Your guide to Shopify’s cohort analysis
Your guide to Shopify’s cohort analysis | Track new customer retention and value over time
Shopify offers customer data analytics so that you can track the behaviour of customers on your Shopify store, where they came from, what they’re buying and whether they make a repeat purchase. One feature that Shopify has added is customer cohort analysis, only available for Shopify Plus members.
A customer cohort in Shopify is a group of customers with similar characteristics that have been grouped, like a customer segment. You can get behavioural cohorts or a monthly cohorts - a group of new customers that made their first purchase in the same month.
Monthly cohort analysis allows small business owners to get an insight into their loyal customer base and post-purchase customer behaviour. This article explains how to read your Shopify report and how to use cohort analyses to improve your e-commerce marketing strategy.Click on one of the links to jump to that section
- How to read cohort analysis reports
- How to read your cohort table
- How to read your cohort retention analysis chart
- Using cohort analysis in your e-commerce strategy
- Frequently Asked Questions
How to read your cohort Analysis reports
Understanding Shopify analytics, specifically your cohort analysis reports is essential to start incorporating this customer data into your e-commerce strategy. To find cohort analysis go to Shopify Admin, then Analytics, and then select the Cohort Analysis report on your dashboard to view the information. You will see a cohort analysis table and customer retention data below. You can also view a 6-month data snapshot in the Shopify App
In this report, you can see a cohort overview when you select All or a specific time frame in the cohort column. You can view the following data:
- Gross sales and net revenue for each customer cohort
- Average order value and average orders per customer
- New or repeat customers and total orders
- Top products by cohort
- Top marketing/acquisition channels by cohort
- Top sales channels (online store or POS)
- Predicted spend tier
- The ratio of subscription sales vs one-time purchases
- Top location for each cohort
Use this section to get an insight into what your cohorts are doing, spending, purchasing and where they came from. You can even categorise your cohorts based on their predicted value to your business; this will be essential for your marketing strategy.
How to read your cohort table
The cohorts are segmented by the month that they made their first purchase. The table shows data over the subsequent since the cohort’s first purchase. The table includes data from the previous 12 months.
You can view cohort data in terms of their:
- Average order value
- Gross sales
- Net sales
- Number of customers
- Repeat customer rate
You can use this table to assess your customers cohort value since their first purchase.
How to read your cohort retention analysis chart
This chart plots the months since the first purchase along the x-axis and the returning customer rate on the y-axis. The graph can compare data from two different cohorts; it can also compare returning customer rate year on year. You can also customise the period that you wish to compare to an acquisition cohort.
The graph starts initially high and then drops off after several months as returning customer rate drops off and levels out. You can use this to analyse when your returning customer rate drops significantly and when you could be retargeting customers. You can also use this chart to calculate the customer lifetime value in added revenue from repeat custom.
Using cohort analysis in your e-commerce campaign
Data collection is vital for formulating an effective marketing campaign; the more data you have, the better your strategy could be. Use cohort analysis to decide where to invest revenue into retargeting campaigns to retain valuable customers.
Suppose specific cohorts are more valuable than others; found in the highest predicted spend tier. In that case, you can specifically target your high-value and loyal customers to ensure you keep them as customers.
Suppose you notice that three months after the first purchase, returning customer rates drop. In that case, you may want to implement a retargeting campaign to entice customers to your Shopify store at the point when they may start to lose interest.
You can also use cohort analysis to decide where your marketing budgets should be allocated. Suppose your returning customer rates are consistently high, and your customer lifetime value is also high. In that case, you may want to consider allocating ad spend to customer acquisition, since you already have good customer retention. However, if your customer retention is low, you will want to allocate budget to retargeting campaigns. You may also want to improve your brand experience to get customers to make a repeat purchase.
You can use the returning customer rate to calculate the lifetime value of your cohorts. Track the additional revenue from each cohort – from returning customers. If this additional revenue is low, you will want to focus on post-purchase cash multipliers such as reward schemes or customer perks. You will also want to allocate budget to retargeting.
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Frequently Asked Questions
How can you use Shopify cohort analysis to reduce customer churn?
You can use cohort analysis to predict post-purchase behaviour. To reduce churn, you will need to implement a structured retargeting campaign that encourages customers to return to your site. Retarget new customers at the point when customer retention tends to drop off, usually at around three months. Comprehensive Shopify analytics data will help you decide who to target and when.
How does Shopify cohort analysis help your e-commerce business?
It gives you an snapshot of your customer behaviour after their first purchase. You can learn how to improve customer retention for your Shopify store. Customer retention is usually much more cost effective than customer acquisition because existing customers are already familiar with your brand and have already been convinced to make a purchase.
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