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Yuno Learning: Building Marketing Channels For Online Business

By: Rudranil Chakrabortty, Bishakha Majumdar

In April 2020, Yuno Learning Global Private Limited, an entrepreneurial venture that offered online training for International English Language Testing System examinations, wanted to optimize its…

• Length: 15 page(s)
• Publication Date: May 10, 2021
• Discipline: Marketing
• Product #: W21213-PDF-ENG

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In April 2020, Yuno Learning Global Private Limited, an entrepreneurial venture that offered online training for International English Language Testing System examinations, wanted to optimize its digital marketing and increase the number of prospects who subscribed to the company's program. The founder and chief executive officer had to decide among multiple marketing channels and funnels to choose the option that maximized value for the marketing effort, and he had to make that decision in the midst of the COVID-19 pandemic, when all businesses were being affected by the move to online interaction.

Bishakha Majumdar is affiliated with Indian Institute of Management Visakhapatnam.

Learning Objectives

The case is intended for use in undergraduate- and graduate-level courses on digital marketing, marketing analytics, marketing strategy, digital business models, and entrepreneurship. The case reviews the marketing strategies adopted by a firm in online business and demonstrates the nuances of channel and funnel analytics by which a firm can arrive at data-driven marketing decisions. After working through the case and assignment questions, students should be able to do the following: Understand the online education industry and its scope and challenges. Understand the online marketing channels for an online business and evaluate their effectiveness through marketing channel analysis. Discern the elements of an online marketing funnel and evaluate the effectiveness through funnel analysis. Understand the processes of marketing channel and funnel analytics and their roles in entrepreneurial decision-making.

May 10, 2021

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Yuno Learning: Building Marketing Channels For Online Business

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Publication Date: May 10, 2021

Source: Ivey Publishing

In April 2020, Yuno Learning Global Private Limited, an entrepreneurial venture that offered online training for International English Language Testing System examinations, wanted to optimize its digital marketing and increase the number of prospects who subscribed to the company's program. The founder and chief executive officer had to decide among multiple marketing channels and funnels to choose the option that maximized value for the marketing effort, and he had to make that decision in the midst of the COVID-19 pandemic, when all businesses were being affected by the move to online interaction. Bishakha Majumdar is affiliated with Indian Institute of Management Visakhapatnam.

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Yuno Learning: Building Marketing Channels For Online Business PESTEL Analysis

MBA Case Pro Case Study Solution | Term Papers | Essays | Assignment

M BA case pro PESTEL Analysis of case study "Yuno Learning: Building Marketing Channels For Online Business" includes 6 parts - Political Factors, Economic Factors, Social Factors, Technological Factors, Environmental Factors, and Legal Factors. Case Study "Yuno Learning: Building Marketing Channels For Online Business" is written - By Rudranil Chakrabortty and Bishakha Majumdar and.

Political Factors that Impact Yuno Learning: Building Marketing Channels For Online Business

Stability of the political system, antitrust and other competitive issues, data privacy laws, government regulations, political activism and protests, government policies, political intervention, intellectual and property rights, russia ukraine war, taxation policies, economic factors that impact yuno learning: building marketing channels for online business, fiscal and monetary policies of various governments post covid, global slowdown, natural disasters and climate emergency, rising energy costs because of russia ukraine war, rising inflation, rising real estate prices, currency risks, increasing wages in emerging economies, economic inequality and income distribution, rising unemployment rates, social factors that impact yuno learning: building marketing channels for online business, consumer behavior, customer loyalty and recommendations, diversity and inclusivity at workplace, increasing urbanization, labor practices and unions, cultural differences, digital technology and market expansion, data privacy and security, demographic changes, health and services products boom, technological factors that impact yuno learning: building marketing channels for online business, 5g and other mobile innovations, investments in automation and robotics, expansion of internet of things (iot), cloud computing and saas services, machine learning and artificial intelligence, augmented reality and virtual reality, ai and other voice input technologies, internet penetration, personalization of product offerings, foray into adjacent markets, environmental factors that impact yuno learning: building marketing channels for online business, renewable energy strategy, e-waste and other wastes, reduction of paper based packaging, packaging and logistics emissions, sustainability efforts across the value chain, customer awareness, heating and water resources, corporate social responsibility, carbon footprint of warehouses and distribution centers, conservation and sustainable practices, legal factors that impact yuno learning: building marketing channels for online business, different taxes and laws in various countries, copyright infringement and counterfeit problem, labor laws compliance, protection of intellectual property rights, business law and other practices, environmental laws compliance, consumer activism, anti trust laws, different regulations for digital content, cyber security safeguards.

