prediction you create at the beginning of the year shouldn't be abandoned to gather dust.

You should adjust your revenue prediction as circumstances in your company change.

For example, your original prediction may have anticipated the execution of 3–4 targeted marketing efforts throughout the year. However, after conducting two, you might alter based on the outcomes. Your revenue prediction will be affected by anything, including trying a new channel, improving the conversion of your advertising, and lowering your performance goals.

Your business model will determine how frequently you should update your revenue forecast. While a more established business might revise its projection every three months, an early-stage startup conducting extensive testing to learn the ropes might need to make revisions every month.

The most crucial thing is to avoid treating your revenue prediction as a static record. It can be a helpful tool for progress if you frequently monitor and analyze it.

Revenue forecasting includes input from several people unless you're a one-person company.

You can learn about marketing's upcoming initiatives from them to generate leads and sales. You may learn more about the funnel and sales velocity from sales. You can get advice and information from everyone active in bringing in and keeping customers. If you're not as "in the weeds" with sales and marketing on a daily basis, this can be useful.

Consti met co-founder Moritz at Helpling. Both heavy spreadsheet users, they decided to channel their frustrations with Excel and Google Sheets into a solution. Teaming up with Ernests, they launched Layer.

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7 Financial Forecasting Methods to Predict Business Performance

• 21 Jun 2022

Much of accounting involves evaluating past performance. Financial results demonstrate business success to both shareholders and the public. Planning and preparing for the future, however, is just as important.

Shareholders must be reassured that a business has been, and will continue to be, successful. This requires financial forecasting.

Here's an overview of how to use pro forma statements to conduct financial forecasting, along with seven methods you can leverage to predict a business's future performance.

What Is Financial Forecasting?

Financial forecasting is predicting a company’s financial future by examining historical performance data, such as revenue, cash flow, expenses, or sales. This involves guesswork and assumptions, as many unforeseen factors can influence business performance.

Financial forecasting is important because it informs business decision-making regarding hiring, budgeting, predicting revenue, and strategic planning . It also helps you maintain a forward-focused mindset.

Each financial forecast plays a major role in determining how much attention is given to individual expense items. For example, if you forecast high-level trends for general planning purposes, you can rely more on broad assumptions than specific details. However, if your forecast is concerned with a business’s future, such as a pending merger or acquisition, it's important to be thorough and detailed.

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Forecasting with Pro Forma Statements

A common type of forecasting in financial accounting involves using pro forma statements . Pro forma statements focus on a business's future reports, which are highly dependent on assumptions made during preparation⁠, such as expected market conditions.

Because the term "pro forma" refers to projections or forecasts, pro forma statements apply to any financial document, including:

• Income statements
• Balance sheets
• Cash flow statements

These statements serve both internal and external purposes. Internally, you can use them for strategic planning. Identifying future revenues and expenses can greatly impact business decisions related to hiring and budgeting. Pro forma statements can also inform endeavors by creating multiple statements and interchanging variables to conduct side-by-side comparisons of potential outcomes.

Externally, pro forma statements can demonstrate the risk of investing in a business. While this is an effective form of forecasting, investors should know that pro forma statements don't typically comply with generally accepted accounting principles (GAAP) . This is because pro forma statements don't include one-time expenses—such as equipment purchases or company relocations—which allows for greater accuracy because those expenses don't reflect a company’s ongoing operations.

7 Financial Forecasting Methods

Pro forma statements are incredibly valuable when forecasting revenue, expenses, and sales. These findings are often further supported by one of seven financial forecasting methods that determine future income and growth rates.

There are two primary categories of forecasting: quantitative and qualitative.

Quantitative Methods

When producing accurate forecasts, business leaders typically turn to quantitative forecasts , or assumptions about the future based on historical data.

1. Percent of Sales

Internal pro forma statements are often created using percent of sales forecasting . This method calculates future metrics of financial line items as a percentage of sales. For example, the cost of goods sold is likely to increase proportionally with sales; therefore, it’s logical to apply the same growth rate estimate to each.

To forecast the percent of sales, examine the percentage of each account’s historical profits related to sales. To calculate this, divide each account by its sales, assuming the numbers will remain steady. For example, if the cost of goods sold has historically been 30 percent of sales, assume that trend will continue.

2. Straight Line

The straight-line method assumes a company's historical growth rate will remain constant. Forecasting future revenue involves multiplying a company’s previous year's revenue by its growth rate. For example, if the previous year's growth rate was 12 percent, straight-line forecasting assumes it'll continue to grow by 12 percent next year.

Although straight-line forecasting is an excellent starting point, it doesn't account for market fluctuations or supply chain issues.

3. Moving Average

Moving average involves taking the average—or weighted average—of previous periods⁠ to forecast the future. This method involves more closely examining a business’s high or low demands, so it’s often beneficial for short-term forecasting. For example, you can use it to forecast next month’s sales by averaging the previous quarter.

Moving average forecasting can help estimate several metrics. While it’s most commonly applied to future stock prices, it’s also used to estimate future revenue.

To calculate a moving average, use the following formula:

A1 + A2 + A3 … / N

Formula breakdown:

A = Average for a period

N = Total number of periods

Using weighted averages to emphasize recent periods can increase the accuracy of moving average forecasts.

4. Simple Linear Regression

Simple linear regression forecasts metrics based on a relationship between two variables⁠: dependent and independent. The dependent variable represents the forecasted amount, while the independent variable is the factor that influences the dependent variable.

The equation for simple linear regression is:

Y ⁠ = Dependent variable⁠ (the forecasted number)

B = Regression line's slope

X = Independent variable

A = Y-intercept

5. Multiple Linear Regression

If two or more variables directly impact a company's performance, business leaders might turn to multiple linear regression . This allows for a more accurate forecast, as it accounts for several variables that ultimately influence performance.

To forecast using multiple linear regression, a linear relationship must exist between the dependent and independent variables. Additionally, the independent variables can’t be so closely correlated that it’s impossible to tell which impacts the dependent variable.

Qualitative Methods

When it comes to forecasting, numbers don't always tell the whole story. There are additional factors that influence performance and can't be quantified. Qualitative forecasting relies on experts’ knowledge and experience to predict performance rather than historical numerical data.

These forecasting methods are often called into question, as they're more subjective than quantitative methods. Yet, they can provide valuable insight into forecasts and account for factors that can’t be predicted using historical data.

6. Delphi Method

The Delphi method of forecasting involves consulting experts who analyze market conditions to predict a company's performance.

A facilitator reaches out to those experts with questionnaires, requesting forecasts of business performance based on their experience and knowledge. The facilitator then compiles their analyses and sends them to other experts for comments. The goal is to continue circulating them until a consensus is reached.

7. Market Research

Market research is essential for organizational planning. It helps business leaders obtain a holistic market view based on competition, fluctuating conditions, and consumer patterns. It’s also critical for startups when historical data isn’t available. New businesses can benefit from financial forecasting because it’s essential for recruiting investors and budgeting during the first few months of operation.

When conducting market research, begin with a hypothesis and determine what methods are needed. Sending out consumer surveys is an excellent way to better understand consumer behavior when you don’t have numerical data to inform decisions.

Improve Your Forecasting Skills

Financial forecasting is never a guarantee, but it’s critical for decision-making. Regardless of your business’s industry or stage, it’s important to maintain a forward-thinking mindset—learning from past patterns is an excellent way to plan for the future.

If you’re interested in further exploring financial forecasting and its role in business, consider taking an online course, such as Financial Accounting , to discover how to use it alongside other financial tools to shape your business.

Do you want to take your financial accounting skills to the next level? Consider enrolling in Financial Accounting —one of three courses comprising our Credential of Readiness (CORe) program —to learn how to use financial principles to inform business decisions. Not sure which course is right for you? Download our free flowchart .

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• Sales forecasting: How to create a sale ...

Sales forecasting: How to create a sales forecast template (with examples)

A strong sales team is the key to success for most companies. They say a good salesperson can sell sand at the beach, but whether you’re selling products in the Caribbean or Antarctica, it all comes down to strategy. When you’re unsure if your current strategy is working, a sales forecast can help.

What is a sales forecast?

A sales forecast predicts future sales revenue using past business data. Your sales forecast can predict a number of different things, including the number of new sales for an existing product, the new customers you’ll gain, or the memberships you’ll sell in a given time period. These forecasts are then used during project planning to determine how much you should allocate towards new products and services. 

Why is sales forecasting important?

Sales forecasting helps you keep a finger on your business’s pulse. It sets the ground rules for a variety of business operations, including your sales strategy and project planning. Once you calculate your sales projections, you can use the results to assess your business health, predict cash flow, and adjust your plans accordingly.

An effective sales forecasting plan:

Predicts demand: When you have an idea of how many units you may sell, you can get a head start on production.

