product case study by giulio palombo

Product Data Science -->

Learn how to develop product sense, create metrics, and design robust A/B tests

Assets packed with power beyond your imagination.

Some companies that approved this course as a professional development expense

You will learn

Data-driven hypotheses for new a/b tests.

Learn what was the data-driven hypothesis behind FB stories, Netflix free trial, Youtube Premium, etc.

Design actionable metrics

When to use average-based vs threshold-based metrics? How to identify those thresholds in metrics such as percentage of users with 7 friends in 10 days?

Evaluate metric trade-offs

How to evaluate changes that positively affect some key metrics, but negatively affect others? Which strategy to use to decide whether a product change is good or not in those cases?

A/B Testing

How to design statistically sound A/B tests? How to choose test traffic percentage? How to deal with novelty effect, connected users, randomization bugs, or other typical issues in tech A/B tests?

Applied data

How to deal with actual tech data, such as sudden spikes or drops, bugs, unbalanced metrics, non-random missing data, A/B test results, conversion data, etc.

Machine Learning

How to use machine learning to fight frauds, build data products, or develop product insights? How to evaluate the impact of new machine learning models into production?

“ One of the best decisions I’ve made for my career. The case studies contain information that I wasn’t able to find anywhere else because most of them are gained with years of experience. ”

Bahar Bazargan – got a job as a Data Scientist @ Facebook – US

Product Case Study – Insights

Should a free trial require credit card info? Where in the funnel should the highest friction point be?

Logistic Regression

When to choose a logistic regression, how to interpret it, and how to use its output to come up with product ideas

A/B tests: Sample Size

How to estimate for how many days you should run an A/B test, from both a statistical and business perspective

A/B tests: Novelty Effect

How to understand if a test is affected by novelty effect and how to deal with it in practice

A/B Tests: Randomization

The crucial step of making sure that test and control are properly randomized

Metrics: Ads Challenge Solution

How to pick a metric for ads, identify the best performing ones, and analyze trends

“ I have taken several DS online courses, and this is the best one. It is extremely realistic. The skills I learned made me a better data scientist and helped me tremendously in my daily job. The 1:1 mentorship part is great too. I would always get a reply almost right away and complex concepts were explained very clearly ”

Kenny Tang – Data Scientist @ SmarTone Telecom Lim – Hong Kong

You will learn real product data science

Course sections

12 sections with more than 130 lessons and exercises in total Real tech company tables, i.e. user table, event table, A/B test tables, etc.

1) Product Sense via Machine Learning

2) product and metrics – case studies.

18 case studies on how to design actionable metrics, understand what drives them, and figure out how to improve them via new product features

3) Personalization

In depth practical exercise on how to use machine learning to build a data product personalized at the user level. This is the framework used to optimize almost all data products

4) Unbalanced Classes

Almost all tech company data have unbalanced classes, e.g. fraud, ad clicks, conversation rate, email clicks, etc. These exercises explain how to deal with that

5) Missing data in tech

Most of missing data in tech are non-random, i.e. users choose to not provide certain information about themselves. These lessons explain how to deal with biased missing data, including Uber and Airbnb case studies

6) Fraud – Case Studies

Fraud is one of the most common data science applications. These case studies explain how to set up the problem from a ML standpoint as well the how to build a product around it

7) A/B Testing – Practice

A series of lessons covering all that’s needed to know about A/B testing. Includes statistical inference theory as well as very practical tech problems (novelty effect, randomization, sample size, testing by market, etc.)

8) A/B testing – Case Studies

12 case studies describing how top tech companies design their A/B tests. They focus on the most common issues tech companies face, like how to test in social networks or marketplaces, how to estimate long term effects, when A/B tests fail, etc.

9) New Product Case Studies

A new list of product case studies. They focus on trade-offs when evaluating multiple metrics at the same time (e.g. what to do if after a test some key metrics are up and some down) as well as explaining the thought process behind using data to choose whether testing a totally new product

10) Collection of tech company blog posts/case studies

This is a collection of company write-ups, tutorials, and blog posts. Includes Airbnb, FB, Linkedin, Google, Netflix and many more other companies describing how they design A/B tests and use DS to drive product development

11) Data challenges with solutions

They come from the “Collection of data science takehome challenges” book. They touch all the topics taught in the course. All challenges come with full solution in R and Python

12) Coding course

Teaches a reusable framework to solve coding exercises in SQL, R, and Python. Includes exercises about metrics, data processing, aggregate statistics as well as probability exercises

Can I pay for this via my employee training budget?

Yes, the course perfectly fits most employee training requirements. Approval process at most companies has been straightforward. This course has been approved by managers at >200 companies of different sizes (from FAANG to 20-people start-ups), industries (tech, banks, consulting, healthcare), and locations (North America, Asia, Europe). If you need any help to facilitate the reimbursement process, need help in matching course content to your current work tasks, or want to see a sample of the invoice you could receive after getting the course, please get in touch.

