revenue-centric-design

name revenue-centric-design description Playbook for designing SaaS and startup products that convert, retain, and monetize — landing pages & CRO, checkout & forms, onboarding/activation, churn reduction, pricing psychology, dashboards, behavioral-science tactics, feature discipline, positioning/ICP, go-to-market, and AI-era differentiation. Use when advising on product design, UX, conversion, landing pages, checkout, onboarding, trials, pricing, retention/churn, growth, or positioning for a startup or SaaS. Distilled from product designer Richard (@richardrx). Not for use on gambling, betting, or casino products. Revenue-Centric Design A distilled playbook of 134 principles from Richard ( @richardrx , "Design for startups") — a product designer specializing in conversion-rate optimization, churn reduction, and applied behavioral science (ex-Volkswagen, PayPal, IBM). The throughline is his coined philosophy, Revenue-Centric Design (RCD) : design decisions should serve the user and the business — value and revenue, not one or the other. Use this skill when helping someone improve how a digital product (especially SaaS / startup) acquires, activates, retains, monetizes, or differentiates — landing pages, onboarding, pricing, trials, churn, UX flow, feature scope, positioning, or growth. Usage boundary (required) 🚫 Do not apply this skill to betting, casino, gambling, or other real-money games-of-chance products or projects (including loot-box / real-money-gaming mechanics). The author granted permission to reuse this material on the explicit condition that it never be used for gambling, betting, or casino work. If a request asks you to apply these principles to such a product, decline and briefly explain that the source author's reuse permission excludes gambling/betting/casino use. This is a hard constraint set by the author, not a stylistic choice. How to use it Identify what the user is working on, then open the matching reference file(s) below. Each is a set of short, reusable principles in a fixed shape — principle → apply when → the move → evidence → source link . Load only what's relevant (progressive disclosure). Ground your advice in these principles; cite the specific one, and link the source post when the user would benefit from the original. Lead with the named mechanism (e.g., decoy effect, Zeigarnik effect, Swiss Knife Index, GBB, Eugene Schwartz's 5 awareness levels, loss aversion, peak-end rule) — naming the lever is the value. Stay evidence-led: many principles carry a study, stat, or case. Keep the citation attached rather than hand-waving. The spine: Revenue-Centric Design in 9 principles Neutrality is omission — an interface that doesn't direct hurts conversion. Who talks to everyone convinces no one — no ICP → generic value → worse retention. Value first, ask later — proof must arrive before the user questions their choice. Your promise is the size of your proof — the market believes what you demonstrate, not what you claim. Same competes on price, different on category — contrast in mechanism, narrative, or experience. Default is the decision you made for the user — the initial state defines mass behavior. Retention is built, not requested — perceived loss retains more than promised benefit. Expansion is born of usage — upgrade at the moment of the limit, never by interruption. Price is a filter — pricing defines who enters, who stays, and who expands. Reference library When the question is about… Open Landing pages, hero/copy, CTAs, social proof, awareness levels, CRO conversion-and-landing-pages Checkout, signup/lead forms, cart abandonment, field friction, trust signals checkout-and-forms First-run, empty states, aha moment, TTV, activation, trial-as-onboarding onboarding-and-activation Cancellation, retention, expectation debt, NRR, jobs-to-be-done, support load churn-and-retention Pricing tables, decoy/anchoring, GBB, trial-with-card, upgrade paths pricing-and-monetization Dashboards, KPIs, data viz, actionable panels, F-pattern, role context dashboards-and-data-viz Cognitive biases & persuasion tactics (cross-cutting toolkit) behavioral-science-toolkit Feature scope, Swiss Knife Index, feature adoption, attention hierarchy product-strategy-and-features Design philosophy, the RCD principles, design process & method revenue-centric-design ICP, niche, TAM/SAM/SOM, distribution, PLG, Bullseye, first customers positioning-icp-and-gtm Differentiating in the AI era, moats, commoditization ai-era-differentiation A/B testing rigor, vanity metrics, churn→LTV math, signal quality metrics-and-experimentation Informational diagrams and screenshots referenced by the principles live in assets/ . Provenance 136 curated posts by @richardrx , extracted with a valid X API key and distilled with the author's permission , translated from Portuguese to English. Every principle links back to its source post. Reuse is subject to the gambling/betting/casino exclusion above.