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Cohort Analysis for E-learning Platforms

In this post, Anton Sazhin explains how e-learning platforms can increase their LTV, decrease their cost of acquisition, and forecast repeat sales. A useful Google Spreadsheet for calculations included.

Status Quo

Half a year ago, when we entered the B2C market with our CORE platform, we faced a metrics dilemma. Our team comes from the academic sphere, so we are used to thinking about educational results, the formation of competencies, students’ skills, and other similar issues. We were greatly disappointed to discover that in-depth analytics can’t be easily applied to e-learning because the business itself measures financial metrics rather than “digital footprints.” That’s why we tried to merge the characteristics of online courses and their financial indicators. 

Static and Dynamic Online-Courses

We split online courses into two types: static and dynamic. Static courses are those that don’t change throughout their lifecycle. Dynamic courses, however, are created with continuous development and improvement in mind.

We share the view that constant progress is essential. However, to know what to improve and where to grow, you have to measure everything. 

Every product has two main financial metrics: CAC (customer acquisition cost) and LTV (lifetime value).

The first metric isn’t commonly used in the e-learning industry, which has focused on the customer funnel, targeted ads, and automated webinars for a long time. In the case of LTV, everything is far more complicated. The LTV for an educational platform is completely different to the LTV for an app or a video game. Here’s how:

  • An app or a game has several appropriate use-case scenarios. The development team’s main objective is to get users on the right track and retain them in the product. In education, there is no “correct” path. Every student’s journey is unique. Customization and individualization of education is the dominant trend these days, but it’s very hard to classify due to the large impact of the human element.
  • The main engagement with an app occurs during the actual interaction with the product. In education, interactions happen in the mind of the user, where you can’t measure metrics. That’s why there are hundreds of pedagogical theories and psychological approaches related to “effective teaching.”
  • A common subscription model doesn’t work well for online courses because a product designed to suit a large cohort of average learners doesn’t provide a sufficient level of individualization.

New Realities in COVID-19 Times

In our current COVID-19 reality, and with the development of the sharing economy, new possibilities are arising for experts and professionals related to the creation of educational products.

  1. Major educational players can’t provide an individual approach for every student. A small online school has two key advantages: personal entrepreneurial initiative and flexibility in terms of individualization. With the proliferation of bots and autoresponders, students value professional feedback because it accelerates the growth of their competencies. 
  2. The same course may be highly effective for one user and absolutely useless for another. Targeting doesn’t solve this problem. In some ways, the e-learning niche resembles mass-market fashion retailers, as many average courses try to make the same educational program fit every student. 
  3. Expertise matters. Over the last year, a lot of true experts have transitioned to the online world. These experts don’t work with “large brands” but create their own educational platforms. UGC platforms like YouTube, TikTok, and Instagram have proved that you don’t need expensive studios and multi-million-dollar budgets to gain views.

That was a long introduction. Now let’s get to models and calculations.

Cohort Analysis for Increasing Effectiveness

How can you customize your e-learning platform and how it’s linked to financial metrics?

The majority of course creators target an extremely broad market, form an attractive offer, promise their students the moon and stars, launch traffic and automated webinars, then gather their profits. This approach has actually worked well in the past. However, today, the cost per lead is very high, it’s hard to grab an audience’s attention, and the unit economy is broken.

How to Decrease CAC and Raise LTV

This is where cohort analysis from product marketing comes into play. In this case, we’ve changed it a bit to suit the e-learning industry due to the differences mentioned above. For our calculations, we used an Instagram-based scenario.

Here, you can find a Google Spreadsheet that can be used during the creation of online courses and e-learning platforms with an emphasis on LTV rather than CAC. In the next section, we’ll explain all the formulas from the table. 

Stage 1. Diagnostics

Let’s assume that you’ve gathered your first pipeline of students. A lot of businesses get to this stage and rush to launch their next auto funnel. However, we recommend you take a different approach. First, examine your audience and break it down into educational cohorts. Measurements of financial and qualitative metrics should be conducted with these groups in mind. To individualize your program, you have to study your target audience.

