How We Solved A Product’s Biggest Pain Point in 2022

#DataBlog

2022 saw a drastic positive change in user sentiment towards our product with the largest subscriber base, as a team made up of engineers, BAs, product managers and customer success specialists combined forces to address the product’s number one challenge at the start of the year; report load times. The team’s combined expertise led to the most used product reports running 10x faster in December vs in January, a reduction in monthly Snowflake costs and a measurable improvement in both user sentiment and engagement; NPS increased from 9 in Feb 2022 to 45 in Nov 2022. This is the story of why we did what we did, how it was done, what the outcome was and what we learned.

Complexity doesn’t come for free

To understand the full context of the product’s performance journey we have to re-rewind back to September 2021 and the Great Merge. Prior to the Great Merge, our two most subscribed retail insights products ran reports using different datamarts, each suited to the respective product requirements. Product A would snappily surface the latest promotional week’s transactional metrics on a Thursday morning, then Product B would get the same numbers plus customer data the following Monday. Happy days.

However, the differing datamarts surfaced small discrepancies in some metrics values in the product’s UIs, some of which were highlighted by users who worked with both tools. In parallel, we wanted to launch report…