Track new feature

Tracking features is the core of using Bucket. Adding a feature is simple: you need to click the "Track Feature" button in the top right, and then fill out the form below:

The fields do the following:

Feature Name:

Provide a name that's a good internal reference for the feature.

Example: "Messaging"

Feature Views

Feature views enable users to categorize features in Bucket and group them together.

Example: You can create views such as "All" features, "Key Features", and "New" features.

Source

Set whether a feature is tracked through events or through attributes. Most features function with events: you send a message and it pings an event to Bucket. By measuring the number of events you can analyze whether users are merely trying a feature or if they have adopted it.

Attribute-based tracking is useful for features that are activated once, such as integration with Slack. Companies don't continually activate Slack integration every time they want to use it, but you will still want to track whether users have churned from the feature and if they are satisfied.

To learn more about event-based tracking vs attribute-based tracking, check out this blog:

When to track features with events or attributes

Event-based tracking

Event name

Choose an event that is fired whenever a user interacts with your feature. Remember that you want this to be the last event in the feature sequence

We suggest following this naming convention in order to keep event names consistent and explicit.

Example: Message Read or Message Sent (And not Message Opened Modal)

Event Attributes

Optionally, filter the event by certain event attributes.

Example: location is "modal"

Target Segment

Once you've started tracking a new feature, you can also configure the feature's target audience and adoption state KPIs.

Target Segmentlets you define which companies are relevant for your feature. For example, some features are only accessible to paying customers. Learn more here

Attribute-based tracking

Company Attributes

Chose company attribute(s) that indicates active feature usage.

Example: has_slack_integration = true

Target Segment

As with event-based tracking, you can define a target segment for attribute-based features

Status

The current state of the feature, i.e. is it in planning, or has it already been released? By default, all features will be set to "Planning" initially, and Bucket will automatically set them to "Evaluating" once tracking data is detected from the feature.

Evaluation Period

The length of time the feature should remain in the "Evaluating" status. Once this time period has elapsed, features will need to be moved to the "Done" or "Canceled" statuses. For more on the different status options, see the Feature evaluation guide