Helps you make smart investments: If you have future goals of expanding your business with new locations or products, knowing when you’ll have the income to do so is important. 

Contributes to goal setting: Your sales forecast can help you set goals outside of investments as well, like outshining competitors or hiring new team members.

Guides spending: Your sales forecast may be the wake-up call you need to set a budget and use cost control to reduce expenses.

Improves the sales process: You can change your current sales process based on the sales projections you’re unhappy with.

Highlights financial problems: Your sales forecast template will open your eyes to problem areas you may not have noticed otherwise. 

Helps with resource management: Do you have the resources you need to fill orders if it’s an accurate sales forecast? Your sales forecast can guide how you allocate and manage resources to hit targets.

When you have an accurate prediction of your future sales, you can use your projections to adjust your current sales process.

Sales forecasting methods

Sales forecasting is an important part of strategic business planning because it enables sales managers and teams to predict future sales and make informed decisions. But why are there multiple sales forecasting methods? Simply put, businesses vary in size, industry, and market dynamics, so no single methodology suits all.

Choosing the right sales forecasting method is more of an art than a science. It involves:

Analyzing your business size and industry

Assessing the available data and tools

Understanding your sales cycle's complexity

A few telltale signs that you've picked the correct approach include:

Improved accuracy in sales target predictions

Enhanced understanding of market trends

Better alignment with your business goals

Opportunity stage forecasting

Opportunity stage forecasting is a dynamic approach ideal for businesses using CRM systems like Salesforce. It assesses the likelihood of sales closing based on the stages of the sales pipeline. This method is particularly beneficial for sales organizations with a clearly defined sales process.

For example, a software company might use this method to forecast sales by examining the number of prospects in each stage of their funnel, from initial contact to final negotiation.

Pipeline forecasting method

The pipeline forecasting method is similar to opportunity stage forecasting but focuses more on the volume and quality of leads at each pipeline stage. It's particularly useful for businesses that rely heavily on sales forecasting tools and dashboards for decision-making.

A real estate agency could use it by examining the number of properties listed, the stage of negotiations, and the number of closings forecasted in the pipeline.

Length of sales cycle forecasting

Small businesses often prefer the length of sales cycle forecasting. It's straightforward and involves analyzing the duration of past sales cycles to predict future ones. This method is effective for businesses with consistent sales cycle lengths.

A furniture manufacturer, for instance, might use this method by analyzing the average time taken from initial customer contact to closing a sale in the past year.

Intuitive forecasting

Intuitive forecasting relies on the expertise and intuition of sales managers and their teams. It's less about spreadsheets and more about market research and understanding customer behavior. This method is often used with other, more data-driven approaches.

A boutique fashion store, for example, might use this method, relying on the owner's deep understanding of fashion trends and customer preferences.

Historical forecasting

Historical forecasting uses past performance data to predict future sales. This method is advantageous for businesses with ample historical sales data. It's less effective for new markets or rapidly changing industries.

An established book retailer could use historical data from previous years, considering seasonal trends and past marketing campaigns, to forecast next quarter's sales.

Multivariable analysis forecasting

Multivariable analysis forecasting is a more sophisticated method that's ideal for larger sales organizations. It analyzes factors like market trends, economic conditions, and marketing efforts to provide a holistic view of potential sales outcomes.

An automotive company, for example, could analyze factors like economic conditions, competitor activity, and past sales data to forecast future car sales.

How to calculate sales forecast

Sales forecasts determine how much you expect to do in sales for a given time frame. For example, let’s say you expect to sell 100 units in Q1 of fiscal year 2024. To calculate sales forecasts, you’ll use past data to predict future trends. 

When you’re first creating a forecast, it’s important to establish benchmarks that determine how much you normally sell of any given product to how many people. Compare historical sales data against sales quotas—i.e., how much you sold vs. how much you expected to sell. This type of analysis can help you set a baseline for what you expect to achieve every week, month, quarter, and so on.

For many companies, this means establishing a formula. The exact inputs will vary based on your products or services, but generally, you can use the following:

Sales forecast = Number of products you expect to sell x The value of each product

For example, if you sell SaaS products, your sales forecast might look something like this: 

SaaS FY24 Sales forecast = Number of expected subscribers x Subscription price

Ultimately, the sales forecasting process is a guess—but it’s an educated one. You’ll use the information you already have to create a data-driven forecasting model. How accurate your forecast is depends on your sales team. The sales team uses facts such as their prospects, current market conditions, and their sales pipeline. But they will also use their experience in the field to decide on final numbers for what they think will sell. Because of this, sales leaders are more likely to have better forecasting accuracy than new members of the sales team.

Sales forecast vs. sales goal

Your sales forecast is based on historical data and current market conditions. While you always hope your sales goals are attainable—and you can use data to estimate what your team is capable of—your goals might not line up directly with your forecast. This can be for a number of reasons, including wanting to create stretch goals that push your sales team beyond what they’ve done in the past or big, pie-in-the-sky goals that boost investor confidence.

How to create a sales forecast

There are different sales forecasting methods, and some are simpler than others. With the steps below, you’ll have a basic understanding of how to create a sales forecast template that you can customize to the method of your choice. 

1. Track your business data

Without details from your past sales, you won’t have anything to base your predictions on. If you don’t have past sales data, you can begin tracking sales now to create a sales forecast in the future. The data you’ll need to track includes:

Number of units sold per month

Revenue of each product by month

Number of units returned or canceled (so you can get an accurate sales calculation)

Other items you can track to make your predictions more accurate include:

Growth percentage

Number of sales representatives

Average sales cycle length

There are different ways to use these data points when forecasting sales. If you want to calculate your sales run rate, which is your projected revenue for the next year, use your revenue from the past month and multiply it by 12. Then, adjust this number based on other relevant data points, like seasonality.

Tip: The best way to track historical data is to use customer relationship management (CRM) software. When you have a CRM strategy in place, you can easily pull data into your sales forecast template and make quick projections.

2. Set your metrics

Before you perform the calculations in your sales forecast template, you need to decide what you’re measuring. The basic questions you should ask are:

What is the product or service you’re selling and forecasting for? Answering this question helps you decide what exactly you’re evaluating. For example, you can investigate future trends for a long-standing product to decide whether it’s worth continuing, or you can predict future sales for a new product. 

How far in the future do you want to make projections? You can decide to make projections for as little as six months or as much as five years in the future. The complexity of your sales forecast is up to you.

How much will you sell each product for, and how do you measure your products? Set your product’s metrics, whether they be units, hours, memberships, or something else. That way, you can calculate revenue on a price-per-unit basis.

How long is your sales cycle? Your sales cycle—also called a sales funnel—is how long it takes for you to make the average sale from beginning to end. Sales cycles are often monthly, quarterly, or yearly. Depending on the product you’re selling, your sales cycle may be unique. Steps in the sales cycle typically include:

Lead generation

Lead qualification

Initial contact

Making an offer

Negotiation

Closing the deal

Tip: You can still project customer growth versus revenue even if your company is in its early phases. If you don’t have enough historical data to use for your sales forecast template, you can use data from a company similar to yours in the market. 

3. Choose a forecasting method

While there are many forecasting methods to choose from, we’ll concentrate on two straightforward approaches to provide a clear understanding of how sales forecasting can be implemented efficiently. The top-down method starts with the total size of the market and works down, while the bottom-up method starts with your business and expands out.

Top-down method: To use the top-down method, start with the total size of the market—or total addressable market (TAM). Then, estimate how much of the market you think your business can capture. For example, if you’re in a large, oversaturated market, you may only capture 3% of the TAM. If the total addressable market is $1 billion, your projected annual sales would be $30 million. 

Bottom-up method: With the bottom-up method, you’ll estimate the total units your company will sell in a sales cycle, then multiply that number by your average cost per unit. You can expand out by adding other variables, like the number of sales reps, department expenses, or website views. The bottom-up forecasting method uses company data to project more specific results. 

You’ll need to choose one method to fill in your sales forecast template, but you can also try both methods to compare results.

Tip: The best forecasting method for you may depend on what type of business you’re running. If your company experiences little fluctuation in revenue, then the top-down forecasting method should work well. The top-down model can also work for new businesses that have little business data to work with. Bottom-up forecasting may be better for seasonal businesses or startups looking to make future budget and staffing decisions.

4. Calculate your sales forecast

You’ve already learned a basic way to calculate revenue using the top-down method. Below, you’ll see another way to estimate your projected sales revenue on an annual scale.

Divide your sales revenue for the year so far by the number of months so far to calculate your average monthly sales rate.

Multiply your average monthly sales rate by the number of months left in the year to calculate your projected sales revenue for the rest of the year.

Add your total sales revenue so far to your projected sales revenue for the rest of the year to calculate your annual sales forecast.