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Getting Started: How Yuno Works

What is yuno learning .

Yuno Learning is a platform that helps connect instructors and learners throughout the globe. We provide learners the luxury to learn from home and instructors the flexibility to work from home.

We also make sure that instructors are provided with all the necessary resources such as lesson slides, practice questions and other teaching material so that their entire focus is on doing what they love, which is teaching.

What do you need to teach at Yuno?

A quiet room: Deliver your classes in a quiet room. Set your routine to make sure that there are no interruptions and background noise.

A fast computer: Use a fast and reliable laptop or desktop. You should have both a good quality camera and a microphone. Delivering classes from mobile or tablet is strictly prohibited. 

Fixed-line WIFI connection: Ensure that you deliver the classes through a fixed-line broadband connection, available to you through a wire or Wifi for uninterrupted teaching experience. Delivering classes through your phone’s hotspot is allowed ONLY in rare cases such as when you’ve run out of backup power (see below) or if the internet lines are down due to inclement weather. You need to inform Yuno staff in advance.

Inverter or power backup device: A power backup for your device and Wifi that allows for uninterrupted access is required. Your power backup is useful ONLY if it allows you to deliver classes without ANY interruption. For e.g. in the event of power failure, if your PC or WiFi shuts down even for a few seconds, it cannot be considered as an uninterrupted source of power backup. There are many inexpensive products available in the market that provide uninterrupted power, if you need to make a purchase. You can contact Yuno staff for details. 

Here are some of the products on Amazon that you can look at for Wi-Fi power backup:

Resonate Router

4G hotspot:  Ensure a 4G hotspot to compensate for WiFi failure or network issues. As mentioned earlier, teaching classes through mobile hotspot will ONLY be allowed in rare cases.

Video ON for classes: It’s mandatory to always have video ON for your classes.

Proper lighting: A good lighting is also essential to make your classes more interactive and to give it a professional appearance. 

Creating your Account

You need to sign up as an instructor on our website to start teaching with us. To create the account follow below steps:

• Create a new gmail id for Yuno such as: [email protected]
• After creating a new gmail id, click here: Become an Instructor

• Enter your mobile number and click “Sign up with Google”.
• Use your new gmail id to fill up the sign up form.
• Once you finish signing up, you’ll receive a Zoom account Activation email on the same id. 
• Click on “Sign in with Google” to activate your Zoom account. 
• Our support team will be in touch with you the entire time to guide and help you create your account.

Getting familiar with Yuno Learning website

The Instructor interface has five main tabs: Home, My Courses, People, Insights and Explore.

When you log in to your Yuno Instructor Account you are on the Home screen.

The Home screen has two submenus, Upcoming and Ongoing, Past.

Upcoming and Ongoing displays classes that are about to happen or already happening. 

Past option displays the list of all classes you have already taken.

Besides this, the Home screen also helps you to schedule a new class by clicking on the Schedule New Class button. Additionally, you can edit or delete an already scheduled class.

To know how to Schedule, Edit or Delete a class click here.

My Courses screen displays all the courses you are taking along with their brief descriptions. 

 To view batches in a particular course you can click View Batches. A sub screen will appear that shows Upcoming & Ongoing and Past batches.

The People tab helps you to manage your learners or students.

It has two submenus, All and Groups

 Under All you can find the names, email ids and phone numbers of all of your learners (in case you want to get in touch with them) .

Under Groups, you’ll find all the batches that are allocated to you. A group is basically a collection of students who’ll be taking up a particular course from you. 

You can also create a new group of students according to their needs, levels or your preferences by clicking on New Group. For instance, you may want to create a separate group for weaker students belonging to different batches who want to understand a specific topic. 

To know how to create, edit or delete a Group(s) click here.

The Insights tab provides instructors with important data metrics so they can self-govern the quality of teaching.

Within the Insights tab, you’ll see 3 different tabs – Overview, Enrollments and Reviews.

Each tab is tailored to help you see the data that’s most relevant to accomplish your teaching goals. The Overview tab shows you some important metrics that reflect on the quality of your teaching. We have carefully selected these metrics.

