Blog

In the SaaS industry, we’ve largely adopted agile development as our preferred methodology for releasing software. Scoping down and time-boxing features ensures that product teams release often and don’t waste months on a grand feature that ultimately doesn’t work.

I’m very pleased to announce that Peter Müller has joined Bucket!

It’s common to track company-level features using attributes. For example, at Bucket, we’re tracking if customers use our weekly reporting feature. We do this by passing an attribute called "weekly_reporting" via Segment’s "group" call.

A feature can be anything in your product, big and small. It can be user facing, like a key interaction in the UI, a minor preference-toggle or even a background job. Features are different and have varying usage patterns.

We’ve added typeahead search to the various dropdowns in the Bucket UI. It’s now much faster to find the event you’re looking for when tracking a new feature.

This week, we’re adding to last week’s release, which focused on making the feature adoption criteria configurable. Today, we’ve added another configuration, which allows you to toggle the “Stopped”-metrics on or off in your report.

One of the most powerful features on Bucket, is the pre-defined adoption states. Out of the box, Bucket buckets (see what we did there?) companies into the following states based on their historic feature usage pattern. Until today, those state definitions were hard-coded.

Our charts now show a partial data marker when looking at the current week’s incomplete data set, and we've added a daily digest to our Slack integration that lets you track new feature adoption.