A more generalized way to estimate your future sales revenue for the year is to multiply your total sales revenue from the previous year.

Example: Let’s say your company sells a software application for $300 per unit and you sold 500 units from January to March. Your sales revenue so far is $150,000 ($300 per unit x 500 units sold). You’re three months into the calendar year, so your average monthly sales rate is $50,000 ($150,000 / 3 months). That means your projected sales revenue for the rest of the year is $450,000 ($50,000 x 9 months).

5. Adjust for external factors

A sales forecast predicts future revenue by making assumptions about your growth rate based on past success. But your past success is only one component of your growth rate. There are external factors outside of your control that can affect sales growth—and you should consider them if you want to make accurate projections. 

Some external factors you can adjust your calculations around include:

Inflation rate: Inflation is how much prices increase over a specific time period, and it usually fluctuates based on a country’s overall economic state. You can take your annual sales forecast and factor in inflation rate to ensure you’re not projecting a higher or lower number of sales than the economy will permit.

The competition: Is your market becoming more competitive as time goes on? For example, are you selling software during a tech boom? If so, assess whether your market share will shrink because of rising competition in the coming year(s).

Market changes: The market can shift as people change their behavior. Your audience may spend an average of six hours per day on their phones in one year. In the next year, mental health awareness may cause phone usage to drop. These changes are hard to predict, so you must stay on top of market news.

Industry changes: Industry changes happen when new products and technologies come on the market and make other products obsolete. One instance of this is the invention of AI technology.

Legislation: Although not as common, changes in legislation can affect the way companies sell their products. For example, vaping was a multi-million dollar industry until laws banned the sale of vape products to people under the age of 21. 

Seasonality: Many industries experience seasonality based on how human behavior and human needs change with the seasons. For example, people spend more time inside during the winter, so they may be on their computers more. Retail stores may also experience a jump in sales around Christmas time.

Tip: You can create a comprehensive sales plan to set goals for team members. Aside from revenue targets and training milestones, consider assigning each of these external factors to your team members so they can keep track of essential information. That way, you’ll have your bases covered on anything that may affect future sales growth. 

Sales forecast template

Below you’ll see an example of a software company’s six-month sales forecast template for two products. Product one is a software application, and product two is a software accessory. 

In this sales forecast template, the company used past sales data to fill in each month. They projected their sales would increase by 10% each month because of a 5% increase in inflation and because they gained 5% more of the market. They kept their price per unit the same as the previous year.

Putting both products in the same chart can help the company see that their lower-cost product—the software accessory—brings in more revenue than their higher-cost product. The company can then use this insight to create more low-cost products in the future.

Sales forecast examples

Sales forecasting is not a one-size-fits-all process. It varies significantly across industries and business sizes. Understanding this through practical examples can help businesses identify the most suitable forecasting method for their unique needs.

Sales forecasting example 1: E-commerce

In the e-commerce sector, where trends can shift rapidly, intuitive forecasting is often useful for making quick, informed decisions.

Scenario: An e-commerce retailer specializing in fashion accessories is planning for the upcoming festive season.

Trend analysis phase: The team spends the first week analyzing customer feedback and current fashion trends on social media, using intuitive forecasting to predict which products will be popular.

Inventory planning phase: Based on these insights, the next three weeks are dedicated to selecting and ordering inventory, focusing on products predicted to be in high demand.

Sales monitoring and adjustment: As the holiday season approaches, the team closely monitors early sales data, ready to adjust their inventory and marketing strategies based on real-time sales performance.

This approach allows the e-commerce retailer to stay agile , adapting quickly to market trends and customer preferences.

Sales forecasting example 2: Software development

For a software development company, especially one working with B2B clients, opportunity stage forecasting can help predict sales and manage the sales pipeline effectively.

Scenario: A software development company is launching a new project management tool.

Lead generation and qualification phase: In the initial month, the sales team focuses on generating leads, qualifying them, and categorizing potential clients based on their progress through the sales pipeline.

Proposal and negotiation phase: For the next two months, the team works on creating tailored proposals for high-potential leads and enters negotiation stages, using opportunity stage forecasting to predict the likelihood of deal closures.

Closure and review: In the final phase, the team aims to close deals, review the accuracy of their initial forecasts, and refine their approach based on the outcomes.

Opportunity stage forecasting enables the software company to efficiently manage its sales pipeline , focusing resources on the most promising leads and improving their chances of successful deal closures.

Pair your sales forecast with a strong sales process

A sales forecast is only one part of the larger sales picture. As your team members acquire leads and close deals, you can track them through the sales pipeline. A solid sales plan is the foundation of future success.  

Related resources

Solve your tech overload with an intelligent transformation

9 steps to craft a successful go-to-market (GTM) strategy

Unmanaged business goals don’t work. Here’s what does.

How Asana uses work management to effectively manage goals

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3 Revenue Forecasting Models for Accurate Revenue Predictions

Jerusha Songate on April 27, 2021

Table of Contents

More baremetrics articles.

Revenue forecasting models help you plan your next phase of growth. Financial models also help you plan how to pivot in response to certain scenarios, like a sudden drop-off in sales or an unexpected surge in demand.

The Baremetrics article  “The SaaS Financial Model You’ll Actually Use”  describes how to create financial models you can use to plan out your next steps—even when your total revenue falls short and things don’t go as expected.

Let’s take a deep dive into why accurate forecasting is an essential business tool, and how you can get started using it to predict future sales. We’ll review the forecasting process and three specific forecasting techniques that may offer the insight you need for revenue projections.

Ready to go to the next level with your forecasting metrics? Sign up for a free trial of Baremetrics today!

What is Revenue Forecasting?

Revenue forecasting is predicting how much revenue you expect to make over a certain period. Those periods range from a quarter (3 months) to a full year.

This process is not just a guess about how much money your business will generate, but some experts admit that, for a startup, revenue forecasting is  more of an art than a science .

Other commentators distinguish between  judgment forecasting —based on intuition and anecdotal evidence—and quantitative forecasting—based on current and historical data. Ideally, data drives your revenue forecasts.

Want to make the most out of the sales data your company collects? Sign up for a Baremetrics free trial today!

Importance of Revenue Forecasting Models

Revenue forecasting models offer a method for predicting revenue. They allow you to move beyond personal judgment—your “best guess” of the success of your sales process—toward quantitative analysis.

Of course, hard data isn’t always possible. If it’s your business’s first year, you may have to rely on intuitive forecasting. Often that comes from your salespeople’s assessment of the likelihood that leads will pan out.

Forecasting models are important because they drive decision-making in your business. They influence your decisions to hire more people, expand into new markets, and set goals for upcoming quarters.

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Use Baremetrics to measure churn, LTV and other critical business metrics that help them retain more customers. Want to try it for yourself?

Three Methods of Revenue and Sales Forecasting

Here are three ways to rely on proven methods of predicting revenue, and develop a picture of your company’s success.

1. Opportunity stage forecasting

This method predicts revenue based on your current prospects. It uses historical data to add a numerical value to each prospect given their stage in the sales journey. The further they are down your sales pipeline, the greater the chances the deal will close.

As an example, assume that over the past two quarters, 60 percent of customers who reached the stage of signing up for a free trial eventually purchased a subscription.

You can use this forecasting method to predict that 60 percent of prospects currently enrolled in a free trial will subscribe. Using this figure, you can forecast your revenue.

In theory, you can predict your revenue based on any opportunity stage. But the further down in the funnel they are, the more accurate the forecast becomes. That’s because you know more about these potential clients, enough to predict future revenue.

There are potential flaws in this method. It does not consider the  age of each prospect . An older lead, or someone who lingers before reaching the stage of the free trial, is perhaps less likely to commit than one who goes through the early stages quickly. Opportunity stage forecasting treats both prospects equally.

2. Test market analysis forecasting

This method helps you to predict revenue based on the projected interest in a product. The process involves rolling out a product or service to a test market and reviewing the results. This is a particularly valuable method for startups who may not have historical data to draw from.

An example of a test market can be a rollout to a small segment of consumers or businesses. Crowdfunding campaigns, such as Kickstarter or Indiegogo, are one form of test marketing.

This method also has its drawbacks. There is no guarantee your product will perform as well in an open market as it did in your test market. Before using this method, it is wise to use additional data that considers competition in your industry and the buying habits of your target consumers.

3. Historical forecasting

This is a straightforward revenue forecasting model.  Historical forecasting  assumes that whatever has happened in the past will continue to happen.

As an example, say your revenue was $100,000 in January. Historical forecasting assumes revenue will also reach $100,000 in February and subsequent months.