You’ll see 5 key data metrics: Active Enrollments, Completed Enrollments, Classes Delivered, Reviews and Attendance. You’ll also see Goals Achieved and Ratings & Reviews.

In the Enrollments tab, you’ll see the batch details of all of your Active Learners. You can use various filter options to filter out the records you want to view. 

Reviews tab contains all the reviews given by your learners. 

The Explore tab gives you access to educational material in the form of videos, articles, worksheets and practice tests. You can refer to these resources to enhance your subject knowledge even further. 

View Profile

You can view your profile by clicking on your profile image and selecting My Profile.

Filling Availability hours

You can also add or modify your availability hours. Click on your profile picture and select settings. Click on the Availability tab to fill your hours of availability and we’ll assign you new batches accordingly.

Logging out 

To log out click on your profile image and click Logout at the bottom of the menu that appears.

Yuno Learner Account

A Yuno Leaner account consists of only 2 tabs: Home and Explore.

Home screen has two submenus, Upcoming and Ongoing & Past.

Upcoming and Ongoing displays the list of upcoming classes that have been scheduled by the instructors.  

To attend a class, the learner clicks on the “Launch class” button and will be directed to the virtual classroom where class will take place. 

Past option displays the list of recordings of all the classes the learner has already attended. 

Using the Explore tab, learners can browse through various courses and educational resources. These learning resources could be practice quizzes, engaging videos, ebooks and informative articles. Our content marketing team works with freelancers around the country to publish tens of new pieces of content each week.

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Yuno learning: building marketing channels for online business pestel analysis russia ukraine war, pestle analysis of yuno learning: building marketing channels for online business in light of russia ukraine war.

In April 2020, Yuno Learning Global Private Limited, an entrepreneurial venture that offered online training for International English Language Testing System examinations, wanted to optimize its dig...

Yuno Learning: Building Marketing Channels For Online Business case study written by By Rudranil Chakrabortty and Bishakha Majumdar and has business operations that directly and indirectly are impacted by Russia Ukraine war. Some of the PESTEL Analysis factors that are impacting the Yuno Learning: Building Marketing Channels For Online Business business environment are – War in Russia and Ukraine, loss of market opportunities in Russia & Ukraine, crypto currency frauds and crash , financial collapse in emerging markets , end of an era of easy liquidity, rising housing debt and increasing mortgage rates, increasing interest rates , slowing growth rates across the world , increasing defence spending , big tech shares collapse , high inflation , increasing food and fertilizer prices , and geopolitical developments such as increasing competition between US and China Check out more Harvard Business Review Case Studies Solutions

19. Food Crisis [Social & Economic Factors]

Business in a hyper political world [political & economic factors], high private debt [political & economic factors], increasing defence budgets [political & economic factors], lockdowns in china [political & economic factors], increasing cost of climate change and natural disasters [environmental factors], extremely high government debt [political & economic factors].

Order a Yuno Learning: Building Marketing Channels For Online Business PESTEL / PEST / STEP Analysis now

Increasing cost of doing business [Economic Factors]

Bursting of crypto bubble [economic factors], high inflation rate across the western world [ economic factor ], increasing cost of fertilizers [social & economic factors], slowing growth rate [political & economic factors], technology war / chips war [technology factors], high probability of recession in united states [economic factors], increase in commodities prices [political & economic factors], over reliance on supply chain based out of china [economic factors], emergence of ai and other automation technologies [technology factors], increase in wages in united states, eu, and china [social & economic factors], emerging markets financial collapse [political & economic factors], books and references.

Ahir Gopaldas and Anton Siebert (2022 July August) "What You’re Getting Wrong About Customer Journeys", Harvard Business Review , 92 Linda A. Hill, Emily Tedards, and Taran Swan (2021) "Drive Innovation with Better Decision-Making", Harvard Business Review 86 Dyer, J. H., & Hatch, N. (2004). Using Supplier Networks to Learn Faster. Sloan Management Review, 45(3), 57–63 Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120 Dyer, J. H., Kale, P., & Singh, H. (2004, July–August). When to ally and when to acquire. Harvard Business Review , 109–115

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Exploring generative ai at harvard.

Jessica McCann

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Leaders weigh in on where we are and what’s next

The explosion of generative AI technology over the past year and a half is raising big questions about how these tools will impact higher education. Across Harvard, members of the community have been exploring how GenAI will change the ways we teach, learn, research, and work.