• ✔   Lifetime access to course curriculum and all its updates Curriculum includes a mix of theoretical lessons, product case studies, and challenges with solution. In the last couple of years, updates included tons of brand new and constantly up-to-date product case studies as well as an entire course on coding for data science
• ✔   Unlimited 1:1 support from course author for 1 year Any questions you have about the course material or anything related to product data science, you can send an email, chat, or share a Google doc with all the questions. You will get a prompt reply
• ✔   Data science coding course When you enroll in the product data science course, you will also automatically get enrolled in the data science coding course from the same author. The coding course teaches a framework to tackle common data science coding exercises in SQL, Python, and R
• ✔   Personalized feedback Send your solution for all the exercises in the course. You’ll get a detailed feedback on your work

“ Lessons, exercises, and projects are great to improve data science skills and product sense. I learned a lot by going through them ”

Doudou Tang – Data Scientist @ Booking.com – UK

I have been creating educational material related to data science since 2015. Firstly focusing on job interviews (A Collection of Data Science Take-Home Challenges, 40 Data Science Product Questions, DS Coding Course) and, more recently, focusing on employee training (Full Course in Product Data Science and Chatgpt for Data Scientists). The Full Course in Product Data Science was among the fastest courses ever to reach $1 million in sales on Teachable. The main idea behind it is to simulate the actual work data scientists do in top tech companies. In 2023, I built and sold a Chatgpt app to Colgate. Based on that experience, I created a Chatgpt for Data Scientists course to help data scientists build and monetize AI apps, and built the DataScienceGPT app . Prior to all this, I worked as a data scientist for several Silicon Valley tech companies, the last one being Airbnb.

I am buying this with my employee training budget, do you provide a certificate or invoice that I can show to my employer?

Yes, definitely. Can provide certificate, invoice, or anything else you need.

Does this course also include the data science take-home challenges and 40 case studies?

Yes, all those challenges and product questions are here too. However, this course includes much more. Its main focus is on teaching product data science via a combination of theoretical lessons and practical examples. The challenges then come at the end to make sure things were learned properly. Also, the course includes many new product questions, like for instance the first one in the samples above, as well as all the challenges have a solution, not just 4. Here is the full curriculum.

What’s the main difference between this course and the other million data science courses available?

Frankly speaking, most data science courses are not particularly useful because they have little/nothing to do with what data scientists actually do at work. Firstly, data scientists don’t spend their time over-tuning a fancy model to marginally improve its performance. In fact, most of data science work is about looking at the data to come up with product ideas and properly designing A/B tests. And the few applied courses tend to be so simple to the point of being highly unrealistic. I.e., most A/B test courses will teach you to randomly split users, run the two versions of the site, and check the results. But that strategy almost never works for several reasons (test and control would never be independent in social networks or marketplaces, can’t estimate novelty effect, etc.). This course will teach you how product data science is actually done at top tech companies. The course uses data that look exactly like tech company tables (including wrong entries, non-random missing values, A/B tests, etc.). And then actual data science projects are built on top of those data.

I have additional questions!

For any additional questions, please email [email protected]

Interested in AI as well?

Product Case Ebook 1

We have added all our winning case study solutions in an ebook. Please feel free to go through the case problem statements and respective solutions as a reference for your product management Interview prep.

A bunch of companies share a take home case study assignment to filter candidates for their face to face interviews. Hence, these product manager case studies will be markers for you to prepare the structure and how to approach product assignment questions.

Solve PM School weekly challenges and get recognised by Industry leaders. For participation, check out PM School Live challenges .

Founder of PM School and Hamster Comedy. 10+ years of work experience having led Product growth challenges in Foodtech, Insurtech, and Gaming.

Fintech Frontiers | Strategy to Product Mastery with Anand MS, Product Leader at Zeta

Product Case Ebook 4

Product Case Ebook 3

Weekly Newsletter.

Want to Make Better Products? Build Better Case Studies With This Method.

Case studies are one of the most useful items in the product management toolkit. To build effective ones, you need to follow a simple but vital set of guidelines.

Robert Cialdini’s book Influence: The Psychology of Persuasion , first released in 1984,  popularized the concept of social proof. This phenomenon consists of individuals copying the actions of others around them in order to acclimate to a system. People are subconsciously influenced by the behavior of other people within a given environment. Although this idea is simple, Cialdini’s book radically changed my mind with respect to how I interacted with the content that my product team and I produced.

Why was this theory so profound? Well, the book helped me understand why people were ignoring almost everything that we gave them. As it turned out, everything that we wrote was focused on ourselves and not on our customers. 

We weren’t influencing. Instead, we were just talking. 

Cialdini’s work gave a conceptual framework to something that the best marketers already subconsciously knew: Nothing sells better than reflecting the customer’s own actions back at them. 

For example, say you want to buy a shirt.  Which of these pitches is more likely to make you buy?

Option A: This shirt is made of polyester, washes well and makes you look professional.

Option B: This shirt is built for the product manager on the go. When you’re sweating the details and pacifying the battle between sales and engineering, you’ll want a shirt that stays tucked in as you rush from meeting to meeting. 

Option B draws on social proof to reflect actions that you’ve experienced back at you. 

Product management (PdM) is about helping the team improve decision fitness. That includes how we influence our customers to use our products, especially if we’re confident that our product is the right one for them. Social proof helps us accomplish this goal. 

Before we can use social proof, however, we need a way to get the information that we want to reflect back to the customer.  In other words, how do we come to see the world as our customers see it? How might we put ourselves in their headspace?

Sure, you can scan different websites, browse social media, or even look at your competitors to see what they’re doing. With any of these strategies, however, you’re only getting part of the picture. Like almost anything dealing with product development, talking to your customer directly is going to get the best results.  

So, for PdMs to get the data they need to gather social proof and understand how customers see the world, we can rely on case studies. Let’s talk about what exactly these are and how you can use them to help you influence your customers and help other teams, like product marketing and sales, make better decisions.

3 Key Steps To Building a Product Case Study

• Make an outline.
• Ask the right questions.
• Analyze carefully.

More Product Advice From Adam Thomas How To Improve Your Product Research

What Is a Case Study?

For our purposes, a case study is an in-depth conversation aimed at understanding how a customer uses our product. We want to get to know who they are, why they use our product, and the context in which they use it.

This technique is how you get inside of your customer’s head. When you have multiple, deep customer conversations over a period of time, you’ll get a better understanding of what drives them. You’ll also be able to target your marketing so that it makes sense to them.