There are some drawbacks to this method as well. Although it draws on historical reality, it assumes a lot about the future. First, that sales are steady and  monthly recurring revenue doesn’t contract or expand. They don’t go down or go up. Second, it does not take into account natural fluctuations, like seasonality, changes in customer demand, or growth as the result of your sales team’s efforts.

There are ways to modify this method to make it more accurate. You can look at trends over the past 6 months to a year. This should show a moving average that considers seasonal changes and  revenue growth  rate.

You can then change your sales forecast projections accordingly by starting with average sales rates that are a more accurate sales picture for your business.

The month-by-month comparison may serve as a benchmark rather than as a straightforward method that ensures forecast accuracy.

How Baremetrics Helps!

Baremetrics uses real data points from your business to help you make smart predictions.

The forecasting tool  is your go-to resource for revenue predictions you can rely on for budgeting and operational decisions.

Baremetrics analytics and insights give you access to powerful data sets about your customers that you can use to create financial models  to build your business.

To learn more about Baremetrics , sign up for a free trial today.

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Revenue Forecasting Models | 101 Guide To Revenue Forecasts

Revenue forecasting is critical for any business, especially when it comes to B2B SaaS. The immense speed of progress in this industry requires keeping up with trends, continuously experimenting with fresh channels, and adjusting budget allocation based on future predicted revenue. 

Accurate revenue forecasts help organizations make data-driven growth decisions.

This comprehensive guide will cover everything you need to know about revenue forecasting models .

What is Revenue Forecasting?

Revenue forecasting is the process of predicting future revenue for a company using historical performance data, predictive modeling, and qualitative insights. Revenue forecasts provide an estimated projection of the total revenues expected in a future period.

Forecast time horizons can range from next month to next quarter to five years from now . Short-term forecasts may focus on immediate sales pipeline conversion, while long-range forecasts take a broader market-based approach.

With revenue forecasting, the goal is to provide the most accurate prediction of future revenue based on current insights. These reports can also be improved by leveraging attribution data so you know exactly what functions of marketing or sales bring in real revenue.

Revenue forecasting helps answer questions like:

• How much revenue can we expect to generate in the next quarter/year?
• How will seasonality trends and new product launches impact revenue?
• How quickly are we expected to grow over the next 5 years?

When done right, revenue forecasting can power key business functions:

• Financial planning : Building P&L statements, budgets, valuation
• Sales planning : Setting quotas, territory mapping, compensation
• Marketing planning : Demand generation budgeting, growth modeling
• HR planning : Hiring goals, resource allocation across teams
• Manufacturing planning : Inventory needs, capacity expansion
• Executive planning : Strategy setting, investment decisions

While revenue forecasting attempts to predict future revenues, it differs from a revenue projection which is typically more aspirational. Let’s understand the differences. 

Revenue Forecasting vs. Revenue Projections vs. Sales Forecasts

These three terms are used quite often when it comes to budgeting and strategic planning but they mean different things. 

• Revenue Forecasts model the actual monetary revenue expected based on sales forecasts, historic performance, market conditions and statistical modeling. It provides the most likely, evidence-based scenario.
• Revenue Projections are what leadership desires to happen—an optimistic target rather than a data-driven expectation. Projections represent an aspirational revenue goal.
• Sales Forecasts predict expected sales bookings and pipelines based on leading indicators like open opportunities. They are an input into revenue forecasts.

Now, let’s understand the types of revenue forecasts that you may come across. 

Key Types of Revenue Forecasts

There are also different types of revenue forecasts based on methodology and time span:

• Short-term vs. Long-term - Short-term forecasts focus on immediate pipeline conversion, while long-term forecasts take a broader market-based view.
• Top-down vs. Bottom-up - Top-down forecasting starts with macro assumptions and allocates them across business units. Bottom-up rolls-up forecasts built from ground realities.
• Operational vs. Financial - Operational forecasts model near-term revenue streams. Financial forecasts take a holistic P&L view including costs and expenses.
• Deterministic vs. Probabilistic - Deterministic forecasts provide a single expected outcome. Probabilistic forecasts model a range of outcomes and probabilities.

Now, let's examine some key business uses and benefits of revenue forecasting. 

Why is revenue forecasting important?  

Accurate revenue forecasts can be the difference between success and failure for a business. Here are a few ways forecasting powers planning across the organization:

1. Budgeting with Realistic Precision

For finance teams, the single biggest use of forecasts is to build organization-wide budgets.

Budgets dictate how much gets spent on everything from R&D investments to marketing programs and payroll. Without reliable revenue forecasts, budgets devolve into guesswork.

For example, assume a company's revenue was $5M last year. Now the CFO needs to build next year's budget.

With intelligent forecasts , finance can model that based on new product launches, a 10% industry growth rate, and sales team expansions, revenues are likely to reach around $7.5M next year.

The CFO can now budget for expenses accordingly - say $1M for new engineering hires, $500K for more marketing, $150K for sales operations software etc.

Without forecasts, the CFO is flying blind . Maybe she pads the budget with a 20% increase to $6M. But if actual revenues only end up at $5.5M, suddenly there's a multi-hundred thousand dollar budget shortfall, requiring drastic cuts.

Conversely, if revenues actually reach $8M but budgets are based on last year's numbers, the company is now missing key growth opportunities due to under-investment. 

‍ 2. Optimize Operations Management

Beyond budgets, forecasts guide operational decisions across departments:

• Sales : Forecasts feed territory assignments, quota setting, compensation planning, and capacity modeling whereas under-forecasting leaves money on the table.
• Marketing : Forecasts dictate digital and outbound campaign budgets and funnel targets where bad forecasts can waste spending and lead to missed opportunities.
• Product : Prioritizing the roadmap requires expected revenues from new features so bad forecasts can result in misplaced priorities.
• HR : Hiring and workforce planning requires expected growth rates and flimsy forecasts risk talent shortages or bloat.

Across the board, teams depend on forecasts to optimize operational management for future success amid constraints.

3. Fuel Strategic Decisions

Forecasts also provide the quantified confidence executives need to drive growth through major strategic moves:

• Funding rounds : Forecasts build credibility on growth potential to establish valuations. Weak forecasts undermine bids for capital.
• M&A valuation : Pre-transaction due diligence depends on target revenue forecasts. Bad forecasts lead to overpayment or lost deals.
• Market expansion : Breaking into new regions or verticals requires quantifying addressable revenues and investment payback.
• New product prioritization : High-impact opportunities are identified by revenue potential under constrained resources.
• Executive recruitment : Attracting star senior talent requires painting a compelling growth.

Creating reliable revenue forecasts empowers executives to place decisive strategic bets amid uncertainties, as opposed to shooting blind.

4. Track Performance to Plan

Revenue forecasts also provide a scorecard against which actual results can be monitored. Comparing real revenue performance vs. forecasted expectations then allows deviations to be easily flagged. With this information at hand, teams can course-correct before small misses snowball into major disasters.

Without forecasts as the reference point, there is no way to reliably track progress against potential. Revenue actuals in a vacuum don't reveal whether performance is on-target or off-course.

What are the types of revenue forecast models?

Now that we understand the fundamentals of revenue forecasting, let's examine some of the most common revenue forecasting models and techniques.

Broadly, forecasting approaches can be divided into two families :

• Quantitative models take a data-driven statistical approach to identifying trends and patterns in historical data that can be used for future predictions.
• Qualitative models incorporate expert perspectives, market analyses and contextual business insights to predict future revenues.

There are four common forecasting models namely linear regression, time series, bottom-up, and top-down. The best way to perform revenue forecasting is by combining multiple models to benefit from each of them.

Let's explore some of these popular models.

1. Linear Regression Models

Linear regression analyzes historical data to model how changes in key variables impact revenue. 

Regression provides a data-backed view into drivers of revenue growth and contraction. 

However, regression models are only as good as the input data. They may miss complex real-world dynamics that are not reflected in historical data. Approaching them as helpful guiding tools rather than absolute truth is important.

Key Benefits

• Quantifies the relationship between revenue drivers and outcomes
• Calculates the impact of each variable on revenues
• Models complex interactions between multiple variables
• Provides data-driven revenue projections

How It Works

Simple linear regression uses one variable, often time, to predict revenue.

For example, it can help a business quantify how much additional revenue every $1 increase in marketing spend has historically generated. This insight can be used to forecast revenue under different scenarios.

 Multiple linear regression incorporates additional factors simultaneously like marketing spend, sales activities, market dynamics etc.

The model examines historical data to calculate coefficients measuring each variable's unique relationship with revenue. These insights feed the predictive model to forecast expected revenue under different scenarios.

Considerations

• Regression modeling requires large volumes of accurate historical data
• Predictive power diminishes beyond modeled relationships
• Difficult to model nonlinear variable interactions

Regression provides a data-backed view into drivers of revenue growth and contraction. It brings statistical rigor to projecting the top and bottom-line impact of decisions around pricing, hiring, product launches, geographical expansion and more. 

