Bucket

Unlocking feature value with product analytics & qualitative feedback – all in one place.

  • Consistently evaluate features: Use the built-in STARS framework for a structured, data-driven approach to feature evaluation.

  • Segment-specific insights: Easily compare engagement across customer segments and audit impact over time.

  • Qualitative feedback integration: Gather qualitative feedback right from within Bucket and enrich your quantitative engagement metrics. 

  • Audit matrix: Compare key feature usage, adoption rates, and more to ensure feature relevancy over time.

  • Real-time slack reporting: Receive automated feature reports directly in Slack.

  • Tailored for B2B SaaS: Designed with the specific needs of B2B SaaS product teams in mind, from Product Managers to CPOs and Engineering teams.

Bucket

How Bucket Works

Bucket is engineered to be the all-in-one solution for B2B SaaS product teams looking to optimize feature value and customer satisfaction. At its core, Bucket employs the STARS framework to offer a structured, repeatable approach to feature evaluation.

  1. Data collection: Bucket starts by collecting quantitative product insights, such as feature engagement metrics, through easy integrations with platforms like Segment.

  2. Qualitative feedback: Alongside these metrics, Bucket gathers qualitative feedback directly within your app, allowing you to understand not just the 'what' but also the 'why' behind user behavior.

  3. STARS framework: All this data is then processed through the STARS framework. This enables you to segment your audience and understand how they have tried, adopted, retained, and are satisfied with each feature.

  4. Audit matrix: For a macro view, Bucket's audit matrix allows you to compare key feature usage across different customer segments and time frames, ensuring that your features remain relevant and impactful.

  5. Real-time reporting: Automated reports and insights can be delivered directly to Slack, enabling your team to make immediate, data-driven decisions.

  6. Actionable insights: Bucket's analytics and feedback loop empower various roles—Product Managers, ProductOps, CPO/CTOs, and Engineers—to act quickly and consistently in delivering features that customers actually care about and use.

By combining quantitative metrics with qualitative insights and structuring them through the STARS framework, Bucket provides a holistic view of feature engagement and customer satisfaction. This enables product teams to make informed decisions, from feature development to iterations.

This is the Bucket feature report. Get a quick overview on how a new feature is performing and dive deeper as needed.
This is the Bucket feature report. Get a quick overview on how a new feature is performing and dive deeper as needed.
Use the audit matrix to compare key feature usage, adoption rates and much more.
Use the audit matrix to compare key feature usage, adoption rates and much more.
See the performance of all your features in one place. Create custom segments to compare feature adoption for different customer segments, pricing plans or geographical locations.
See the performance of all your features in one place. Create custom segments to compare feature adoption for different customer segments, pricing plans or geographical locations.
Bucket

Get more out of Bucket with Segment

Bucket’s recommended way of ingesting data is via Segment. Implement Bucket by sending identification and tracking events from your web application to Bucket’s API.

Bucket fully supports Segment’s Identify, Group, and Track events, meaning you can get started with Bucket without changing any code! Using Segment also means you can pipe historic data into Bucket from the get go and get historic feature analytics for your existing features.

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Integrate Bucket with Segment

Segment makes it easy to set up Bucket.