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Purchase Interval Distributions

Purchase Interval Distributions | Gain Insights for Enhancing Customer Engagement and Retention in Shopify Stores

Last Update:
Aug 12, 2024

In the dynamic world of eCommerce, understanding the timing of customer purchases—particularly the intervals between them—is crucial for maintaining engagement and maximizing retention. The 'Purchase Interval Distributions' report provides Shopify store owners with essential insights into the patterns of customer repurchases, helping to inform targeted marketing and communication strategies.

What's Purchase Interval and Its Definition

Purchase interval refers to the average number of days between purchases for repeat customers. This metric is central to RFM (Recency, Frequency, Monetary) analysis, which categorizes customers by how recently and frequently they've made purchases, as well as the monetary value of those purchases. By understanding purchase intervals, businesses can better determine when a customer is likely active or at risk of lapsing.

Detailed Insights from the "Purchase Interval Distributions" Report

Knowing the average value of purchase intervals is useful, but understanding their distribution is vital for pinpointing when customers typically repurchase. This insight helps in timing marketing efforts effectively, targeting customers precisely when they are most likely to buy again. Additionally, it assists in identifying customer segments that may need specific engagement strategies to boost retention, thereby optimizing your outreach and maximizing customer lifetime value.

⏱️ Popular Purchase Interval Range

Curious about how the repurchase intervals of your segment's customers are distributed? 📊 Check out the histogram to get a clear view! It shows key statistics like the mean, median, and maximum values—so make sure to compare these metrics.

If the average is significantly higher than the median, it could indicate that a subset of high-spending customers is skewing the overall average upward. For instance, when setting thresholds like "R in the RFM segment," consider using the median as a reference, or use the histogram to see where your desired value fits within the overall distribution. 📈

Note1: The repurchase intervals of customers in each segment are automatically divided into deciles (10 equal parts) to create a range (x days to y days). To ensure data accuracy, the top and bottom 5% of the data are excluded when creating these ranges. However, this exclusion is only for range creation, and it does not affect the overall customer count (customers excluded during range creation are still counted in the highest and lowest ranges in the report).

Note2: One-time buyers are not included in this report because they only have a single purchase, which means we can't calculate a span between purchases to determine their purchase interval. Essentially, without a second purchase, there's no way to measure, so their data is considered non-applicable and excluded from this analysis.

Why 'Purchase Interval' Insights Matter

  • Segment-Specific Purchase Cycles: Different customer segments exhibit unique buying cycles. Knowing the distribution of purchase intervals helps determine the optimal times for communication, avoiding the risk of engaging customers too early or too late in their buying cycle.
  • Risk Assessment in RFM Analysis: In RFM analysis, defining the appropriate threshold for when a customer becomes "at-risk" is crucial. Insights from purchase intervals allow businesses to set more accurate thresholds based on when the likelihood of a repurchase begins to decline.
  • Enhancing Lifetime Value: Shortening the purchase interval within targeted customer segments can significantly increase the Average Order Count, thereby improving the overall Lifetime Value of the customer. This is a key strategy for focused marketing efforts aimed at boosting customer retention and engagement.

Use Cases - Recommended Segments Filters

  • Targeted Segment: Utilize insights from the latest purchase interval to fine-tune when you should approach customers. Adding a condition based on the days since their last order allows for more precise targeting, ensuring your communications are timely and relevant.
  • Repeat or Loyal Customer Segments: Analyze patterns from your most loyal customers to understand the average number of days they return to make another purchase. Learning from successful customer behaviors can help replicate these strategies across other segments to enhance retention.

The 'Purchase Interval Distributions' report is an invaluable resource for any Shopify store looking to optimize its customer engagement and retention strategies. By understanding the typical intervals between purchases, you can better align your marketing efforts with customer behaviors, ensuring that communications are well-timed and effective. Leveraging these insights can lead to increased customer loyalty, higher repeat purchase rates, and ultimately, greater success for your store.

Author
ECPower Product Manager

Edited and supervised by Product Manager of ECPower - Shopify Customer Segment & Journey Management, supporting Shopify merchants' CLV growth, CRM strategy and data analytics.

Change log

22 Apr. 2024 Article Published

12 Aug 2024 Updated

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