Introducing Planned features
Adding tracking to a feature release is often an afterthought or forgotten altogether. Many engineers have received a DM from a PM around the time of feature release saying something frantic like:
“did you remember to add tracking? we need to track this feature!”
We believe there’s a better workflow for this, and that workflow unlocks some very useful automations.
Today, we’re introducing Planned features on Bucket!
When a feature goes on the roadmap, there’s often a story issue created for it in the issue tracking of choice. It describes the customer problem, maybe a potential solution and ideally also a basic tracking implementation specification (tracking spec). The tracking spec describes which instrumentation to add to the code, so it can be measured and evaluated post-release.
Now, you can plan features on Bucket and hand them off to engineering as a ticket that includes the exact tracking spec - right from the Bucket UI.
Here’s how it works.
First, track a new feature. In the new feature modal, you can now enter events and/or attributes that don't exist yet. In this example, we want to fire off the “Pinned card” event whenever a customer pins a card in our product UI.
Once created, you now have a feature tracking spec that you can share with your engineering team. It contains all the information needed for the engineers to know exactly what event or attribute to track before releasing this feature.
You can share the feature tracking spec as a link, copy as Markdown or create a Linear issue straight from Bucket. You can also add a note about when to fire the event.
With the feature created on Bucket, the system will listen for events with the name “PinnedCard”. When engineering is done with the feature and deploys it, Bucket will get notified as soon as a user interacts with the feature. If you want to, you can get a Slack notification when that happens.
Besides getting the feature tracking spec out of DMs and into the issue tracking system, there’s another huge benefit to creating planned features: Automated feature evaluation! 🥁
Automated evaluation
We want to empower product teams to make impactful features. To validate impact, you need to track customer engagement. If customers aren’t adopting the feature or are churning away fast, you need to act on it.
With Planned features, Bucket will know when a new feature is released and can therefore automatically start to report feature engagement metrics to your team. By default, Bucket will send you a feature engagement report to Slack every Monday – empowering everyone in the product team (engineers, PMs and designers) to act on bad engagement or adoption.
With the Bucket insights, the product team can quickly determine if the feature is “Done for now” or needs another iteration.
If you need to dig deeper and ask for customer feedback, Bucket makes it easy to figure out which customers that are relevant to reach out to. Here’s an example of that:
That’s our workflow: Repeatable and automated. Just how we like it!
More updates soon.