Overview
This recipe provides a method to evaluate the impact of special events (such as site renewals, rebranding, first-purchase incentives, or membership program updates) based on the following points:
- Change in the quality and initial purchasing behavior of new customers before and after the key event: This involves comparing new customers from the period before the key event to those after it (e.g., customers who made their first purchase in the 4 weeks before event X vs. those in the 4 weeks after).
- Change in the quality and behavior of existing customers before and after the key event: This focuses on existing customers, analyzing their order data to see how their behavior changed before and after the key event.
How to Use
1. Compare Metrics of New Customers Before and After the Key Event (e.g., Average Purchase Amount)
Typically, customers who join after the event might have a shorter lifetime, resulting in lower purchase frequency or lifetime value (LTV). For more accurate evaluation, use the "Insights" feature to narrow down the order period.
2. Compare Detailed Order Data of New Customers Before and After the Key Event (e.g., Differences in First Purchase Products, Distribution of Average Purchase Amount)
Using period filters to specify corresponding periods will allow for a more precise comparison.
3. Analyze Differences in Existing Customer Behavior Before and After the Key Event Using "Insights" (e.g., Differences in Purchased Products, Purchasing Cycles)
Specify the same length of period before and after the event using period filters for a more accurate comparison.
Comparing New Customers
In this example, assume the key event X occurred on April 1, 2024. Adjust the actual dates when creating segments.
🕘 New Customers in 4 Weeks Before Event X
- Segment Name: 🕘 New Customers in 4 Weeks Before Event X
- Description: This segment consists of customers who made their first purchase in the 4 weeks leading up to the key event.
- Criteria: Customers who placed an order between March 4, 2024, and March 31, 2024, with the order being their first purchase.
Create this segment in ECPower
🕒 New Customers in 4 Weeks After Event X
- Segment Name: 🕒 New Customers in 4 Weeks After Event X
- Description: This segment consists of customers who made their first purchase in the 4 weeks following the key event.
- Criteria: Customers who placed an order between April 1, 2024, and April 28, 2024, with the order being their first purchase.
Create this segment in ECPower
Analyzing Existing Customers
In this example, assume the key event X occurred on April 1, 2024. Adjust the actual dates when creating segments.
⏱️ Existing Customers Before+After
- Segment Name: ⏱️ Existing Customers Before+After
- Description: This segment consists of customers who made purchases both before and after the key event.
- Criteria: Customers who placed an order on or before March 31, 2024, and also placed an order on or after April 1, 2024.
- This segment is useful for analysis after a significant amount of time has passed since the key event.
Create this segment in ECPower
📝 Existing Customers Present Before Key Event
- Segment Name: 📝 Existing Customers Present Before Key Event
- Description: This segment consists of customers who made a purchase before the key event.
- Criteria: Customers who placed an order on or before March 31, 2024.
- This segment is useful for analysis when not much time has passed since the key event.