As part of this effort, the Office of the Provost has convened three working groups . They will discuss questions, share innovations, and evolve guidance and community resources. They are:

• The Teaching and Learning Group , chaired by Bharat Anand , vice provost for advances in learning and the Henry R. Byers Professor of Business Administration at Harvard Business School. This group seeks to share resources, identify emerging best practices, guide policies, and support the development of tools to address common challenges among faculty and students.
• The Research and Scholarship Group , chaired by John Shaw , vice provost for research, Harry C. Dudley Professor of Structural and Economic Geology in the Earth and Planetary Sciences Department, and professor of environmental science and engineering in the Paulson School of Engineering and Applied Science. It focuses on how to enable, and support the integrity of, scholarly activities with generative AI tools.
• T he Administration and Operations Group , chaired by Klara Jelinkova , vice president and University chief information officer. It is charged with addressing information security, data privacy, procurement, and administration and organizational efficiencies.

Klara Jelinkova, Bharat Anand, and John Shaw.

Photos by Kris Snibbe/Harvard Staff Photographer; Evgenia Eliseeva; and courtesy of John Shaw

The Gazette spoke with Anand, Shaw, and Jelinkova to understand more about the work of these groups and what’s next in generative AI at Harvard.

When generative AI tools first emerged, we saw universities respond in a variety of ways — from encouraging experimentation to prohibiting their use. What was Harvard’s overall approach?

Shaw: From the outset, Harvard has embraced the prospective benefits that GenAI offers to teaching, research, and administration across the University, while being mindful of the potential pitfalls. As a University, our mission is to help enable discovery and innovation, so we had a mandate to actively engage. We set some initial, broad policies that helped guide us, and have worked directly with groups across the institution to provide tools and resources to inspire exploration.

Jelinkova: The rapid emergence of these tools meant the University needed to react quickly, to provide both tools for innovation and experimentation and guidelines to ensure their responsible use. We rapidly built an AI Sandbox to enable faculty, students, and staff to experiment with multiple large language models in a secure environment. We also worked with external vendors to acquire enterprise licenses for a variety of tools to meet many different use cases. Through working groups, we were able to learn, aggregate and collate use cases for AI in teaching, learning, administration, and research. This coordinated, collective, and strategic approach has put Harvard ahead of many peers in higher education.

Anand: Teaching and learning are fundamentally decentralized activities. So our approach was to ask: First, how can we ensure that local experimentation by faculty and staff is enabled as much as possible; and second, how can we ensure that it’s consistent with University policies on IP, copyright, and security? We also wanted to ensure that novel emerging practices were shared across Schools, rather than remaining siloed.

What do these tools mean for faculty, in terms of the challenges they pose or the opportunities they offer? Is there anything you’re particularly excited about?

Anand: Let’s start with some salient challenges. How do we first sift through the hype that’s accompanied GenAI? How can we make it easy for faculty to use GenAI tools in their classrooms without overburdening them with yet another technology? How can one address real concerns about GenAI’s impact?

While we’re still early in this journey, many compelling opportunities — and more importantly, some systematic ways of thinking about them — are emerging. Various Harvard faculty have leaned into experimenting with LLMs in their classrooms. Our team has now interviewed over 30 colleagues across Harvard and curated short videos that capture their learnings. I encourage everyone to view these materials on the new GenAI site; they are remarkable in their depth and breadth of insight.

Here’s a sample: While LLMs are commonly used for Q&A, our faculty have creatively used them for a broader variety of tasks, such as simulating tutors that guide learning by asking questions, simulating instructional designers to provide active learning tips, and simulating student voices to predict how a class discussion might flow, thus aiding in lesson preparation. Others demonstrate how more sophisticated prompts or “prompt engineering” are often necessary to yield more sophisticated LLM responses, and how LLMs can extend well beyond text-based responses to visuals, simulations, coding, and games. And several faculty show how LLMs can help overcome subtle yet important learning frictions like skill gaps in coding, language literacy, or math.

Do these tools offer students an opportunity to support or expand upon their learning?

Anand: Yes. GenAI represents a unique area of innovation where students and faculty are working together. Many colleagues are incorporating student feedback into the GenAI portions of their curriculum or making their own GenAI tools available to students. Since GenAI is new, the pedagogical path is not yet well defined; students have an opportunity to make their voices heard, as co-creators, on what they think the future of their learning should look like.