How Do You Build Case Studies?

Building case studies is no different than doing any other interview .  When conducting a proactive conversion with customers, you need to understand what you want, use open-ended questions, and analyze everything carefully.

Make an Outline

You can go in a bunch of different directions when you talk to your customers. In fact, if you’re like most PdMs, this is an easy trap to fall into. Everything that the customer says may seem like gold, and it’s easy to follow any string in hopes of chasing down an insight. 

So, how do you avoid that trap? You’ll need to write an outline to keep yourself on track. A case study outline is simple and has three components. 

Hypothesis. You need a clear hypothesis whenever you talk to a customer. What question are you trying to answer by talking to the customer? Why are they important? Note this information upfront, and derive the questions from the hypothesis. Consider it your anchor.

Goal. What type of assets are you planning to create from this interview? Who wants this information? Having this in the form of an aligning statement, something that helps the team know what you are looking for and what you want to build, will help with analysis. Do it now so you won’t have to think about it later.

Questions. These are based on both the hypothesis and the goal. 

Those three components will help you avoid the trap of letting the interviews meander. Now, let’s talk a little bit more about those questions. 

Ask the Right Questions

Your question set should be short, with no more than five max.

You want to follow up on your initial questions to get as many stories as possible. If you have more than five, you risk letting the interview get rigid since you’ll feel pressured to get to as many questions as possible. Further, asking fewer questions will make sure you have some uniformity to the answers.

Even though you’re just asking a few questions, you’ll want to keep them open-ended.  An open-ended question like “Walk me through your shirt purchase. What drove this decision?” is better than “Did you like our service?” The latter could too easily elicit just a yes or no response while the former invites the customer to provide more detail.

You want to have a free-flowing conversation, which means focusing on the customer. Conversations are going to give you the information you need to build that social proof. Once you’ve acquired that information, you can analyze the material and create the case study. 

Analyze Carefully

Before conducting an analysis, make sure you sit with these conversations for a while. 

Take the time to find good quotations that are interesting and align with your values by transcribing the interviews. Check to see if the language in your marketing materials matches how your customers talk. The closer your work matches their worldview, the more they will trust the product.

This process may seem simple at first. As you start to put this plan into action, however, you’ll see how much data you can collect and how closely you can tailor your product to match the mental model of your customers.

You’ll eventually be able to see if the plan is working when you make changes and hear from the customer again. The next time you talk to them, you want to hear something along the lines of, “Your [page/feature/tool] described my issue exactly, and that’s why I bought the product.”

Build Artifacts To Put Case Studies to Work

When you have the data from the interviews, you’ll be able to build artifacts that match your customer’s mental model.

What are some artifacts that can come from doing a case study?

Testimonials. These are short-form statements, usually a paragraph or less, that come directly from the customer and attest to the value of your product or service. During the interview, the customer may offer a bite-sized anecdote that sums up a feature or your product in a helpful way. These statements are great to use on a sales or product page to give your work more credibility.

Articles. These interviews create the kernel of an article for your writers. If your team has a blog, use it to underscore the high points that customers report or spotlight a particularly well-liked feature. Writing an article based on the case study conversation can help customers see, in a more relaxed context, how your product will work for them.

White Papers. A white paper is a one-page selling document highlighting the technical side of a product. For more technical products, you must give potential custoemrs a look at how the product functions in a more structured, quasi-academic format. Your case studies will allow your team to write a white paper by giving you anchor points led by the customer. 

Customers want to tell their stories. When your product is great, rest assured they are doing it anyway. Most of the time, they are happy to spend time with you and your team and give you good feedback. More importantly, you’ll get the social proof you need to stand above the rest of the marketplace.

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50 Product Management Case Studies

We often wonder what kind of process other product teams have created, planned, and most importantly, how they have implemented it. That is why we at Producter have compiled 50 different case studies for you.

a year ago   •   4 min read

We often wonder what kind of process other product teams have created, planned, and most importantly, how they have implemented it.

That is why we at Producter have compiled 50 different case studies for you.

Brought to you by Roadmape

1- Rules of Flow for Product Management: an AirBnB Case Study

“Engagement” is a term that is so overused in product management that it has almost lost its meaning. So often I’ve heard from teams, “We’ll measure the success of this test with engagement,” which could mean anything from feature click-through to bounce to we-aren’t-really-sure-this-will-drive-conversion-so-we’re-hedging-our-bet. Underneath, the reason this term has been co-opted and jargonized is that genuine, productive engagement can be ramped toward long-term customer loyalty. And loyalty pays off: a loyalty increase of 7% can boost lifetime profits per customer by as much as 85%, and a loyalty increase of 3% can correlate to a 10% cost reduction ( Brand Keys ).

2- The Psychology of Clubhouse’s User Retention (...and churn)

3- Netflix Q1 ’21 Subscriber Growth Miss: Can We Avoid Another One?

As a data analyst supporting a mobile subscription business , Netflix’s Q1 ’21 subscriber growth miss is a classic example of when I would get called for recommendations to prevent a miss in the future. I thought this would make an interesting case study to discuss my approach to finding insights to drive subscriber growth. Sadly I’m not a Netflix employee and will be limited to publicly available data but the wealth of information on the Internet about Netflix is sufficient to generate insights for this case study.

4- Amazon Go Green

As part of the Design Challenge from productdesign.tips, our team came together to find ways for Amazon to encourage more sustainability on their e-commerce platform. As with any unsolicited design project, the challenge comes with a lack of access to application analytics and technical feasibilities. Nonetheless, the question remains: How might we design checkout screens for an e-commerce app to help people recycle the goods they buy?

