How to run a pricing analysis on Starch

Pricing analysis is the process of figuring out whether what you're charging is the right number — and doing it with actual data instead of gut feel or what you set two years ago. That means pulling together conversion rates, churn data, competitor positioning, cost structure, and willingness-to-pay signals, then stress-testing the implications before you change anything. It sounds straightforward. In practice it spans multiple tools, involves judgment calls about which data to trust, and often gets deprioritized until a competitor undercuts you or a renewal conversation goes sideways. What this workflow looks like in practice depends on your business model and what data you already have. Analyzing SaaS pricing tiers looks different from reviewing project-based service rates or auditing a product line's margin by SKU. The questions overlap; the data sources don't. On Starch, you describe the analysis you want — 'show me conversion rates by pricing tier alongside churn by cohort, updated weekly' or 'model what happens to runway if I raise prices 20% but lose 15% of monthly volume' — and Starch assembles the right connections and surfaces to run it. That might mean pulling Stripe subscription data on a scheduled sync, querying your analytics tool live from the integration catalog, or running a scenario model against your actual Plaid transactions. The persona-specific pages below go deeper on how to set this up for your context. Start there if you already know your situation; stay here if you want to understand the workflow first.