pricing-research

What problem does it solve?

Pricing-research eliminates guesswork in SaaS and developer-product pricing by collecting competitor pricing, market signals, and willingness-to-pay inputs before you model or decide on tiers.

Core Features & Use Cases

• Competitor pricing intelligence: Capture tier names, price points, feature gating, value metrics, free-tier limits, add-ons, and pricing page UX from direct, adjacent, and API-only benchmarks.
• Review and sentiment mining: Extract price sensitivity and perceived value signals from sources like G2/Capterra, Reddit, Hacker News, and relevant social discussions.
• Internal data analysis inputs: Organize internal usage/segment patterns (when available) such as adoption rates, churn correlations, and expansion triggers to ground recommendations in evidence.
• Willingness-to-pay (WTP) design: Produce framework-ready research plans (e.g., Van Westendorp, Gabor-Granger, conjoint) including survey instruments, sampling guidance, and how to interpret outputs.
• STIG/GRC and API gateway context: Incorporate compliance and procurement-specific pricing factors and developer/API value structures (rate limits, overage mechanics, authentication/key pricing).

Quick Start

Use the pricing-research skill when you need to research competitor pricing benchmarks for a SaaS product by asking: "Research competitor pricing for my SaaS, including tier comparisons, value metrics, review sentiment, and a willingness-to-pay research plan."