Beyond this, we’re starting to see other learning benefits. Importantly, GenAI can reach beyond a lecture hall. Thoughtful prompt engineering can turn even publicly available GenAI tools into tutorbots that generate interactive practice problems, act as expert conversational aids for material review, or increase TA teams’ capacity. That means both that the classroom is expanding and that more of it is in students’ hands. There’s also evidence that these bots field more questions than teaching teams can normally address and can be more comfortable and accessible for some students.

Of course, we need to identify and counter harmful patterns. There is a risk, in this early and enthusiastic period, of sparking over-reliance on GenAI. Students must critically evaluate how and where they use it, given its possibility of inaccurate or inappropriate responses, and should heed the areas where their style of cognition outperforms AI. One other thing to watch out for is user divide: Some students will graduate with vastly better prompt engineering skills than others, an inequality that will only magnify in the workforce.

What are the main questions your group has been tackling?

Anand: Our group divided its work into three subgroups focused on policy, tools, and resources. We’ve helped guide initial policies to ensure safe and responsible use; begun curating resources for faculty in a One Harvard repository ; and are exploring which tools the University should invest in or develop to ensure that educators and researchers can continue to advance their work.

In the fall, we focused on supporting and guiding HUIT’s development of the AI Sandbox. The Harvard Initiative for Learning and Teaching’s annual conference , which focused exclusively on GenAI, had its highest participation in 10 years. Recently, we’ve been working with the research group to inform the development of tools that promise broad, generalizable use for faculty (e.g., tutorbots).

What has your group focused on in discussions so far about generative AI tools’ use in research?

Shaw: Our group has some incredible strength in researchers who are at the cutting edge of GenAI development and applications, but also includes voices that help us understand the real barriers to faculty and students starting to use these tools in their own research and scholarship. Working with the other teams, we have focused on supporting development and use of the GenAI sandbox, examining IP and security issues, and learning from different groups across campus how they are using these tools to innovate.

Are there key areas of focus for your group in the coming months?

Shaw: We are focused on establishing programs — such as the new GenAI Milton Fund track — to help support innovation in the application of these tools across the wide range of scholarship on our campus. We are also working with the College to develop new programs to help support students who wish to engage with faculty on GenAI-enabled projects. We aim to find ways to convene students and scholars to share their experiences and build a stronger community of practitioners across campus.

What types of administration and operations questions are your group is exploring, and what type of opportunities do you see in this space?

Jelinkova: By using the group to share learnings from across Schools and units, we can better provide technologies to meet the community’s needs while ensuring the most responsible and sustainable use of the University’s financial resources. The connections within this group also inform the guidelines that we provide; by learning how generative AI is being used in different contexts, we can develop best practices and stay alert to emerging risks. There are new tools becoming available almost every day, and many exciting experiments and pilots happening across Harvard, so it’s important to regularly review and update the guidance we provide to our community.

Can you talk a bit about what has come out of these discussions, or other exciting things to come?

Jelinkova: Because this technology is rapidly evolving, we are continually tracking the release of new tools and working with our vendors as well as open-source efforts to ensure we are best supporting the University’s needs. We’re developing more guidance and hosting information sessions on helping people to understand the AI landscape and how to choose the right tool for their task. Beyond tools, we’re also working to build connections across Harvard to support collaboration, including a recently launched AI community of practice . We are capturing valuable findings from emerging technology pilot programs in HUIT , the EVP area , and across Schools. And we are now thinking about how those findings can inform guiding principles and best practices to better support staff.

While the GenAI groups are investigating these questions, Harvard faculty and scholars are also on the forefront of research in this space. Can you talk a bit about some of the interesting research happening across the University in AI more broadly ?

Shaw: Harvard has made deep investments in the development and application of AI across our campus, in our Schools, initiatives, and institutes — such as the Kempner Institute and Harvard Data Science Initiative. In addition, there is a critical role for us to play in examining and guiding the ethics of AI applications — and our strengths in the Safra and Berkman Klein centers, as examples, can be leading voices in this area.

What would be your advice for members of our community who are interested in learning more about generative AI tools?

Anand: I’d encourage our community to view the resources available on the new Generative AI @ Harvard website , to better understand how GenAI tools might benefit you.

There’s also no substitute for experimentation with these tools to learn what works, what does not, and how to tailor them for maximal benefit for your particular needs. And of course, please know and respect University policies around copyright and security.

We’re in the early stages of this journey at Harvard, but it’s exciting.

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