However, these models are only as good as the input data . They may miss complex real-world dynamics that are not reflected in historical data. Approaching them as helpful guiding tools rather than absolute truth is important.

2. Time Series Forecasting

Time series analysis detects historical patterns in data over time. This helps tease out seasonal and cyclical trends from broader growth trajectories and random noise.

It decomposes revenue time series into:

• Trend - Overall upward/downward trajectory
• Seasonality - Cyclical patterns
• Noise - Random unexplained variations

Time series models maximize signals and minimize noise in historical data for sophisticated revenue projections tailored to the business. These models can incorporate recent data, balancing responsiveness to change with smoothing noise and help you extract actionable insights for reporting and forecasting.

• Models trends and seasonality specific to the business
• Highlights time-based nuances impacting revenue
• Provides granular, frequently updating forecasts

Time series techniques like moving averages, exponential smoothing, and ARIMA modeling analyze a revenue time series to optimize the predictive modeling of its components. 

For example, enterprise software revenues may spike every fourth quarter due to a year-end budget flush. Media subscriptions may dip in the summer months when travel is high. Understanding these nuances helps make more contextual and accurate forecasts.

You can then use the insights generated from the time series forecasts to smoothen the growth curve giving you more predictable revenue. 

Time series models need sufficient history to detect reliable patterns. They may miss entirely new market dynamics or one-off events, unlike the past. Hence, combining them with human judgment is important.

3. Bottom-Up Forecasting

Bottom-up forecasting taps insights from sales, account management and other frontline teams to build projections. They incorporate pipeline health, competitive threats, and market mood along with historical data.

Let’s take an example organization with sales, marketing, finance , and leadership teams. Here’s how bottom-up forecasting would work:

• The sales team starts by analyzing the health of its current pipeline and expected deal cycles to forecast expected conversion rates by product line and region.
• Meanwhile, marketing examines recent campaign performance and lead generation trends to estimate new MQLs by campaign channel. They apply conversion rates to project new SQLs.
• Finance consolidates these detailed bottom-up forecasts from each department. They identify and resolve any inconsistent methodologies or assumptions between teams.
• Leadership reviews the consolidated forecast and makes final top-down adjustments to determine the official revenue projection.
• Incorporates insights from sales, account management, and other frontline teams
• Reflects pipeline health, competitive dynamics, and micro-market nuances
• Promotes buy-in through the inclusion of cross-functional inputs

Inconsistent assumptions between teams can skew the overall forecast. Guidance from leadership on industry outlook, macroeconomic factors and growth objectives helps align assumptions and methodologies.

4. Top-Down Forecasting

Top-down forecasting starts with the big-picture view of the total addressable market, growth trajectories, economic conditions and business strategy. Leadership sets goals and divides revenue targets across functions.

This ensures strategic alignment between long-term goals and short-term operations. However, seemingly arbitrary targets could demotivate teams without context on the rationale so with top-down forecasting, you need to ensure two-way communication and transparency from leadership.

Let’s look at top-down revenue forecasting through an example. 

• The executive/leadership team starts with the overall revenue growth target based on market outlook and strategic goals. They divide this target across sales, marketing and customer success based on revenue impact capacity.
• Each team gets their individual revenue target along with guidance on growth assumptions like pricing, conversions, expansions etc. 
• Teams build goal-aligned execution plans around sales territories , campaigns, and account targeting to meet their top-down number.
• Leadership reviews department plans to ensure coordination and consistent assumptions are in place.
• Teams lack insights into the rationale behind seemingly arbitrary targets
• Overlooks micro-market nuances and competitive dynamics
• Requires reconciliation of opposing projections

Blending both top-down and bottom-up approaches for revenue forecasting can help set realistic targets based on market conditions while aligning activities to growth objectives.

What is the Best Method for Revenue Forecasting?

The best forecasting method depends on your use case. Let’s understand this with two examples.

A SaaS company with recurring subscription revenue may find time series analysis to be very effective. That’s because, studying historical revenue patterns over time, seasonal cycles and trends become apparent. Statistical time series models can help quantify these patterns to accurately predict recurring revenues.

On the other hand, for a retail chain opening new store locations, a bottom-up approach could prove more useful. Each new store manager could prepare detailed forecasts for their location based on demographics, nearby competitors, marketing plans etc. Aggregating these bottom-up projections provides a realistic the overall revenue forecast.

The point is, every business is situated differently. The ideal approach depends on:

• Data availability - length of revenue history, presence of relevant drivers/variables
• Revenue characteristics - recurring/seasonal patterns, level of variability
• Business structure - centralized/decentralized, product diversity
• Strategic context - expanding to new markets/geographies, introducing major new offerings

Leaders need to understand revenue drivers in their industry and business and use the insights to tailor the forecasting methodology to their specific situation and objectives.

Combining methods can also be beneficial. For example, a short-term quarterly forecast may use time series analysis to leverage recent revenue trends. And for the annual budget, a bottom-up approach could then add local market perspectives for a comprehensive view.

The key is adapting forecasting approaches to match business realities which provides the accuracy and insights required for confident decision-making across the organization. 

Revenue Forecasting Models: Best Practices

What are some of the best practices for ensuring accurate revenue forecasting when using these revenue forecasting models? Let’s look at 4 of the best practices that you should consider following. 

1. Start with high-quality data

Remember this—garbage in, garbage out. Even the most advanced model cannot compensate for poor-quality data. Invest in processes and systems to collect accurate, complete revenue data, with proper change logs and auditing.

2. Eliminate outdated information

Stale data loses relevance quickly. Establish mechanisms to continually gather the latest data on revenue drivers. This could involve surveys, sales team feedback, customer interviews etc.

3. Reduce the length of planning cycles

Annual plans using old assumptions miss market shifts. Re-forecast more frequently using the latest data to stay agile. Quarterly or even monthly cycles are preferable.

4. Avoid a futile bid for perfection

Obsessing over tiny accuracy improvements is counterproductive beyond a point. Focus on balancing usefulness and cost when selecting model sophistication.

How Factors Can Help Your Business Drive Revenue

Let's face it—optimizing your GTM strategy is tedious, and time-consuming without having all the right data in one place.

You have your metrics in different silos across marketing, sales, and revenue and piecing together a complete picture feels impossible. You could have leaks in your funnel, but cannot find the exact pages. Attribution has become a shot in the dark. And you're pouring money into campaigns without knowing if they’re working or not.

This is where Factors comes in. 

Factors integrates all your disparate data sources—CRM, MAP, web analytics, social media, ad platforms—into one unified view. 

You can quickly pull custom reports to get insights and answers on the fly. Factors also leverages leading IP resolution technology to reveal anonymous website traffic . Helping you discover up to 64% of untapped traffic and turn them into known, sales-ready accounts. More accounts to market means more pipeline and revenue.

With unified data and a complete view of your funnel, you gain the power to make strategic decisions that move the revenue needle. Scale what works, fix leaks, attribute MQLs to campaigns, analyze account journeys—Factors has you covered.

Don’t shoot in the dark. Book a demo with Factors to see how we can help you get better insights and data to power your forecasting models and make data-driven decisions to boost pipeline and growth

1. What is revenue forecasting and why is it important?

Revenue forecasting is the process of predicting future revenue for a company using historical data, predictive modeling, and insights. Accurate forecasts empower data-driven planning and growth decisions across functions like finance, sales, marketing and operations. Reliable revenue forecasts are mission-critical for budgeting, managing operations, fueling strategic growth moves and tracking performance.

2. What are the top revenue forecasting models?

Popular models include linear regression to model revenue drivers, time series analysis leveraging historical patterns, bottom-up forecasting aggregating projections from frontline teams, and top-down forecasting starting with leadership’s total target. Combining approaches provides flexibility to tailor models to business needs and data availability.

3. How often should you update revenue forecasts?

Outdated assumptions lose relevance quickly, so forecasts should be refreshed frequently. Quarterly or monthly re-forecasting cycles are preferable to stay agile versus annual plans. Access to latest revenue driver data enables more responsive modeling.

4. What are some common pitfalls of revenue forecasting?

Potential pitfalls include unpredictable market shocks, limitations of available data, human errors in model assumptions, and finite resources to build sophisticated models. Perfection is unrealistic but maximizing useful accuracy is key.

5. What data is needed for accurate revenue forecasts?

Quality historical revenue data is the foundation. Relevant drivers like market trends, sales activities, product changes, and economic indicators help explain revenues. Updated inputs prevent stale assumptions. Data challenges need pragmatic solutions.

6. How can technology enable better revenue forecasts?

Tools like CRM, account intelligence and analytics tools like Factors , etc. provide key sales and marketing data inputs. Purpose-built FP&A software centralizes data for modeling and reporting. Technologies like AI and machine learning can boost forecasting sophistication.

