Introducing the feature evaluation workflow
Todo -> Doing -> Done. But what happens when a feature is marked as Done? It’s deployed and live with the customers. That’s undoubtedly the most crucial time in the feature cycle, and that’s exactly where existing workflows stop today.
At Bucket, we want to add a final step to the feature delivery workflow: The Evaluation step. In the Evaluation step product teams make sure that their customers actually like the feature they’ve released. We believe most features should go through this step.
We’ve come to expect almost every other step in the feature delivery workflow, like testing, deploying to production etc, to be automated. We believe that the evaluation of features should also be as automated as possible.
Last week we announced how you can plan features on Bucket. The Planned state is for when the feature is in development.
Today, we’re announcing the remaining states: Evaluating and Done. Together, they make up a complete, automated feature evaluation workflow.
When you log in today, you’ll see these columns: Planned -> Evaluating -> Done.
When a Planned feature is deployed (and marked as Done in JIRA or Linear), it automatically goes into Evaluating mode on Bucket.
Bucket reports engagement metrics on all features in Evaluating mode to Slack every Monday.
When you have enough insights to decide if the feature has reached the impact you expected from it, you mark it as Done on Bucket. If the feature needs more work, you rinse and repeat the workflow.
We’ve also shipped the ability to set a Release date for each feature. You can set it manually or let Bucket do it. Once data for a feature starts flowing in, the feature changes state automatically from Planned to Evaluating, and Bucket will automatically set the release date to the current date if a date isn’t already set. You can modify the release date later, if needed.
The release date will also appear in the Slack reports, so you can easily track how long a feature has been in evaluation.
After 2-4 weeks, you should start to see leading indicators on adoption and churn, which will indicate feature success or not. If you need to dive deeper and speak with customers, Bucket makes that very easy, too.