Integrating Low Stock Messages in E-Commerce Testing
Introduction
This guide outlines the process of including low stock messages in version 1 (v1) of an e-commerce platform, ensuring that test criteria are met consistently across different platform versions. The expected outcome is to accurately compare user behavior in response to low stock notifications between v1 and the original version (v0).
Step-by-Step Instructions
Understanding the Addition of Low Stock Messages in v1
The first step is to recognize that low stock messages were not present in v0 but are being added in v1. For a product listing page (PLP) test to be considered valid, it should trigger as true for users who would have seen the message in v1.
Identifying Low Stock Criteria across Versions
It's important to identify users in v0 who met the low stock product criteria as if they were in v1. This ensures that the test triggers correctly, even if the user did not see the message in v0, because they would have seen it in v1.
Analyzing User Behavior Based on Messaging
The rationale is to understand whether users in v1 are more likely to interact with the product due to the low stock message compared to users in v0, who did not see the message.
Ensuring Consistent Test Criteria
It's crucial to maintain consistent test criteria by having the test shown true for users who either saw a low stock item message or would have seen it in v0, ensuring a fair comparison of user behavior across both versions.
Confirming Behavior on PDP and CART
Verify that the test is already firing correctly for both variants on the product detail page (PDP) and cart page (CART), as expected.
Addressing Low Stock Messaging on PLP
Ensure that for the PLP, the test shown true triggers for users who see the low stock messaging or who would have seen it had they been bucketed in v1.
Conclusion
By following the steps provided, you can successfully integrate and test low stock messages in your e-commerce platform. This guide ensures that the behavior of users is consistently compared across different versions of the platform, providing valuable insights into the impact of stock-level notifications on user engagement and behavior.
