Company Context

InsightHub is a B2B SaaS company that provides customer feedback analytics tools to mid-market product teams. The company has 3,500 paying customers, strong retention, and a growing enterprise segment, but leadership believes the product roadmap is increasingly driven by internal opinions rather than validated user needs.

Problem

The Head of Product wants to launch a new research initiative before committing engineering resources to a major AI-assisted insights feature. In the past, research projects at InsightHub have produced long reports but unclear decisions: teams learned interesting things, yet still debated what to build next. As a result, research cycles take 6-8 weeks, stakeholder confidence is low, and only 30% of research outputs directly influence roadmap decisions.

You are the product manager responsible for defining success for this research project before it starts. Your goal is not to design the feature itself, but to ensure the research effort has clear objectives, decision criteria, and measurable outcomes so the company can decide whether to invest in the feature.

Deliverables

1. Define what “success” means for this research project before any interviews or analysis begin.
2. Identify the key user segments and decisions the research must inform.
3. Propose the research questions, outputs, and metrics that would determine whether the project was successful.
4. Explain trade-offs in scope, speed, and rigor, and how you would align stakeholders upfront.
5. Describe how research findings should translate into a product recommendation or next-step decision.

Constraints

• You have 4 weeks to complete the research project.
• Research team capacity is limited to 1 researcher and 1 PM.
• Budget only supports 12 customer interviews and lightweight survey work.
• Leadership expects a clear go / no-go / iterate recommendation at the end of the project.
• Engineering wants enough clarity to avoid building a low-value feature, but does not want research to delay roadmap commitments.