What's better than acquiring one new customer?
It sounds like a trick question, but the answer isn't "acquiring two customers." It's actually retaining an existing customer. *
For more detailed strategies on Customer Retention please find ReplyCo's article - https://replyco.com/brainery/32-customer-retention-strategies/
There’s a common misconception that businesses need to acquire new customers if they want to make more money.
Getting new customers is obviously beneficial and can help your business grow. But that’s not the only way to boost your profits.
Focusing on customer retention is a much more viable and cost-effective marketing strategy.
In fact, it will cost you six to seven times more money to acquire a new customer than it will to retain an existing one.
Not only is retention cheaper than acquisition, but it also has a very high ROI. Research shows that you can increase your profits anywhere from 25-95% just by increasing your retention rates by 5%.
The repeat customers graphs show the customer retention rate, how many times a customer bought at your business in a specific date range, this will help you identify the Frequency and see how many of your customers are loyalty vs new.
What is cohort analysis?
A cohort analysis is a powerful and insight method to analyze a specific metric by comparing its behavior between different cohorts, or groups, of users. This type of data analysis is most often segmented by user acquisition date, and can help businesses understand customer lifecycle and the health of your business and seasonality.
Cohorts? Segments? Shifting curves? We get it — this stuff gets confusing fast.
But here’s the deal: It’s actually pretty simple.
To start, we’ll strip away the jargon and define the cohort analysis in plain English.
“Cohort” is just a fancy word for the group.
Instead of looking at all users in one broad view, cohort analysis breaks them down into groups. Think platform, acquisition date or channel, specific customer behavior — anything you want.
Cohort analysis measures user engagement over time, making it easy to spot friction points and behavioral patterns.
Essentially, it gives you a data-driven approach to understanding exactly what makes users fall in love with your app — so you can keep making it happen.