From adee80a8577b85a08e9ad7bcdc1dc8db49020c38 Mon Sep 17 00:00:00 2001 From: kelsey-brown Date: Tue, 9 Apr 2024 17:41:23 +0000 Subject: [PATCH] squash! Prettier --- content/departments/data-analytics/cody_analytics.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/departments/data-analytics/cody_analytics.md b/content/departments/data-analytics/cody_analytics.md index 4da711c8ccb3..bac4cc175c17 100644 --- a/content/departments/data-analytics/cody_analytics.md +++ b/content/departments/data-analytics/cody_analytics.md @@ -16,7 +16,7 @@ Below is an overview of a few of the key metrics we're using to measure and iter **Metric: Retention** -- **Definition:** The percentage of users who trigger an active product event (based on our [product user definition](#cody-product-dau)) 1 week after signup. Retention can be measured at other intervals besides Week 1 as well (such as Day 1, Day 7, Week 4, etc) but our company-level retention KPI will standarize on Week 1 +- **Definition:** The percentage of users who trigger an active product event (based on our [product user definition](#cody-product-dau)) 1 week after signup. Retention can be measured at other intervals besides Week 1 as well (such as Day 1, Day 7, Week 4, etc) but our company-level retention KPI will standarize on Week 1 - **Why this metric:** As we continue to ship improvements to Cody, retention will be key to understanding how much value users are getting from the Cody. - **Source of truth:** This data is logged by eventlogger, and accessed via [Amplitude](https://app.amplitude.com/analytics/sourcegraph/chart/3pmjrguv)