Cohort analysis is the single best way to see and understand your brand's churn rate. Given existing customers spend on average 73.72% more than new ones, finding ways to maximize ret russia contact number whatsapp ention rate is one of the primary benefits of cohort retention analysis.
Image Credit
3. Identify behavioral segments to create personalized campaigns and experiences for
Lastly, you can use cohort analysis to effectively segment customers.
For example, what personal experiences should you create for customers who have recently lapsed versus those that return every week versus those that are brand new to your site. Do customers who come from different ad campaigns act differently? And if so, how can you create better offers for them?
These are the types of questions and answers you can get from using cohort analysis.
Cohort analysis best practices and examples
1. Optimize post purchase campaigns
According to our last study on email marketing statistics, post purchase campaigns converted an outstanding 8.2% of the time.
Cohort analysis allows you to understand when your customers naturally return and make repeat purchases. With this data, you can optimize your post purchase campaigns and augment them with replenishment reminder triggered messages.
Above, Tula uses cohort analysis to understand when their customers naturally make another purchase. They trigger their replenishment emails as reminders before this date, and add on extra incentives after. In this email, they highlight three specific benefits of
Free shipping - "Score free shipping every time"
Bundled gifts - "Enjoy a free gift on us with each order"
2. Transform broad LTV metrics into useful 30 day, 60 day or other payback period metrics
Lifetime value (LTV) is often treated as the holy grail of eCommerce revenue metrics.
However, time matters for both cash flow and ROI calculations. In this regard, payback periods are much more actionable than broad LTV metrics.
From customer acquisition, how often are your customers coming back, how soon are they coming back, and how much are your profiting when they do.
With cohort analysis you can clearly understand how much revenue customers are generating per period.
Below is one example of how to see this data. Here we are charting how much revenue a cohort generates over time.
3. Understand LTV and payback metrics with behavioral segmentation
To make payback metrics more actionable, you should segment the data by various properties. Properties can include
Marketing channels and campaigns - This is especially important if you are using cohort analysis to optimize your ad campaigns.
Products - Determine which products lead to repeat purchases. This is ideal for surfacing which products you should create ad campaigns around.
Customer segments - Finally, your customer segments do not act alike. You can get a better understanding of important segments by pulling them apart from the rest of the data. For example, you may want to look at how first time buyers engage with your brand vs how customers enrolled in your loyalty program engage.
Barilliance empowers eCommerce stores with a variety of out of the box behavioral segmentations. Broadly, Barilliance can track on-site engagements such as which pages are visited, items added to carts, a product display pages viewed.