5- Quora Case Study – The Wonderful World of Quora

Quora has become a substantive resource for millions of entrepreneurs and one of the best sources for Business to Business market. Majorly used by writers, scholars, bloggers, investors, consultants, students this Q/A site has much to offer in terms of knowledge sharing, connection building and information gathering.

6- Building a product without any full-time product managers

Jambb is an emerging social platform where creators grow their communities by recognizing and rewarding fans for their support. Currently, creators monetize fan engagement through advertisements, merchandise, and subscriptions, to name a few. However, this only represents 1% of fans, leaving the other 99% (who contribute in non-monetary ways) without the same content, access, and recognition that they deserve.

8- What if you can create Listening Sessions on Spotify

Summary: The project was done as a part of a user experience design challenge given to me by a company. I was given the brief by them to work on a feature of Spotify and I spent around 25–30 hours on the challenge in which I went through the entire process, from the research to testing.

9- Redesigned Apple Maps and replicated an Apple product launch for it

Quick-fire question; what is the single most important and widely used feature in a phone — asides from texting and instant messaging friends, coworkers and family? Maybe you guessed right, perhaps this feature is so integrated into your life that you didn’t even think about it — either way, it is your phone’s GPS. It is reasonable to say that GPS technology has changed society’s lives in ways we never could’ve imagined. Gone are the days of using physically printed maps and almanacks, when we now have smartphones with navigation apps. Since the launch of the iPhone and the App Store, consumers have been able to use different apps for their personal navigation needs. Everyone has a preference, and apps have come out to try and address every need.

10- Intuitive design and product-led growth

In 2018, Miro was hardly a blip on the radar in the Design world. Fast forward two years, and suddenly Miro is solidly the number one tool for brainstorming and ideation.

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6 Product Management Case Studies You Can't Miss

Associate Product Marketer at Zeda.io.

Mahima Arora

Created on:

March 18, 2024

Updated on:

8 mins read

Transform Insights into Impact

Build Products That Drive Revenue and Delight Customers!

Product management case studies are detailed analyses of how a product was conceptualized, developed, and marketed. A typical product management case study contains the following:

• The pain points and expectations of the user
• Competing products in the market
• Development , delivery, and iteration methods
• Marketing strategies implemented to relay the product’s value proposition
• How the product was received
• Lessons for the product team

So, why should you learn about the development of a product in so much detail? The answer lies in the sixth bullet.

Let’s look at how reading case studies related to product management can help you.

How product management case studies help you

Here’s why reading product management case studies is a worthwhile investment of your time. A well-written case study:

• Gives you an in-depth understanding of real product problems : Meeting or exceeding the expectations of the customers is always challenging. Whether it is technical complexities, budget limitations, or organizational miscommunication, a case study helps you recognize the source of the problem which led to the development of a less-desirable product.
• Contains practical insights outside of the theory : Even a layman can learn the steps of SaaS product management . However, seasoned product managers know that developing a successful product takes more than learning the development steps. These case studies contain tons of real-life scenarios and the lessons that come with them.
• Educates you and makes you a better product manager: Product management case study examples take you through the journey of developing a product, which helps you improve your existing approach toward product development. You will also learn better ways to manage your team and resources.

In simple terms, a product management case study helps teams learn lessons that they can emulate to develop a more profitable product.

In this article, let’s look at six product management case studies that are a must-read for every product manager.

1. Slack: Initial product launch strategy

Stewart Butterfield started a gaming company called Tiny Speck to change the world of massively multiplayer online role-playing games (MMORPG). Him and his team created Glitch which was quite different from other games in that genre such as World of Warcraft.

Glitch was a 2D game that did not have the violent aspects that typical MMORPG games had at the time. It allowed extensive character personalization and Butterfield described it as “Monty Python crossed with Dr. Seuss on acid”.

While building Glitch, Butterfield and his team used the Internet Relay Chat (IRC), an online chat tool popular in the 80s and 90s. However, it fell short as the team found it difficult to keep track of past conversations, which motivated them to build their own communication tool.

As they developed Glitch, their internal chat tool gained more features based on their needs.

Despite lots of support from investors, Glitch was unable to attract enough players to keep running profitably and Butterfield eventually shut it down in 2012 .

After six months, in early 2013, Butterfield renamed their internal communication tool Slack - acronym for Searchable Log of All Conversation and Knowledge and requested his friends and colleagues to try it out and give feedback — they all loved it.

By May 2013, Slack was ready for the big reveal which posed a new challenge — executing the perfect launch strategy to drive demand.

Slack’s Challenge: Nailing the initial product launch

While launching an app that can have such an impact on how organizations work, it is crucial to get it right. At the time, there weren’t many team messaging apps and most teams had conversations via email.

Slack needed a significant number of early adopters to validate their hypotheses about team collaboration and collect data that will help them improve its services further. Consequently, this increased the stakes for the first launch.

How did Slack do it

CEO Stewart Butterfield revealed that on the first day of the launch, Slack welcomed 8000 new users which rose to 15000 at the end of the second week. The credit for this initial success, he explains, went primarily to social media.

Social media helped Slack deliver its PR pieces through its genuine users. This led to a snowballing effect because people interacted with people.

Slack recorded over 18 million active users in 2020.

Although the impact of social media-based word-of-mouth marketing will have different levels of success as it depends on factors such as the type of product and its use cases, you should have a social media marketing strategy to spread the word.

Suggested Read: Leveraging VoC-driven AI Insights to Build Revenue-generating Products

2. Superhuman: Finding product-market fit

‍ Superhuman is a premium email service for busy teams and professionals who need more of everything; speed, usability, and personalization. Apart from superb design, Superhuman processes and executes any request within 100ms.

