Quickly identify and prioritize cause of conversion drop after a product release

After a code release, JCPenney fast-tracked a fix with IT that saved the company $25K in daily losses or 12% of its annual revenue.


JCPenney pushes releases on a biweekly basis. After one release, the team saw a sudden 6% conversion drop for a major product line. It’s UX team identified a drop in its purchasing funnel via Adobe Analytics, but couldn’t determine the cause. Marketing hadn’t changed any campaigns and IT couldn’t find any problems after retesting the code.

With Quantum Metric, the team could start its investigation where Adobe left off, and identified 9 of 100 new errors that actually had an impact on abandonment. Furthermore, only 3 of the 9 errors were primary causes.

The UX team fast-tracked a fix, and one week later, the drop not only reversed, but sales improved 5% over previous levels.


Watch a 2-minute demo video of this use case:

Use Case Prioritization, Reduce MTTI/MTTR
Team E-commerce, Product, UX
Industry Retail

Interested in Learning More?

Get a demo