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Choose Qual vs Quant Research

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Your question is Choose Qual vs Quant Research. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

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Problem

Company Context

StreamSpace is a mid-stage B2B collaboration software company with 25,000 paying teams and a growing self-serve product. The company competes on ease of use and fast onboarding, but activation for new teams has stalled at 41% over the last two quarters.

Problem

The Head of Product asks you to improve new-team activation for StreamSpace's workspace setup flow. Several open questions have emerged: why invited teammates fail to complete setup, whether the current checklist is confusing, and which onboarding changes would most improve activation. The research team has limited bandwidth and can only run one major study in the next 4 weeks before roadmap planning.

You need to decide which questions should be answered qualitatively versus quantitatively, and how to sequence the work. Existing data shows: 68% of admins create a workspace, but only 41% of teams complete three key setup actions within 7 days; invited users drop off most heavily at the permissions and integrations steps; NPS comments mention both "confusing setup" and "too many steps," but the product team disagrees on what that means.

Deliverables

  1. Define the core research questions you would ask before choosing a method.
  2. Explain how you would decide whether each question is better answered qualitatively, quantitatively, or with a mixed-methods approach.
  3. Recommend a research plan for the next 4 weeks, including prioritization and sequencing.
  4. Describe the trade-offs of your approach, including confidence, speed, and decision usefulness.
  5. Define how you would know the research produced actionable product direction.

Constraints

  • One UX researcher and one product analyst are available part-time.
  • You have 4 weeks before QBR roadmap commitments.
  • Engineering can instrument minor event tracking changes, but no major rebuild of analytics.
  • Budget supports at most 12 user interviews or one survey to up to 2,000 users, not both at full scale.
  • Leadership expects a recommendation tied to activation impact, not just a research summary.