How to use Cohort Analysis in Marketing
How do you know if your marketing campaigns are effective? You gather data, it is that simple. The evaluation and interpretation of this data can help you quantify your organization's performance and take the necessary steps to optimize it. But if every data point doesn’t track to a business goal, the numbers can easily obstruct decision-making. We often lack strategic plans for using data and we end up tracking information that is not relevant to business goals. Even worse, analysis paralysis is taking over, hence an action to improve the campaigns' result is never made. So, what is the solution?
While there are many ways to analyze your data to get insights, cohort analysis is a compelling way to aggregate and quantify user data. Doing a cohort analysis is a great way to better understand the effectiveness of a marketing campaign, a new feature or the impact of increasing prices. Rather than analyzing all your marketing data at once, a cohort analysis breaks them into related groups for analysis. These groups (cohorts) usually share common characteristics over a certain period of time. Hence, Cohort analysis allows you to study a group of users who created an account or made a first purchase on the same month and see how they perform over time.
Why it is so useful?
Cohorts provide a clean way of looking at the data. Once a cohort is defined, it is static and it will not change. So, when looking at retention rates by cohort, you can really understand how well you are retaining your customers. If instead you are looking at retention rates across your entire customer base, you will get a mix of older customers (who historically have high retention rates) and newly acquired customers (who generally have lower retention rates). Thus, as you try to decipher why your retention rate may be too low or fluctuating a lot, you won’t really know if it is being impacted by newer customers or older customers.
Cohort reporting allows companies to see patterns clearly across the life-cycle of a customer (or user) rather than slicing across all customers blindly without accounting for the natural cycle that a customer undergoes. By seeing these patterns of time, a company can adapt and tailor its service to those specific cohorts. The cohort analysis grows into an important type of marketing tool, indicating the quality and effectiveness of chosen business activities, as well as giving the ability to predict future events. It helps to avoid rash and superficial decisions, which often happens when we only rely on general indicators.
How can Marketers use cohorts?
Although there are hundreds of cohorts Marketers can create, we should focus our attention on which cohorts will produce the most insightful data. Before you start tracking any cohorts, ask yourself these questions:
Will the data I get from these cohorts produce insights that can change my marketing strategy?
Will I be able to clearly know what is working and what is not on my marketing campaigns?
Will this cohort help me improve my KPIs for this year?
Once you have a clear answer on the questions above, you can start experimenting on creating and tracking some cohorts. Here are a few suggestions:
Signed Up / Purchased, organized by time: Create a cohort that tracks people who visited your site and signed up or submitted a contact form (if you are in B2B environment). You will see when they first visited your site and how long it took them to sign up after their first visit. This can essentially tell you if your marketing campaigns lead people to take immediate action.
Client Retention: Track the number of clients that you acquired within a defined time-span (i.e. January) and monitor for how long they are keep doing business with you (when they lapse). You will learn how well you are performing on retaining new clients and understand why a specific cohort of clients lapsed after a specific time period.
Repurchase Rates: Find the people who have repurchased and then segment the purchases by product categories, marketing channels, or marketing campaigns. In that way, you will be able to understand what are the product categories that make people coming back or if certain marketing channels tend to bring customers that stay longer with your business.
How to get started?
Now that we explained the importance of including cohort analysis into your arsenal, your next question should be 'where to start from?'. If you are fun of Excel, then it is your lucky day since Andrew Chen has created an Excel template that you can download for free here. The idea is that you have to enter only a small amount of data and everything else is calculated automatically. You will have to type in the basic cohort data: How many customers did you acquire in each month and how many of them were retained in each subsequent month. If you also want to see your churn on an MRR basis and get a sense for your CLTV, you’ll also have to enter the corresponding revenue numbers.
In case you want to try something more advanced and you are interested into coding, you can use Python instead. Although Excel is a perfect tool to get your hands dirty and understand how the calculations are made, it does not provide any flexibility and it is time consuming. Calculating cohort metrics can be really complicated. To begin with, there are numerous ways of structuring the cohort table and visualizing the results. Thus, I have written an example of a cohort analysis with Python that you can check on my Github account. Reading and understanding the results is still the more challenging part of the analysis so I spent some time on writing comments and explaining the results further at the end of the code.
Bringing it all together, in today’s highly competitive digital economy, the result that counts is revenue and the only way to ensure your marketing team delivers that result is through data-driven marketing. As Marketing is expected to deliver higher returns and overcome their data paralysis, performing cohort analyses against marketing data is a crucial part of analytics. Fortunately for Marketers, there are hundreds of different cohort analyses they can run and all of which will provide insights that will help them optimize campaigns and performance. Cohort analysis is useful for every department across your organization since it examines the cohort over a period of time and delivers unique insights.
Give it a try and let me know the results!
