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The PIE Framework is a CRO prioritisation model developed by WiderFunnel to help teams decide which pages and experiments to tackle first. PIE stands for Potential, Importance, and Ease. Each candidate page or test idea is scored on these three criteria, averaged into a PIE score, and ranked against other candidates in the backlog. The framework is page-centric by design — it helps you decide where on your site to focus, rather than which individual element to change.
PIE Score = (Potential + Importance + Ease) / 3
Example: Your cart page has a 70% abandonment rate (Potential: 9), it handles 80% of your revenue (Importance: 10), and you need 2 weeks to instrument (Ease: 5) → PIE = 8.0. Prioritise this over a category page that scores 6, 5, 8 → PIE = 6.3.
Ecommerce sites have dozens of page types — home, PLP, PDP, cart, checkout, thank you — and limited testing bandwidth. PIE ensures testing resources go to pages where fixing problems translates directly into revenue, not to pages that are easy to change but don't move the needle. The Importance criterion is particularly valuable for D2C brands: it forces teams to confront whether the page they're excited about actually sees meaningful traffic and contributes to conversions.
The growth team at Sugar Cosmetics is reviewing three pages for their quarterly test roadmap: the product detail page (PDP), the homepage, and the order confirmation page. Running PIE scores: PDP has clear drop-off data from heatmaps (Potential: 8), it's the primary conversion point (Importance: 9), and tests are easy to configure (Ease: 7) → PIE: 8.0. Homepage has brand refresh needs (Potential: 6), decent traffic (Importance: 7), but requires design and dev effort (Ease: 4) → PIE: 5.7. The PDP wins the first sprint, which turns out to be the right call — the team discovers that adding a "shade finder" tool on the PDP lifts add-to-cart rate by 14%.
PIE tells you where to run tests. Once you have selected a high-PIE page, you need to define specific hypotheses for what to change on that page — this is where heatmap analysis, session recordings, and user research feed into your test design.
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