We recommend forming cohorts of your target audience based on the following criteria:

  • Level of expertise
  • Educational goals (why students picked your course)
  • Convenient interactional environment (with whom and when your audience likes to study the most)
Measurements of financial and qualitative metrics

Stage 2. Developing an LHS (Learner Health Score) Model for Your Course

Learner Health Score

Learner Health Score is an integral assessment of the importance of all indicators related to the repeated purchase of your ecosystem. You should assign a specific weight to each indicator and, based on the interview, polls, and metrics from your LMS (learning management system), create a table with your metrics. LHS is vital to improving your LTV and decreasing CAC for your platform.

Here are the LHS parameters from our model:

  • Feedback quality. This parameter is determined by the number of negative comments and questions presented to the support team.
  • Educational goals. Did your learners achieve the goals they set at the beginning of your course?
  • Success rate. The success rate is the percentage of learners who finished the course and completed all of the home assignments and tests.
  • Free time. The main reason why learners leave the course is a lack of time. You may learn that your target audience doesn’t have enough time for self-development.
  • Capacity to pay. This indicator can be measured based on the number of credits and loans for the course.
  • Loyalty. Previously, NPS (net promoter score) was a widespread technique to measure customer loyalty. However, it’s quite an outdated approach. Instead, you can ask your users a question like:

“How would you feel if this course never existed?

  1. No changes
  2. I would be disappointed
  3. I would be very sad

A good outcome here would be no less than 40% of respondents choosing option B.

Learner Retention Rate (LRR) measures how many students demand a refund. On average, this LRR will be no less than 95%. Sometimes, you can run into users who buy the course but never actually attend it. They decrease the LHS rate but don’t influence the LRR because they don’t ask for a refund. However, it’s unlikely that these students will buy your course again.

CAC is the cost of client acquisition for the course.

CO, or cost of ownership, gathers all collateral expenses for student support, spending on the educational platform, chatbots, automatic newsletter systems, and more.

Active Loyal Learners (ALL) = LHS * LRR. This is the percentage of users who continuously buy courses within your educational ecosystem. 

Stage 3. Creating the Best Educational Program and Delivering Results to Clients

Make users love your courses. Develop engagement techniques, work with your students, and help them achieve their desired results. The higher the LHS, the greater the probability of new purchases. Dividing clients into cohorts improves educational outcomes but puts an additional load on your support team. We recommend keeping chat sizes to between 30 and 100 students. In a perfect world, you should build your educational program around users’ desires. In practice, only 20% of the educational program should be individualized. It is this 20% that helps you win the hearts of your students.

Stage 4. Measuring LHS

At this stage, you have to be honest with yourself and rate your online course. This rate will influence the predictive analytics of further launches. Excessive optimism can lead to unexpected financial losses. To forecast upcoming sales, multiply your LHS by your LRR to get an ALL metric.

Stage 5. Create Matrix of Courses

An average adult will participate in no more than four courses per year. The average course length is one month. That means you have two months to create a new course. The only way to minimize the cost of acquisition is to create a valuable educational program and manage to sell it while students take a break from education.

The basis for an online course matrix:
  • Incremental training level (basic, professional, guru)
  • Provide complementary programs (for instance, the last course covered promotion via Instagram Stories, now it’s time to cover copywriting)
  • Take into account your audience’s specific requirements 

To identify your audience’s real pain points, you have to engage in a dialogue with your students. Analyze their requests and test your hypotheses to build a strong relationship with them. 

How to Improve ALL?

To keep your audience engaged during a break from education, you have to stay in touch. Provide them with free webinars, useful newsletters, exciting previews, and secret chats. 

Unlike other apps or games, you have to retain users in your ecosystem for several months, even when nobody is studying. Otherwise, your students will leave your platform and search for other educational options.

It’s important to understand that in order to create product matrices and ecosystems, you should be a professional in the field you’re teaching. Here’s a link to a table you can use when creating educational platforms with an emphasis on LTV.

Our recommendation:

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