Rahul Vohra built Rapportive in 2010 — a plugin that adds social profiles to Gmail which was later acquired by LinkedIn . This gave Vohra an intimate view of email and quickly realized that things will progressively get worse.

In his words, “I could see Gmail getting worse every single year, becoming more cluttered, using more memory, consuming more CPU, slowing down your machine, and still not working properly offline.” 

He also brought attention to the number of plugins people used, “And on top of that, people were installing plugins like ours, Rapportive, but also Boomerang, Mixmax, Clearbit, you name it, they had it. And each plugin took those problems of clutter, memory, CPU, performance offline, and made all of them dramatically worse.”

Vohra had one question in his mind — how different would the email experience be if it was designed today instead of 12 years ago?

‍ Superhuman was born to give professionals the email experience that they have been long waiting for. Smooth, easy on the eyes, and most importantly, blazingly fast.

But, there was one elephant in the room.

The idea of building a better email service than the existing players sounded great. However, going against some of the biggest brands of Silicon Valley required more than a bad personal experience with Gmail. 

The Superhuman team needed evidence that such a product is actually desirable.

Superhuman’s Challenge: Establishing product-market fit

The team at Superhuman was competing against the email services of Apple, Google, and Microsoft which made the product-market fit quite crucial.

But how do you know whether you have achieved product-market fit?

How did Superhuman do it

Vohra and his team came up with an innovative idea to measure product-market fit by testing crucial hypotheses and focusing on the right target audience.

Superhuman had two hypotheses :

• People are dissatisfied with Gmail and how slow it is.
• People are also dissatisfied with third-party email clients and how buggy they were.

In a product management case study , Vohra explained how to find the right audience — the users who would be ‘very disappointed’ if they could no longer use your product. After identifying them, all you have to do is build the product as they want it.

3. Medium: “Highlights” feature

Evan Williams co-founded Blogger and Twitter which has helped millions of people share their thoughts with the world. Although both platforms became quite popular, they still couldn’t deliver the best reading experience to their users. Blogger allowed readers to browse topics by authors only and Twitter made it difficult for authors to aptly describe themselves.

He quickly recognized the need for a publishing platform that delivers a diverse experience for the readers and allows the authors to speak their hearts.

That’s how Medium was born. It enabled readers to browse articles by topics and authors, helping them to gain different perspectives on any particular subject. It also allowed everyone from professional programmers to amateur chefs to share their insights with the world as they wanted it.

The developers slowly added more features to Medium such as tags, linked images, social cards, and sharing drafts as it evolved through the years.

One of the many notable features of the platform is the “Highlight” feature — where you can select any particular post section and treat it as a mini-post. You can comment on the Highlight or tweet it, which is handy for both personal revision and sharing interesting snippets with others.

Suggested Read: Want to become a Product Coach?

Medium’s Challenge: Determining whether “Highlights” added value

Medium faced a challenge while determining a metric that can give them an accurate assessment of the desirability of this feature. In other words, they needed a metric that would tell them whether the “Highlights” feature made user interactions better and more rewarding.

How did Medium do it

The team at Medium solved the challenge by shifting their focus to one crucial metric rather than multiple vanity metrics such as organic visits and retention time which signifies how much value your users are getting out of your product based on retention rate. 

For Medium, it was Total Time Reading (TTR) . It is calculated by estimating the average read time which is the number of words divided by the average reading speed (about 265 WPM) and adding the time spent by the reader lingering over good paragraphs by tracking scrolling speed.

4. Ipsy: Managing distribution 

Michelle Phan started her journey as a YouTuber who recognized the importance of makeup in someone’s self-expression. She has been sharing beauty tips and makeup tutorials with her audience since 2007. 

While on a trip to Thailand, she observed how little girls scrambled to pay for makeup samples in front of vending machines. Five years later, she launched a subscription-based Glam Bag program — where the customers will receive 4-5 deluxe-sized samples of makeup products.

MyGlam, as it was known back then, quickly gained over half-a-million monthly subscribers which created one of the biggest online beauty communities.

Phan quickly realized what she wanted to do — to build a brand for women who wanted to share their perspectives on beauty and meet like-minded people with similar interests and styles.

Ipsy , which comes from the Latin root “ipse” meaning “self”, was created by Phan, Marcelo Camberos, Jennifer Goldfarb, and Richard Frias to expand the user experience.

Although Phan knew how to convert viewers into paying customers, executing a marketing strategy by scaling it up was challenging.

Ipsy’s Challenge: Managing a content distribution strategy

The first makeup tutorial by Michelle Phan has now over 12 million views. Videos like that helped Phan get her first subscribers on her MyGlam program.

This shows the importance and impact of influencer-led content on revenue for businesses in the beauty industry.

However, running an influencer content distribution strategy involves collaborating with multiple passionate influencers. It was challenging to find like-minded influencers who will promote only one brand. Moreover, when working with influencers, it's important to implement effective content moderation to make sure the posted content aligns with your goals.

Phan and her team had a simple solution for this.

How did Ipsy do it

Phan and Spencer McClung, EVP of Media and Partnerships at Ipsy, partnered with beauty influencers like Bethany Mota, Promise Phan, Jessica Harlow, and Andrea Brooks who were already subscribed to MyGlam to create content exclusively for Ipsy.

In a case study analysis, McClung revealed that it put Ipsy on a content-based growth loop where the content was created by both the influencers and customers for the beauty community.

Sponsored content for products by influencers helped them increase their reach and helped Ipsy get more loyal customers. This growth loop gained Ipsy over 3 million monthly subscribers .