7. What best practices improve revenue forecasting?

Best practices include maintaining high-quality data, eliminating outdated information, shortening planning cycles, combining modeling approaches, and focusing models on business needs. Avoid needless complexity but leverage enough sophistication to meet objectives.

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Revenue Forecasting & Planning Guide: 4 Models For Planning Your Top Line

Steve Groccia

Head of Customer Operations

Ask any finance leader what their toughest responsibilities are, and you’ll inevitably hear revenue forecasting near the top of the list.

No matter how many years of experience you have, each organization comes with unique inputs, processes, and source systems that make top-line forecasting a bespoke, often painful, part of business planning.

But it’s critical that finance pushes through the sleepless nights and headaches to nail down an accurate revenue forecast. Your company lives and dies by its ability to hit growth targets and revenue projections . And your top-line forecasts tie directly into your SaaS valuation  as VCs look to understand the trajectory of your business.

While revenue forecasting is a highly-customized process for each business, there are still certain principles, approaches, and best practices that every finance team  should understand. Here’s what you need to know to plan your top line (and make revenue forecasting a pain-free process with Mosaic).

Table of Contents

What Is Revenue Forecasting?

Revenue forecasting is the first step of any planning process in which you project future top-line growth with driver-based forecasting and assumptions that are most relevant to your business model.

An effective revenue forecast sets the stage for an entire budgeting cycle. It’s what aligns the entire business with growth goals, creates the foundation for each department’s budget, and sets the stage for informed decision-making.

There are multiple ways to model your top line. But before you worry about the nuts and bolts of modeling, you have to approach revenue forecasting as a project manager. There are three things to think about before you actually start the process of revenue planning:

• Timing. You’ll revisit your top-line plan consistently throughout the year. But the primary process ties directly to your annual planning cycle. For companies that end the year in December, you should be kicking off the revenue forecasting process in October, just after completing Q3. You have an idea of how the year will close out, and you can use that projected information to launch planning conversations about realistic/unrealistic growth.
• Philosophy. Are you a hyper-collaborative organization, or do plans take a more top-down path in your organization? If you’re going to frequently meet with department leaders, build that into your timeline because those conversations could extend the planning process. If your company is more direct with revenue expectations, you can have more streamlined talks with your salespeople to build the plan.
• Stakeholders. Prioritize alignment across necessary stakeholders as early as possible. What sales ops sees as the key drivers may not be the same as what the sales leader thinks — which may not be the same as what finance believes. The sooner you align with stakeholders on the approach to revenue planning, the smoother the process will be.

These pre-planning fundamentals are what could make the difference between revenue forecasts that inform an efficient, aligned growth plan vs. ones that miss the mark (setting your company back in the process).

Why Is Revenue Forecasting Important?

Revenue forecasting is important because it provides a concrete overview of your company’s growth path and allows you to make relevant business decisions . Revenue equals customers, customers inform hiring and product development, new customers and renewals equate to cash flow, and cash is the lifeblood of any business. So, your ability to accurately forecast and project revenue is critical to planning.

There are ripple effects of the revenue planning process that go beyond just projecting top-line momentum. Strong top-line planning also helps you:

• Verify the headcount plan . Headcount is typically the biggest expense for a small business (especially for SaaS companies). That’s why modeling out your headcount plan is just as crucial as your revenue plan. But without accurate forecasting, you risk having to push out staffing plans, which in turn sets product development back and prevents you from meeting your growth potential.
• Push the limits of customer acquisition costs . For earlier-stage startups, growth at all costs is almost essential as you fight to capture as much market share as possible. Accurate revenue forecasts give you a better idea of acceptable acquisition costs and give your marketing and sales teams more realistic budgets to attack the market opportunity.
• Build trust with investors. Presenting inaccurate revenue forecasts in your board deck quarter after quarter will erode trust. Instead of getting to tap into the strategic value of your board, you’ll spend entire board meetings trying to explain why your company can’t effectively map out its growth path. Maintaining clean, consistent revenue forecasts creates a foundation of trust between you and your investors.

Finance teams only unlock these advantages when they come up with the best possible approach to revenue planning for their organizations — and that starts with choosing the right model.

4 Revenue Forecasting Models to Plan Your Top Line

You’ll never find a one-size-fits-all financial model template  for top-line planning. But there are a few broad categories of revenue forecasting methods that you can adapt to your needs.

The following 4 revenue forecasting models cover both sides of the top-down vs. bottom-up budgeting  conversation, giving you an opportunity to triangulate results and ensure accuracy.

1. The Quota Capacity Model for Sales Forecasting

A sales capacity model (or a quota capacity model) is a bottom-up revenue forecasting method that uses historical data points for sales rep performance and ramp times to forecast future top-line growth.

Sales capacity models are effective for companies with sales-heavy go-to-market motions and a decent foundation of historical data. As long as your CRM setup  is clean, you’ll be able to build out an accurate sales ramp  waterfall that drives bookings projections based on your sales headcount plan.

In addition to your sales headcount plan and ramp rate, this model uses quota attainment for both ramping and ramped AEs to generate outputs for new bookings, billing, revenue, and collections.

Get started with a quota capacity model template

2. the arr snowball model.

The ARR snowball model is another popular method for SaaS revenue forecasting . It uses trends in ARR data to project future revenue growth, broken out into new ARR, upgrade ARR, downgrade ARR, and churned ARR.

Unlike a sales capacity model, earlier-stage companies can build out an ARR snowball without having the most granular historical data. Rather than needing deep insight into sales ramp rates and performance, you only need to see a recent trend in revenue growth to project next month, next quarter, next year, and beyond.

A sales capacity model is the truest form of a bottom-up approach to planning. The ARR snowball, on the other hand, is more of a blend of bottom-up and top-down. It leans on assumptions for things like seasonality, new customers, and average annual contract value  to drive revenue outputs. However, it’s not as deeply dependent on departmental collaboration as true bottom-up models.

Download an ARR snowball model template from our finance experts

3. the sales cycle to new bookings model.

The sales cycle to new bookings revenue forecasting method uses trends in sales cycle data to determine how many leads you need to generate to hit your business goals. Historical trends in opportunities created, deal conversion rates , days to close, and average bookings amounts help you create assumptions for new business in the coming months.

For a company that doesn’t have a large, mature sales function, this may be an easier approach to top-line planning than the sales capacity model. It’s also a simple way to sense-check your numbers if you primarily use a sales capacity model or an ARR snowball model to plan revenue.

4. The Bookings, Billings, and Collections Model

This simple top-down revenue forecasting model uses new customer counts and average revenue per customer to forecast net new bookings. Using historical net retention rates, you can forecast renewal bookings, billings, and collections.

Unlike the sales capacity model and ARR snowball model, this approach to revenue forecasting makes broader assumptions about business growth to model out high-level company goals.

The main advantage of this type of model is that finance can build it without much input from the rest of the business, speeding up the early stages of the planning process. As long as you can come up with a 3-month average ARR per customer and a 12-month average for net revenue retention , you can generate revenue predictions for your business.

(We’ll use this approach for our walkthrough of how to build a revenue forecasting model.)

How to Build a Revenue Forecasting Model in Mosaic

Just because Excel and Sheets are flexible enough to handle the highly-customized nature of top-line planning doesn’t mean they’re the best tools for the job.

The amount of time and effort you have to put into pulling data from source systems, updating complex webs of financial assumptions , and revising models based on ad hoc requests takes away from the strategic work you should be spending more time on.

Mosaic’s Topline Planner gives finance teams a blend of both worlds — the flexibility of spreadsheets with the real-time data necessary to plan at the pace of a high-growth company. Our new Topline Planner enables you to quickly build and maintain custom revenue forecasts using elements that are unique to your business. The cloud-based grid combines on-demand metrics with intuitive formulas to create a seamless modeling experience.

You can build out any of the revenue forecasting models listed above within the Mosaic platform. Here’s a walkthrough of the SaaS bookings , billings, and collections model to give you an idea of how it works.

Create Assumptions for Customer Count Growth and Average ARR Per Customer

This revenue forecasting model starts with projecting net new bookings based on new customer growth and average ARR per customer.

Start by creating a row in Mosaic that pulls in the Customer Count metric from your actuals. Then, forecast growth using the 3-month average and apply it forward over the forecast time period.

Then, you can create another new row that uses Average ARR per Customer as the actuals definition. If you plan to increase your average ARR over time, apply that growth rate. For example, you could use a per-month forecast method and assume ARR per Customer will grow 5% every 12 months.

Calculate Net New Bookings Based on Your Assumptions

Before you can calculate SaaS bookings, you need to know the change in customer count month-over-month. Add a line item to your top-line model that dynamically calculates customer changes using the formula method in Mosaic.

