How a Single Paywall Experiment Generated $50M – Jeff Morris, Chapter One, Ex-Tinder

In 2018 Tinder A/B tested a toggle in the app's top navigation bar that let users enter a new subscription tier directly. Treated as a small-to-medium 'throwaway' test on the experiment roadmap; the design team opposed adding the top nav. Result was read off the daily revenue dashboard. Guest's broader advice: audit where users can reach premium features and add more prominent paywall entry points; don't bury them in the nav.

Put a paywall on the number of swipes a free user can make per day, after seeing people swipe through their entire city in a few sessions and use auto-swipers. The goal was a healthier marketplace; monetization was a side benefit. General principle: charge for one or two things early, then follow power users to decide which 'superpowers' to gate, considering what share of users should have each one.

Every subscription feature had its own paywall entry point. A dashboard reviewed every morning showed clicks per entry point, conversion rate and the mapped incremental subscription revenue. Features that did not convert were either given more prominent placement or made free. Never moved a free feature behind the paywall.

Moved from a single tier (Tinder Plus) to three subscription tiers with consumables on top, designed as packages for different customers: from a younger, lower-income, often non-US entry subscriber up to whales spending as much as $50,000 a year. Required building new bundles and new features for each segment. Recommended the same to a portfolio company stuck on a single tier.

Replaced a set-and-forget single price from early basic tests with a complex pricing grid driven by many factors, geography first. Pricing work started when the US market saturated and growth shifted to India and LATAM, which had much lower willingness to pay than North America/UK. Advice: focus pricing on your core market first (North America for most US developers).

Paywalls and paid interactions got as much design love as any core feature. Example: in 2017 added a gold shimmer animation to a paywall, about a couple of days of engineering time. Warns against PM-designed paywalls and against too many paywalls making the product feel spammy.

At Tinder, users were asked to subscribe only after the magic moment: getting a match and having a conversation. Contrast: an AI website builder pushed freemium users to pay before they could get a working (debugged) build.

Tinder focused on core engagement loops and retention first, and only turned on serious monetization in years four to five, at 30-40M monthly actives. The guest contrasts this with today's apps that monetize in the first session and can mistake hard-paywall revenue from young cohorts for product-market fit.

In 2016 built a dedicated revenue team inside product: the guest plus three iOS and three Android engineers, running a roadmap of small/medium/large experiments with revenue features treated as their own product line. Grew to 40+ engineers. Downside at public-company scale: finance-driven forecasting pushed the team into 'Excel culture' instead of testing ideas.

Flighty moved from a hard paywall toward a hybrid: the first flight is fully free with all pro features, then some premium features lock after it. Host suggests the pattern for high-cost apps (e.g. one free deep research per month).

An AI website builder could not afford to let freemium users debug their initial builds, so users who prompted a buggy site were pushed into a subscription before seeing a working result.

Supabase, a Chapter One pre-seed investment, ships a new feature every day and leaned into AI website builders.