Suggested Read: Pivoting equals failure?🤯

5. Stitch Fix: Mastering personalization

Katrina Lake, the founder of Stitch Fix , realized back in 2011 that apparel shopping needed an upgrade. eCommerce failed to meet the expectations of the shoppers and retail shops were falling short in terms of options.

In an interview with The Cut , she revealed "Searching online for jeans is a ridiculously bad experience. And I realized that if I imagined a different future, I could create it."

After realizing that no one has merged data and fashion shopping, she set out to make a difference. She started a personal styling service out of her apartment in 2011 when she was pursuing her MBA from Harvard.

Lake relied on SurveyMonkey to keep track of her customer’s preferences and charged $20 as a styling fee. In late 2012 Eric Colson, then the VP of data science and engineering at Netflix, joined Lake on her journey of crafting the future of retail.

Lake and Colson wanted to give their customers much more than just personalized recommendations.

Stitch Fix’s Challenge: Building a personalized store

Stitch Fix wanted to give their customers more than just personalized recommendations — they wanted to build a personalized store for them where everything they look at, from clothes to accessories, matches their flavor.

But everyone’s body dimensions, preferences, budgets, and past choices are unique which can make building a personalized store difficult.

The team at Stitch Fix found a simple yet effective solution for this challenge.

How did Stitch Fix do it

Katrina Lake, CEO of Stitch Fix, revealed in a case study that personalization is crucial for the onboarding, retention, and monetization of customers.

When signing up, Stitch Fix asks you a few questions about your fashion choices and picks clothes that look the best on you. Furthermore, the collections in your personal store will keep improving as it continuously learns more about your personal preferences.

Also, there is no subscription fee which makes Stitch Fix a great option for occasional shoppers. Suggested Read: Canva’s Success Tale in the World of Design

6. Pinterest: User retention

Ben Silbermann started his tech career at Google’s customer support department. Although he loved the company and believed in its vision, he quickly became frustrated as he wasn’t allowed to build products.

With support from his girlfriend (now wife) Divya and a college friend Paul Sciarra (co-founder), Ben created an app called “Tote” in 2009 which was described as a “catalog for the phone”. Tote allowed users to catalog their favorite items and will be alerted whenever they were on sale so they can make a purchase.

However, the users used it to share their collections with each other instead. Ben recalled how he collected insects as a kid and loved sharing his collection with others. He recognized how people, in general, love to do that.

And, just like that, Pinterest was born where users can “pin” whatever they are interested in and add it to their personal collections.

Pinterest quickly became a hit and entered the global market.

Despite huge success within the US, Pinterest struggled to retain users globally. The team realized that the primary reason users churned is that something stopped them from getting the product’s core value — building personal collections.

Pinterest’s Challenge: Helping customers quickly realize the core value

There are many things that can prevent a user from accessing a product’s core value and one of them is internal friction within the product.

Pinterest’s product folks zeroed in on the one feature that was the gateway to the product’s core value — the “Pin It” feature.

Users outside the US simply couldn’t relate to the term, even though all it did was save the item they like to their personal collection.

How did Pinterest do it

The “Pin It” feature of Pinterest is linked directly to its brand identity. Casey Winters, former growth product lead at Pinterest, suggested changing it to “Save”, particularly in areas outside of the US.

As of the third quarter of 2022, it has over 445 million monthly users all over the world exploring various “ideas” to build collections for sharing with their friends.

Casey concludes in the product management case study that checking whether the users are getting your product’s core value is pivotal in solving most of your growth challenges.

Key Takeaways

Case studies for product management contain in-depth insights that help product teams improve their approach toward their product’s ideation, analysis , development, and commercialization.

The six product management case study examples we reviewed above give these crucial insights:

• Slack : Don’t forget to use social media for marketing your product before its launch.
• Superhuman : Focus on the users that will be “very disappointed” if they can’t use your product anymore to achieve product-market fit.
• Medium : Track the one metric that tells you whether your users are getting value from your product rather than vanity metrics such as organic traffic.
• Ipsy : Partner with influencers to educate your target audience on how to get the most out of your product.
• Stitch Fix : Learn about what your users want and recommend them just that.
• Pinterest : Continuously experiment by changing multiple variables to uncover new growth opportunities.

To put these lessons into practice, you need to provide your team with the right tools that help them interact with your users, learn about their preferences, monitor their usage data, plan the next steps, and manage product development effectively.

Zeda.io is a product management super-app that allows you to do just that. You can run your entire product management process , from ideation to delivery, in one place. Zeda.io comes with over 5000 integrations with Zapier, enabling you to hit the ground running in no time.

Start your free trial today . Also, looking for the latest trends in AI, UX, product management, and startups? Join our biweekly newsletter now! We distill complex topics into actionable insights just for you. Hit the 'Subscribe' button and never miss out on these valuable updates. Act now – because in the fast-paced world of tech, staying ahead matters! Subscribe here.

• What is a product management case study?

Answer: A product management case study is a detailed analysis of how a product was developed and iterated over time for maximum success. These studies help product managers learn from others and improve their own approach toward product management.

• How do you prepare a product management case?

Answer: You can prepare a product management case study in four steps — understand customer needs, monitor the stages of development, identify the factors that affected the course of product development, and extract takeaways.

• What are the 3 major areas of product management?

Answer: Discovery — recognizing the need for a product, planning — creating a roadmap to plan the product’s development, and development — the various sprints through which a product is developed are three major areas of product management.

• What are the 7 steps of product planning?

Answer: Concept development, competitive analysis, market research, MVP development, introduction, product lifecycle, and sunset are the seven steps of product planning.

• What are the 5 dimensions of product management?

Answer: Reliability, usability, functionality, maintainability, and efficiency are the five dimensions of product management.

• What are the 4 P's of product management?

