Tracking product metrics in Metabase
· 45 minutes
About this event
In this talk, Conor Dewey, Product Manager at Metabase, went over the ways you can start tracking product metrics and other KPIs in Metabase using features like CSV uploads, conditional formatting, custom expressions, and alerts.
Product Manager, Metabase
Previously Data Scientist at Squarespace and Product Growth at Hugo (Acquired by Calendly).
Conor gave a brief overview of KPI tracking at Metabase and the questions we aim to answer about customer satisfaction, like:
- How satisfied are people using our product?
- What does the journey to being satisfied look like?
- What is stopping people from being satisfied?
In order to show how we track this, Conor explained how to upload a CSV to Metabase to track NPS survey results. For example, you can collect survey results in Google Sheets, add those results to Metabase, and use Metabase to track month-over-month results.
Conor then explained how to create a model from this CSV data, organize it into columns, and apply conditional formatting to different ranges, such as NPS scores. He highlighted promoter scores of 10-9 as green, passive scores of 8-7 as yellow, and detractor scores of 6-0 as red. These colors help designate lower NPS scores from the rest, so your team can decide which ones require further attention.
He also explained how to create custom expressions for NPS scores, like how to apply “promoter” “passive” and “detractor” labels to group results by monthly responses and visualize percentages as a bar chart.
He also showed how to set up an alert on the saved question, so you can get new results automatically in a Slack channel.
Last, Conor talked a bit about the role of customer research and how qualitative data can only get your team so far. You need to use signals as jumping off points and talk to customers to learn more. He also gave a few resources that can help you start tracking product metrics.