Company Context

PulseFit is a digital health company with 2.4 million monthly active users across its fitness app and wearable device ecosystem. The company generates $180M in annual revenue, primarily from subscriptions ($12/month premium plan) and hardware sales. PulseFit is preparing to launch PulseFit Coach Pro, an AI-guided premium coaching feature aimed at improving retention and increasing ARPU among existing subscribers. The company is the #3 player in its category behind two larger incumbents, and leadership believes the launch could add $20M+ in annual recurring revenue if positioned correctly.

Strategic Situation

The Chief Strategy Officer must decide how to structure customer research over the next 10 weeks to inform pricing, messaging, target segment, and launch channel decisions for Coach Pro. The debate is whether to prioritize qualitative research (e.g., interviews, focus groups, diary studies) to understand user motivations and unmet needs, or quantitative research (e.g., surveys, usage analysis, conjoint, pricing tests) to validate market size, willingness to pay, and likely conversion. The CEO wants a recommendation on the right mix of research approaches and how each should be used to support a go-to-market decision.

Data Points

Additional facts:

• Internal survey of 8,000 users found that 41% say they want more personalized coaching, but only 18% say they would “definitely pay more”.
• Beta usage data from a lightweight prototype showed 27% weekly engagement among 1,200 invited users, but the sample was skewed toward highly active premium subscribers.
• Competitor A launched a similar premium coaching add-on at $9.99/month and disclosed a 6% attach rate among paid subscribers.
• Competitor B bundled coaching into its top-tier plan, increasing ARPU by 11% but also raising support costs by 18%.

Deliverables

You are advising the CSO. Address the following:

1. Explain the difference between qualitative and quantitative research in this business context.
2. Recommend when PulseFit should use each approach and what decisions each method should inform.
3. Propose a practical research plan for the next 10 weeks, including sequencing and sample design.
4. Assess how the research choice affects go-to-market risk, pricing confidence, and launch timing.
5. Recommend the final research mix and justify it with business impact.

Constraints

• Research budget is capped at $400,000.
• Leadership needs a launch recommendation in 10 weeks.
• Product, marketing, and data science teams can support only one major survey and one structured qualitative program before launch.
• The board expects a clear estimate of likely adoption and revenue impact, not just directional customer feedback.