Now, create another row for Net New Bookings (ARR). Forecast this metric by multiplying Average ARR per Customer by Customer changes.

The result is an output of bookings for the new customers you expect to sign in each month during your forecast.

Model Your Renewal Bookings

The particular calculations in this step will depend on your business model. But for the example, let’s assume you have annual contracts that renew each year.

Add a Net Dollar Retention row, pulling in retention data for a 12-month lookback period that considers upsells, downsells, and churn. Use the per-month forecast method to forecast net dollar retention.

Add a placeholder row for Renewal Bookings that pulls in your bookings actuals. Then, add another row for Total Bookings that adds new and renewal bookings.

Go back to your Renewal Bookings row and forecast with a formula that accounts for your 12-month renewal cycle and calculates based on your average retention rate.

Calculate Billings and Collections

Once you’ve modeled net new and renewal bookings, you can build out calculations for billings and collections. Assume you bill your customers in the same month you book your deals. In that case, your billings forecast would be equal to your Total Bookings ARR line.

Then, build out assumptions for your collections schedule. A basic assumption might be that you’ll collect 75% on a Net 30 basis, another 20% two months later, and lose 5% of bookings as uncollectible.

Once you’ve finished modeling out your collections, you have a complete top-line model for the top-down scenario.

To check your forecast accuracy, you could also build out an ARR snowball or a sales capacity model to verify the numbers from a bottom-up perspective.

Create the Most Accurate Revenue Forecasts with Strategic Finance Software

It’s time to take top-line planning beyond the spreadsheet.

Finance teams don’t have time to fight against complex spreadsheets and point system data pulls to nail down their revenue forecasts. We believe revenue planning should be a simpler process, which is why we’re thrilled to release our Topline Planner.

When you use Mosaic for revenue forecasting, you can maximize speed and precision with:

• Direct connections to the metrics catalog. Access the full library of on-demand financial metrics  to accelerate modeling with real-time actuals.
• Intuitive formulas. Quickly create formulas with the help of a function library that has auto-complete features.
• Sheet-like formatting. Leverage the flexibility of spreadsheets with our dynamic grid, which lets you modify cells, copy/paste, and add rows with just a few clicks.
• Metric cross-reference. Connect top-line data to your income statement, balance sheet, and headcount planners for more dynamic forecasting and flexible budgeting processes.
• Simple scenario planning . Use scenario planning software to duplicate models and tweak assumptions to quickly sensitize your plans and see how different scenarios impact the business.
• One-click goal setup. Set forecasted topline metrics as goals and quickly access them in the Analysis Canvas dashboards to track your historical performance.

Want to learn more about how Mosaic takes the pain out of the typical high-stress top-line planning process? Reach out for a personalized demo  and find out how you can forecast revenue with ease.

Revenue Forecasting FAQs

How do you forecast revenue in excel.

Excel has a feature called “ Forecast Sheet ,” which allows you to create a forecast based on values corresponding with your date range. Based on these values over time, Excel will create a customizable revenue forecast. But more often than not, forecasting revenue in Excel means creating the right set of assumptions for projected performance and building formulas to calculate future revenue.

Unfortunately, the practicality of using Excel to project top-line growth is limited due to the need for manual revision of financial forecasting models and the lack of real-time data (which is why  financial forecasting software can be particularly valuable).

How do you forecast revenue in Google Sheets?

Google Sheets has a “ FORECAST ” formula to forecast revenue that can help create the most basic top-line projections. The forecast uses the total revenue of previous months to forecast the next month’s revenue, but it is limited in customizability and requires a lot of manual revision. Instead, forecasting revenue typically means creating the right set of assumptions and building out the formula logic to project future performance. Unlike other forecasting tools, Sheets does not deliver real-time data.

What is top line forecasting?

Top line forecasting, also known as revenue forecasting, is the process of modeling or predicting future revenue from sales of products and/or services. It’s important to know the difference between top line vs. bottom line growth .

Continue reading...

The snowball effect of financial assumptions, headcount modeling: template must-haves and the best tool, the latest mosaic insights, straight to your inbox, own the   of your business.

Business planning startup Pigment raises $145M in rare French tech mega-round

Paris-based startup Pigment has raised a $145 million funding round just five years after its inception. The enterprise software company offers a business planning platform for large companies to visualize their past financial performance and forecast upcoming quarters.

This funding round comes as a bit of a surprise as large rounds have been few and far between in France. According to a recent study from EY , funding rounds in the French tech ecosystem were down 38% in 2023 compared to 2022.

But if you remove buzzy AI startups like Mistral AI and capital-intensive infrastructure plays that are not really tech startups, like EV charging networks (Driveco) and EV battery factories (Verkor), funding rounds are drastically down. Pure software startups have had a rough couple of years.

Pigment appears as an exception with its Series D. Existing investor Iconiq Growth is doubling down by leading this new funding round. Sandberg Bernthal Venture Partners, IVP, Meritech, Greenoaks and Felix Capital are also participating — many of them were existing investors too.

And there’s a reason why Pigment managed to raise so much at a significantly higher valuation less than a year after its previous funding round . In 2023, the startup managed to triple its revenue and double its customer base with well-known clients like Unilever, Datadog, Kayak and Merck. Half of Pigment’s clients are based in the U.S.

“Our current investors told us ‘if you’re going to raise money in 18 months to scale with others, we might as well offer you great terms right now for an internal round.’ And everything happened very quickly … In one week, it was a done deal,” co-founder and co-CEO Eléonore Crespo told me.

Before Pigment, Crespo worked for VC firm Index Ventures and Google. She co-founded Pigment with Romain Niccoli, who was the co-founder and CTO of adtech startup Criteo — an early success of the French tech ecosystem.

“IVP — one of our backers — benchmarks the growth rate of all SaaS companies. And since we’ve been selling our product, we’ve been in the top 5% of SaaS companies with the best growth rate ever, in terms of revenue growth,” Crespo said.

Image Credits: Pigment

Pigment is a flexible business planning tool that is used by chief financial officers and finance teams to create reports and budgets. It’s a modern SaaS platform, meaning that you can integrate it with all your company’s data (ERP, HRIS, data lakes, etc.) and use it as a collaboration tool.

In addition to finance teams, sales teams can use Pigment to create quotas and see how everyone is performing against quarterly quotas. HR teams can see how they should scale the workforce up and down based on strategic changes and financial objectives.

“We’ve done a lot of work to address other teams, not just finance teams. We’ve developed a lot of modules that enable us to serve HR teams, supply chain teams and sales teams,” Crespo said.

In fact, as more teams start using Pigment, it becomes an important tool for cross-team collaboration. And it’s supposed to work better than legacy tools from Oracle and SAP.

Like many software companies, Pigment has also added AI features. As Pigment acts as the central repository for all the important metrics of a company, customers can ask questions to Pigment AI in natural language to get a quick answer. Examples include “Can you give me a breakdown of revenue per country?” or “Why was our actual revenue lower than our forecast last quarter for this product?”

But more importantly, the company has optimized its core product so that it works well even with large datasets and complicated calculations. The best enterprise software products are must-have products, which means that companies usually don’t need to spend a lot of resources on improving the product — clients need this tool to operate. Pigment is still the challenger in this industry, so it believes it needs to provide a better product to compete with other business planning products.

EV startup Canoo's 2024 revenue forecast disappoints, shares tumble

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Granth reports on the North American Consumer and Retail sector, covering a broad range of companies from consumer packaged goods and restaurants to department stores and apparel retailers. Granth's work on the website usually appears on the Retail & Consumer page of Reuters Business section. He holds a post-graduate degree in international relations and area studies and has previously worked as a research analyst.

Wall St ends flat as investors await CPI, earnings

U.S. stocks were essentially unchanged at the close of a choppy session on Monday, with a solar eclipse offering distraction ahead of crucial inflation data and the kick-off of first-quarter earnings season.

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Mineta Transportation Institute Publications

The future of california transportation revenue.

Martin Wachs , University of California - Berkeley Hannah King , University of California, Los Angeles Asha Weinstein Agrawal , San Jose State University Follow

Description

Stable, predictable, and adequate transportation revenues are needed if California is to plan and deliver an excellent transportation system. This report provides a brief history of transportation revenue policies and potential futures in California. It then presents projections of transportation revenue under the recently enacted Senate Bill 1, the Road Repair and Accountability Act of 2017. Those revenue projections are compared with projections of revenue should SB 1 be repealed by voters in the November 2018 election. State-generated transportation revenues will be higher under SB1 than if the act is repealed. For 2020, the mean projection is that the state will collect $10.4 billion with SB1 in place and $6.6 billion without it, a difference of $3.8 billion. Over time, changes in fuel economy and other factors will change annual revenue By 2040, the mean projection is that the state will collect $8.6 billion with SB1 and $3.4 billion without it, a $5.2 billion difference. The total of all state transportation revenue collected between 2018 and 2040, assuming no other revisions to transportation revenue programs during these years, will be about $100 billion less if SB 1 is repealed than if the law is retained. The final section of the report addresses public attitudes toward transportation tax and fee policies, since future any policy changes must be informed by public willingness to consider revenue increases and opinions about which taxes or fees would be most appropriate.