Answer: Product, price, place, and promotion are the 4Ps of product management which represent four crucial aspects product teams should simultaneously focus on while developing a product. 

• What are the 5 phases of the product management process?

Answer: Idea generation, screening, concept development, product development, and commercialization are the five phases of the product management process .

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Product management case studies - Netflix, Spotify, Slack and Airbnb

Case studies play a pivotal role in product management, serving as valuable tools to understand real-world scenarios, learn from past successes and failures, and shape future strategies. 🎯💡

The Importance of Case Studies in Product Management 🔍📚🚀 ​

In this article, we explore the significance of case studies in product management and how they provide actionable insights, inspire innovation, and drive effective decision-making. So, let's dive in and discover why case studies are an indispensable asset for product managers! 🕵️‍♂️💼💡

🧐 Gaining Insights from Real-World Scenarios ​

Case studies offer a glimpse into real-life product management experiences, showcasing the challenges faced, strategies implemented, and outcomes achieved. They provide an opportunity to learn from industry leaders and understand how they tackled complex problems, made critical decisions, and achieved success. 💡🎓📊

💡 Inspiring Innovation and Creativity ​

By analyzing case studies, product managers can uncover innovative approaches and creative solutions implemented by successful companies. These success stories can serve as a catalyst for fresh ideas, spark creativity, and inspire new ways of thinking. 🚀💡💭

🚦 Avoiding Costly Mistakes ​

Case studies not only highlight success stories but also shed light on failures and pitfalls encountered by organizations. By studying these failures, product managers can identify common pitfalls, avoid costly mistakes, and make informed decisions based on lessons learned from others' experiences. 🚫💸🚧

🔄 Adapting Strategies to Different Contexts ​

Each case study presents a unique context, market dynamics, and customer segments. By examining a range of case studies, product managers can gain insights into how strategies and approaches differ based on industry, company size, target audience, and other factors. This adaptability is crucial in developing customized strategies for their own products and markets. 📊🌍🔀

🌟 Validating and Communicating Product Decisions ​

Case studies serve as concrete evidence to validate product decisions and gain stakeholder buy-in. By referencing successful case studies, product managers can showcase the effectiveness of their strategies and build confidence in their decision-making process. This can be particularly valuable when navigating complex organizational structures or addressing skeptics. 💪✅🗣️

📈 Driving Continuous Improvement ​

Through case studies, product managers can identify areas of improvement, spot trends, and drive continuous innovation. By analyzing successful case studies, they can identify best practices to emulate and incorporate into their own product management processes. This constant quest for improvement ensures staying ahead in an ever-evolving market. 🔄📈💡

So, whether you are a seasoned product manager or just starting your journey, embracing case studies as a valuable resource can unlock invaluable insights, inspire innovation, and guide your product management decisions. 🎓🔍🚀

Now, let's delve into some captivating case studies and extract the pearls of wisdom they offer! 💎📚✨

Case Study 1: Netflix - Personalization and Content Recommendation ​

Netflix is a global streaming service that offers a wide range of movies, TV shows, and original content. One of the key challenges for Netflix's product management team was to enhance personalization and content recommendation to improve user engagement and retention.

Challenges Faced: ​

• Content Diversity: With a vast library of titles across different genres and categories, Netflix needed to cater to diverse user preferences and ensure that each user discovered content tailored to their tastes.
• User Retention: Keeping users engaged and subscribed to the platform was essential for Netflix's long-term success in the highly competitive streaming market.
• Discoverability: With an ever-growing library, it was crucial for Netflix to help users navigate and find relevant content easily.

Product Management Strategies Implemented: ​

• Recommendation Algorithms: Netflix developed sophisticated recommendation algorithms that analyzed user viewing history, ratings, and behavior patterns to generate personalized recommendations. These algorithms leveraged machine learning and AI techniques to provide users with suggestions based on their individual tastes.
• Content Tagging and Metadata: Netflix invested in tagging and categorizing its content with rich metadata, including genre, subgenre, themes, cast, and more. This enabled the platform to create personalized content collections and improve search and discovery functionalities. Personalized Thumbnails: Netflix tested and implemented personalized thumbnails that displayed images relevant to individual users' preferences and viewing habits. This approach aimed to capture user attention and increase the likelihood of content selection.
• A/B Testing and Experimentation: Netflix conducted extensive A/B testing and experimentation to optimize the user interface, recommendation algorithms, and user experience. This iterative approach allowed them to continuously improve the platform based on data-driven insights.

Results and Lessons Learned: ​

• Improved User Engagement: Netflix's personalized recommendations and content discovery features significantly increased user engagement and the amount of time users spent on the platform.
• Enhanced User Retention: By consistently delivering content that aligned with individual user preferences, Netflix successfully retained users and reduced churn rates.
• Differentiation in the Market: The focus on personalization and recommendation algorithms helped Netflix differentiate itself from competitors and establish its position as a leading streaming service.

Case study 2: Spotify - Personalization and Discoverability ​

Spotify is a leading music streaming platform with millions of users worldwide. One of the key challenges for Spotify's product management team was to improve personalization and discoverability to enhance the user experience and increase user engagement.

