Product Discovery

What is product discovery?

Product discovery is figuring out what your customers need so you can build the right products and features. It’s about making sure you invest time and resources wisely, solving real problems.

Start with research. Talk to your users. Conduct surveys and interviews to gather insights. Understand their pain points and needs. This helps you avoid building features based on assumptions.

Next, ideate. Brainstorm potential solutions to the problems you’ve identified. Involve your team in this process to get diverse perspectives. Prioritize ideas that offer the most value to users.

Move on to prototyping. Create a minimum viable product (MVP) to test your ideas. An MVP lets you validate your solution without spending too much time or money on full development. Keep it simple but functional.

Finally, test and refine. Gather feedback on your MVP. Use this input to make improvements. Iterate until your product meets user requirements and solves their problems effectively.

By following these steps, you ensure that the final product aligns with customer needs and delivers real value. This approach saves time, reduces costs, and enhances user satisfaction.

Examples of product discovery

Example 1: Social media analytics tool

Problem: Marketers need to track the impact of posts across multiple channels.

Solution: Develop a tool that compiles data automatically. This saves time for creative tasks.

Example 2: Online meeting scheduling app

Problem: Sales teams need flexible scheduling options for internal and external meetings.

Solution: Create a feature allowing different availability settings for various meeting types. This reduces scheduling conflicts.

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What builders love about us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
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