By clicking “Accept All Cookies”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.

A 5 Minute Cohort Analysis in 3 Steps (Part 1)

Álvaro González San Pedro
October 18, 2016

First steps to a cohort analysis

By Álvaro González San Pedro (Associate)

If you’ve never heard about cohorts before, or if you have but you are still unsure of what they mean, this post is for you. If you’ve already used cohorts, but want to deepen your knowledge, jump to Part 2: Run a full stack cohort analysis from scratch (…).

Before getting to cohorts, let’s start from the very beginning. You want your business to escalate, and perhaps even more important, you want investors to believe in it. One condition is absolutely sacred then: at some point in time, the value you can gain from a user during his lifetime (customer lifetime value- LTV) has to exceed the cost of acquiring this new user (Cost of Acquisition or CAC). Otherwise the business will never be profitable. It’ll require external funding eternally and sooner than later investors will grow tired of wasting their money on something that might never pay off (and unfortunately we all know that investors are not exactly known for their patience waiting for results).

What does this mean then? First, that acquiring new users is not always as profitable as we might think; particularly if they don’t end up covering what it initially cost to acquire them. Let’s work with an example; if you spend 100 on marketing and you manage to acquire 10 new users, each has a CAC of 10. If this new user is not expected to generate at least 10 euros of contribution margin during his lifetime as a user (LTV); then the effort might not make sense. Indeed, sometimes it might be wiser to work on retaining already acquired users, than acquiring new ones. So how can we know what to do when?

Let’s do a bit of easy maths. The CAC is quite straightforward to calculate (normally, total marketing cost divided by the number of newly acquired users), so let’s have a look at a client’s future profitability (LTV). The LTV can be calculated up to different periods: up to 12 months (what you make from this client in 12 months), 24 months, etc. The most aggresive managers/investors will target +36-months paybacks in order to boost growth, whilst the more conservative prefer shorter paybacks, sometimees even lower than 6 months. To calculate the LTV just multiply the number of orders that a customer is expected to make over his/her lifetime as a user –say in 36 months– (this is recurrence) and multiply it by your average contribution margin per order. Simply put, LTV = recurrence during a customer’s lifetime x contribution margin.

Calculating your margin is also straightforward; recurrence might be a tad more complicated and this is where cohorts (finally!) come in. In statistics, a cohort is a group of people who share a common characteristic; thus, a cohort could be a group of customers who are from the same city, who are female, who were born the same year, etc. A cohort analysis then is the study of how a certain group of people who share a common characteristic behave across time.

Applied to our field, one of the most important factors that could explain changes in customer behaviour across time is the date in which the customer was acquired: people that become users in similar dates could have reacted similarly to a specific acquisition strategy from the company (for instance, vouchers) or felt the need to use the service/good in the same season, etc. This is important to know. Thus, it has become a standard to define cohorts as the group of people who become first time buyers (FTB) in a given date (usually a given month, sometimes week). For instance, all the new users you gain in September 2016 make up a cohort.

You are now ready to do your own cohort analysis, using our 3-step/5' template. But first, read part 2: “Run a full stack cohort analysis from scratch (…) where you’ll find the Excel file for you to download. Don’t worry, the template we are sharing is as intuitive as possible and you’ll just need 5 minutes to complete the 3 steps by yourself! Stop bothering your tech team with things you can do on your own and let them focus on the hard stuff.

What are you waiting for to try it out? If you have any further doubts with interpreting or updating the data, we’ll be delighted to help out. Email us! If you have any problems with the download please contact us.

**

At Samaipata, we are always looking for ways to improve. Do not hesitate to send us your thoughts. We strive to partner with early-stage founders and to support them in taking their business to the next level. Check out more ways in which we can help here or for all our other content here

And as always, if you’re a European digital business founder looking for Seed funding, please send us your deck here or subscribe to our Quarterly updates here.

Latest News

See also

More insights to better the world through technology

Unlocking Business Expansion with This Strategic Framework

Unlocking Business Expansion with This Strategic Framework

There comes a time within your business where you realise that your team needs additional skill set and expansion. Typically, product-market fit has been established and the opportunity to grow revenue and profit is there.
Read more
Scaling your customer service team: in-house or outsource?

Scaling your customer service team: in-house or outsource?

As an early-stage startup, making the decision to manage your customer service team in-house or to outsource really depends on a variety of factors including where you are as a company in terms of your lifecycle, size and complexity, what your strategic customer service vision & goals are, and finally, what your financial resources and priorities are.
Read more
5 tips to retain top talent in a startup

5 tips to retain top talent in a startup

In a rapid-growth startup, demands can be high, budgets can be low, and processes can be lacking. There’s also strong competition for top talent in the startup environment and it can be challenging to keep talent as other companies also look to acquire people with specific skills, many of which can afford higher salaries.
Read more
Restructuring data teams that are ready to scale: 5 learnings from BlablaCar

Restructuring data teams that are ready to scale: 5 learnings from BlablaCar

In today's interconnected world, data has become a powerful driving force behind innovation and growth. Companies that harness the potential of data hold a competitive edge, and one such company at the forefront is BlaBlaCar. As a pioneer in the carpooling industry, BlaBlaCar has revolutionized the way people travel and the way it leverages data plays a critical role in its business strategy. In this article, we delve into the fascinating world of BlaBlaCar's data team strategy, exploring how we restructured our teams in order to scale.
Read more

What role software can really play in helping us reach net zero goals?

While considerable venture capital investments have already flowed into the software sector, the intensifying climate crisis is pushing the need for radical action to the forefront. Software is currently receiving negative publicity as seen as involving too “shy” of an effort. On the other hand, hardware and infrastructure investments, which were traditionally overlooked by asset-light venture capitalists, are gaining momentum.
Read more

The data challenge in Climate Tech

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros.
Read more
arrow icon
arrow icon