• Content Overload: With a vast library of songs, playlists, and podcasts, Spotify users faced difficulties in discovering new content that aligned with their tastes and preferences.
• User Retention: Ensuring users stayed engaged and retained on the platform was crucial for Spotify's long-term success in a highly competitive market. Catering to Diverse Tastes: Spotify needed to cater to a wide range of musical genres and user preferences to provide a personalized experience for each individual user.
• Recommendation Algorithms: Spotify leveraged advanced recommendation algorithms to analyze user listening patterns, preferences, and behaviors. These algorithms provided personalized recommendations for songs, playlists, and podcasts based on individual user profiles.
• Discover Weekly and Release Radar: Spotify introduced personalized playlists like Discover Weekly and Release Radar, which curated a selection of new and relevant content for each user on a weekly basis. These playlists helped users explore new music and stay up-to-date with their favorite artists.
• User-Curated Playlists: Spotify empowered users to create and share their own playlists, fostering a sense of community and allowing users to discover music based on the recommendations of others with similar tastes.
• Collaborations and Exclusive Content: Spotify forged partnerships with artists, influencers, and podcast creators to offer exclusive content and collaborations. This enhanced the platform's discoverability and provided unique experiences for users.
• Enhanced Discoverability: Spotify's personalized recommendations and curated playlists significantly improved the discoverability of content for users, leading to increased engagement and satisfaction.
• Improved User Retention: By tailoring the user experience to individual preferences and providing fresh and relevant content, Spotify was able to retain users for longer periods, reducing churn rates.
• Differentiation in the Market: The focus on personalization and discoverability helped Spotify differentiate itself from competitors and solidify its position as a leading music streaming platform.

Case Study 3: Airbnb - Scaling Trust and Safety Measures ​

Airbnb is a global online marketplace that connects travelers with hosts offering unique accommodations. As the platform grew in popularity, ensuring trust and safety became a critical focus for Airbnb's product management team.

• Trust Concerns: Trust and safety were paramount for Airbnb's success. Instances of fraudulent listings, host-guest conflicts, and safety incidents posed a challenge in building trust among users.
• Regulatory Compliance: Airbnb had to navigate various legal and regulatory frameworks worldwide, ensuring compliance and addressing concerns related to housing regulations, taxation, and guest safety.
• User Experience: Balancing trust and safety measures without compromising the user experience was essential to maintain the platform's user-friendly nature.
• Verified Hosts and Guests: Airbnb implemented a verification process, encouraging hosts and guests to provide identity verification, social media profiles, and reviews from previous stays to establish trustworthiness.
• Ratings and Reviews: The product management team enhanced the ratings and reviews system, allowing users to share their experiences and provide feedback on hosts and guests. This helped establish accountability and transparency.
• Safety Measures: Airbnb introduced safety features such as secure messaging, 24/7 customer support, and a dedicated Trust and Safety team to address concerns promptly. They also implemented safety guidelines for hosts and guests.
• Regulatory Compliance: Airbnb collaborated with governments and local authorities to ensure compliance with regulations, providing transparency and addressing concerns related to housing regulations and taxation.
• Improved Trust: The implementation of verification processes, ratings, and reviews contributed to increased trust among Airbnb users, fostering a safer and more reliable community.
• Enhanced Safety: The introduction of safety measures and guidelines improved the overall safety of stays, addressing user concerns and reducing incidents.
• Regulatory Partnerships: Collaborating with governments and local authorities helped Airbnb navigate regulatory challenges and establish a legal framework for operating in various jurisdictions.

Case Study 4: Slack - Improving User Onboarding and Adoption ​

Slack is a widely popular collaboration and communication platform used by teams worldwide. As it gained traction in the market, Slack faced challenges in user onboarding and adoption.

• Low User Activation: Many new users signed up for Slack but struggled to fully activate and integrate the platform into their workflow.
• Lack of Engagement: Some users found the platform overwhelming or faced difficulty in navigating its various features, leading to low engagement levels.
• Competition and Alternatives: Slack faced increasing competition from similar collaboration tools, which prompted the need to differentiate and continuously improve its product.
• Enhanced Onboarding Experience: Slack's product management team revamped the onboarding process to provide a more guided and intuitive experience for new users. They introduced interactive tutorials, tooltips, and contextual help to help users understand key features and get started quickly.
• Simplified User Interface: The product management team identified and addressed pain points in the user interface, simplifying navigation and reducing clutter. They focused on improving the overall user experience and making it more intuitive for users to find and utilize the platform's functionalities.
• Integration with Third-Party Tools: Recognizing the importance of seamless integration, Slack's product management team worked on enhancing the platform's capabilities to integrate with popular third-party tools and services. This allowed users to connect their favorite apps and streamline their workflow within Slack.
• Improved User Activation: By implementing a more intuitive onboarding experience, Slack witnessed an increase in user activation rates. New users were able to grasp the platform's key features more efficiently, leading to higher adoption.
• Increased Engagement: The simplified user interface and improved navigation contributed to higher user engagement, as users found it easier to discover and use Slack's features.
• Competitive Edge: By prioritizing user needs and continuously enhancing the product, Slack maintained a competitive edge over alternative collaboration tools in the market.

Conclusion ​

In product management, case studies serve as valuable resources for gaining insights, inspiring innovation, and driving effective decision-making. By analyzing real-world scenarios, product managers can learn from successes and failures, adapt strategies to different contexts, and validate and communicate product decisions. Case studies provide actionable insights, guide product management practices, and ultimately contribute to the success of products and businesses.

So, whether you're a seasoned product manager or aspiring to be one, embracing case studies as a source of inspiration and learning will help you navigate the dynamic landscape of product management and drive impactful outcomes.

Remember, each case study provides a unique perspective and set of lessons, so explore a diverse range of case studies to expand your knowledge and sharpen your product management skills.

• 🧐 Gaining Insights from Real-World Scenarios
• 💡 Inspiring Innovation and Creativity
• 🚦 Avoiding Costly Mistakes
• 🔄 Adapting Strategies to Different Contexts
• 🌟 Validating and Communicating Product Decisions
• 📈 Driving Continuous Improvement
• Challenges Faced:
• Product Management Strategies Implemented:
• Results and Lessons Learned: