Why is the Lifetime Revenue Cohort Analysis Important?
Cohort analysis and customer LTV allows you to assess exactly how a group of your users/customers behaved over their lifetimes. Individually too many factors could be responsible for a single customer’s LTV for you to develop accurate assessments. If looking at the overall data, certain assessments may be true for some customers and horribly wrong for others, which could lead to decisions that can cause significant damage to your business.
This kind of cohort analysis can be useful for several different purposes, but the most immediate benefit is often better customer acquisition decisions. Many companies limit their marketing spend to channels that yield profitability on a customer’s first purchase. These companies will pay to acquire customers through a given channel as long as their average first purchase yields more gross margin than it costs to acquire them.
The problem with this approach is that it often results in an under-investment in growth. If your competitors are marketing based on a deeper understanding of buying behavior, they will outgrow you. The lifetime revenue cohort analysis helps you to understand the consequences of expanding your customer acquisition spending, and it provides an easy way to convey this to the rest of your team.
If future customers behave like existing customers, then acquiring customers for a higher CPA will result in a predictable payback period. Depending on the cash position of the business, you can define what payback period you are comfortable with, find the relevant spot on the chart, and spend accordingly. Additionally, you can use this analysis to see if you are getting better at onboarding, engaging, and generating revenue from the users you acquire.
Determine what questions you want to answer
The point of an analysis is to produce actionable information you can use to improve your business, products, user experience, etc. To ensure that happens, it is important that you are answering the right questions. Answering the wrong questions can make your analysis essentially useless.
Define the metrics that will be able to help you answer the question
A cohort analysis requires you to identify measurable events such as a subscription start and cancel dates as well as specific properties such as the value of a customer’s monthly payment.
Define the specific cohorts that are relevant
Each person in a cohort must share a related yet distinguishable trait that separates them from the other cohorts. The most common trait used to do this is date, such as the date at which each customer starts using the product, but this can be segmented further to examine differences between other traits.
Perform the cohort analysis
There are various methods you can use to perform a cohort analysis. In Excel it is generally done using pivot tables and data visualization. In this example we are going to use data visualization to examine churn rate, monthly revenue and customer lifetime value.
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