In today's fiercely competitive eCommerce landscape, acquiring new customers is undoubtedly important. However, it is equally—if not more—essential to nurture those customers into loyal advocates who repeatedly engage with your brand and make multiple purchases over time. By identifying the specific products that drive higher long-term retention rates, you can optimize your marketing strategies, tailor your product offerings, and ultimately boost customer loyalty and lifetime value.
In this article, we will guide you through the process of analyzing your product performance to identify those hidden gems that have the power to transform one-time buyers into devoted, repeat customers. With this data, you'll gain the knowledge and tools necessary to make data-driven decisions that propel your eCommerce success to new heights.
Method #1: Identify top products by repeat sales
One approach to identifying which of your products yield the highest long-term retention rate is to create a report that shows the repeat sales percentage for each product. This report will provide you with a clear view of the products with the highest long-term retention rates, allowing you to make informed decisions about which products to focus on for improvement and promotion.
Keep in mind that the "Repeat Sales %" metric from Shopify is calculated as Total Sales from Repeat Customers divided by Overall Total Sales. With that said, breaking this metric down by Product Titles will show you the percentages of sales that came from repeat purchases (anything other than a customer's first purchase) compared with overall sales data for each product.
To create this Custom Report, you can:
Pull in Repeat Sales % (and any other metrics you'd like to see alongside this, such as Average Order Value, Total Sales, or the raw Repeat Sales data)
Add a Product Title Breakdown
Sort the report to show you the top rows by Repeat Sales %
Adjust your date range to correspond with the dates you'd like to analyze
In this example, you can see that the top product in the set date range for repeat sales was the "Polar Bear Blanket" product. This tells us that about 64% of the total sales that came from that product were repeat sales, with a total of $54.19K.
Customer Retention from Sample Products:
In high customer acquisition cost environments, selling sample products can be a great strategy for achieving cost-effective customer acquisition, higher conversion rates, and opportunities for targeted marketing.
Further, analyzing the retention rates from these sample products allows you to identify the most effective samples, optimize marketing efforts, nurture customer loyalty, and ultimately maximize revenue and profitability.
If you'd like to analyze retention rates specifically from sample products, you can create a Custom Report to visualize this data in the below steps:
Pull in Repeat Sales % (and any other metrics you'd like to see alongside this, such as Average Order Value, Total Sales, or the raw Repeat Sales data)
Add a Product Title Breakdown
Add a filter for "Customer First Order Product Title" - This is where you can add a rule to only visualize the data where customers' first orders contained a specific sample product title.
Sort the report to show you the top rows by Repeat Sales %
Adjust your date range to correspond with the dates you'd like to analyze
In this example, we're filtering the report for Customer First Order contains "Sample", so we're only seeing data for customers that purchased some sample product first. You can see that the top product in the set date range for repeat sales was the "Holiday Scents Essential Oil" product. This tells us that about 94% of the total sales that came from that product were repeat sales, with a total of $17.46k.
Method #2: Identify top products by Lifetime Value (LTV)
Another approach for identifying your product performance over time is to look at your Customer Lifetime Value (LTV) by product. Your LTV tells you approximately how much an average customer will spend at your store by calculating Gross Sales divided by Total Customers. While analyzing this metric won't tell you specifically which products a customer purchased in their repeat purchase behavior, it will allow you to assess the performance of individual products in terms of their ability to drive long-term customer value.
Fortunately, Polar Analytics has a pre-built LTV by Product Table, accessible directly within the Products Tab. This table enables you to quickly identify the products that yield the highest LTV, Average Order Value, and Purchase Frequency on your store. Keep in mind that you can apply filters directly to the table to segment this data further (by collection, product type, or even sales channel).
Pro Tip: Play around with sorting this table by LTV, Average Order Value, and Purchase Frequency to get a more wholistic understanding of your product performance. Keep in mind that even if a product has a low Average Order Value, it could still have a high LTV depending on the purchase frequency, giving you more insight into customer retention by product.
With this analysis, you can make more informed targeted marketing decisions based on which products seem to yield the highest customer retention. If you'd like to learn more about how to explore retention analysis in Polar, check out our guide to the Retention Tab here.