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Publication type.

Transportation Finance

MTI Project

Mineta transportation institute url.

https://transweb.sjsu.edu/research/1850-California-Fuel-Tax-Futures

State taxes, Highway user taxation, Fuel taxes, Registration fees

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Transportation

Recommended Citation

Martin Wachs, Hannah King, and Asha Weinstein Agrawal. "The Future of California Transportation Revenue" Mineta Transportation Institute Publications (2018).

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Amid dismal revenue forecast, Healey administration plans to freeze state hiring

Governor Maura Healey plans to institute a freeze on hiring in portions of the state government lasting at least through the end of the fiscal year in June, according to three sources with direct knowledge of the plan, another sign the state’s rocky financial situation hasn’t improved.

The freeze, which is expected to take effect Wednesday, comes just hours before the administration is slated to release its latest revenue projections, and could indicate that tax collections continue to lag behind the projections state officials use to budget public services.

Some details of the freeze remained unclear, including how much money the Healey administration expects to save with the move.

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In a statement to the Globe, Healey’s budget chief Matthew Gorzkowicz confirmed the move but characterized it as “hiring controls.” He said the Healey administration is taking the action “as one tool at our disposal to responsibly manage spending over the next three months.”

“These hiring controls, while temporary, will help ensure that the administration can balance the budget at the end of the year and preserve critical funding for core programs and services,” Gorzkowicz said.

Certain positions, including those in direct care and public safety, will be exempt, according to officials in Healey’s budget office. So are seasonal hires, positions that have to be filled due to a court order or settlement, returns from leave, and new hires who received offer letters before April 3.

All other hiring will be subject to approval by Healey’s budget office, officials said, adding that the administration is not considering additional spending cuts “at this time.”

State tax revenues have been sliding since last year, with collections now running below projections for eight straight months. Even after the Healey administration downgraded the state’s tax forecast at the start of the calendar year, revenue collections through February were still $275 million below even those lowered projections.

Officials on Beacon Hill closely monitor the monthly revenue figures, particularly as the House and Senate prepare to craft budget plans for the next fiscal year in the coming months.

In January, Healey unveiled her own budget bill, a $58 billion plan that would increase spending by about $2 billion over the current budget, or about 3.7 percent. That’s below increases of the past years, which Healey cited as evidence that officials are “tightening our belts” after a period of soaring revenues during the pandemic.

Then in January, Healey, citing lower-than-expected tax revenue collections, slashed $375 million in spending, cutting hundreds of millions from programs that provide outreach for seniors, behavioral health supports, homeless shelters, and other services.

In a letter to lawmakers at the time, Healey said the cuts won’t have an impact on school funding or local aid, nor are state officials planning to lay off any government employees.

At the same time, her budget office also lowered the amount of tax revenue it expected to collect this fiscal year by $1 billion. Revenues at the time were running $769 million, or about 4 percent, behind the state’s original projections midway through the current fiscal year.

After years of sometimes record-breaking budget surpluses, tax revenues began tailing off in 2023. The state’s take plummeted last April before it ended the fiscal year, having collected roughly $600 million less than it expected.

The vast majority of that shortfall, roughly $593 million, involved lower-than-expected collections of capital gains taxes, a volatile revenue source, officials said at the time.

At the same time, costs to state continue to mount. For example, the state projects it will spend $915 million in the next fiscal year for its struggling emergency shelter system, which has been overwhelmed by an influx of homeless and migrant families. And a spending bill moving through the Legislature would allow the governor to dip into the roughly $850 million left in a state escrow account that contains the remnants of last year’s multibillion-dollar surplus.

This would not be the first time an administration paused hiring to address a budget hole.

In 2015, then-governor Charlie Baker implemented a state hiring freeze for nonessential workers just over 24 hours after he was sworn in.

At the time, Baker said in a statement that the state’s deficit “proves that Massachusetts is facing a spending problem that must be remedied.”

Emma Platoff of the Globe staff contributed to this report.

Samantha J. Gross can be reached at [email protected] . Follow her @samanthajgross . Matt Stout can be reached at [email protected] . Follow him @mattpstout .

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Follow our news, recent searches, perion slides after slashing 2024 revenue forecast on microsoft bing changes, advertisement.

:Perion Network's U.S.-listed shares plunged more than 35 per cent on Monday, after the Israeli ad tech firm cut its annual revenue forecast, driven by a drop in search advertising due to changes at Microsoft's Bing.

The company now expects 2024 revenue in the range of $590 million to $610 million, against its prior expectation of $860 million to $880 million.

Changes in ad pricing and other mechanisms by Microsoft Bing in its search distribution led to a decline in search advertising activity, Perion said on Monday.

"The revenue concentration with Microsoft has always been a risk with investing in Perion," said Eric Martinuzzi, an analyst at Lake Street Capital Markets.

"Microsoft advertising unilaterally changed the amount it was willing to pay for indirectly sourced search traffic by all of its search partners..... that's what's causing the reset for Perion."

Microsoft accounted for 35 per cent of its revenue in 2022, according to Perion's annual report. The agreement was renewed in 2020.

Perion estimated first-quarter revenue of $157 million, compared with Wall Street estimates of $175.5 million, according to six analysts polled by LSEG.

The company's stock was down $13.30 in early trading.

They are down about 32 per cent so far this year, pressured by competition from Big Tech firms including Alphabet's Google and Facebook-parent Meta Platforms.

Perion expects to announce its first-quarter results on May 8.

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• Boeing-stock
• News for Boeing

Delta Air Lines Q1 Earnings Preview: Bright Forecast With A Dash Of Boeing Drama, Solar Eclipse Spotlight

Leading airline company Delta Air Lines Inc (NYSE:DAL) is set to report first-quarter financial results before market open Wednesday, April 10, 2024.

Here's a look at the key earnings estimates, analyst ratings and key items to watch.

Earnings Estimates: Analysts expect Delta Air Lines to report first-quarter revenue of $12.547 billion, according to data from Benzinga Pro.

The company reported revenue of $12.759 billion in last year's first quarter. Delta has beaten revenue estimates from analysts in over 10 straight quarters.

Analysts expect the airline company to report first-quarter earnings per share of 35 cents, compared to 25 cents per share in last year's first quarter.

The company has beaten earnings per share in four of the last five quarters, including three straight quarters.

Delta recently said it expects first-quarter earnings per share to come in a range of 25 cents to 50 cents. The company has guided for full year earnings per share to be in a range of $6 to $7.

Analyst Ratings: Several analysts increased their price targets on Delta Air Lines ahead of quarterly financial results.

Here are the most recent analyst ratings on Delta Air Lines.

Bank of America: Buy rating, raised price target from $50 to $53.

Morgan Stanley: Overweight rating, raised price target from $77 to $85.

UBS: Initiated with Buy rating, price target $52.

Related Link: Apple iPhone Allows ‘Greatest Hack’ Ever For Airline Flights: Text Yourself, Your Uber Driver And Watch The Magic Unfold

Key Items to Watch: The airline sector has had an up-and-down 2024 due to concerns over Boeing Co (NYSE:BA) airplanes and customer concerns of the safety of airplanes.

Delta shares have been among the better performers in the airline sector in 2024 and a strong earnings report could help continue to the positive momentum.

Comments on the ongoing Boeing struggles could be an item to watch. Delta recently said it expected Boeing 737 Max 10 deliveries to be postponed into 2027, from a previous estimate of 2025. Delta ordered 100 of this aircraft type.

Another item to watch could be overall health of the airline industry with Delta reporting strong March figures and saying it was seeing corporate demand come back.

The solar eclipse on April 8 was also an event highlighted by Delta having a flight that followed the path of totality. While this is only one flight, Delta may have benefitted from other flights that went near the path being booked and seeing strong ticket sales or overall strong travel around this key event.

The U.S. Global Jets ETF (NYSE:JETS) is up 11.4% over the last year and up 7.3% year-to-date in 2024. Delta is the largest holding in the airline ETF.

Delta shares meanwhile are up 40.9% over the last year and up 17.2% year-to-date.

DAL Price Action : Delta shares are up 2.26% to $47.10 on Monday versus a 52-week trading range of $30.60.

Read Next: Delta To Introduce Premium Lounge Experience At New York, Boston And Los Angeles Airports

Photo: Courtesy Delta

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