PMF Hypothesis Tracker

A customizable PMF Hypothesis Tracker in Google Sheets (or Notion) can act as a living document to track and test key assumptions around product-market fit.

The tracker includes:

• Hypothesis Column: Outline the core PMF hypotheses, such as:
  • We will achieve an optimal balance between platform control and personalized recommendations for users.
  • SMBs will pay a premium for faster integrations with their existing systems.
• Persona Column: Assign each hypothesis to one or more customer personas (e.g., enterprise clients, SMBs, consumers).
• Metrics/Validation Criteria Column: Define the key metrics to test the hypothesis (e.g., engagement rates, customer acquisition cost, retention rate).
• Testing Methods Column: Detail the methods used to validate the hypothesis (e.g., user interviews, beta test results, A/B testing).
• Outcome/Decision Column: Track the outcomes of hypothesis testing (e.g., validated, refuted, needs iteration).

Development Logs

The Development Logs repository can be organized into folders by key areas of early-stage development and PMF discovery. These logs serve as reference material for new startups facing similar issues.

Example structure:

• MVP Development → Sub Folder: Tech Challenges → UI/UX Design
• Product-Market Fit → Sub Folder: Persona Mismatches
• Sales and Product → Sub Folder: Sales-Product Alignment → Beta Test

New startups can easily reference past portfolio companies' experiences to avoid common mistakes. For example, if a startup is struggling with onboarding complexity, they can search through the MVP Development folder to find solutions like redesigning tutorials or using automated onboarding tools that previous companies implemented.

Collaboration can be encouraged by having portfolio companies regularly update their logs with lessons learned, mistakes made, and successful solutions.

Product Beta Testing

• Set up automated feedback collection tools (e.g., Typeform, UserTesting, or in-app feedback tools) to gather qualitative and quantitative data during the closed beta.