Playbook
Paywall A/B Testing & Experimentation
Build paywall variants, split traffic, and read results the same day with Superwall — no app release and no engineering queue required.
A/B test your paywalls with no app release required. Build variants, split traffic, and read results the same day — without shipping a new build or waiting on the engineering queue. Most teams test paywalls at the speed of their release cycle. Superwall moves paywall experiments into the dashboard so growth teams can build, split, and learn the same day.
Why it matters
Paywall A/B testing and experimentation is the number-one thing subscription teams ask Superwall for. The reason is simple: when paywalls are hard-coded into the app, every copy change, price test, and layout idea is gated behind a build, a review, and a staged rollout. Learning slows to a crawl, and the experiments that would compound into real revenue never get run.
Superwall removes the release tax. Paywalls live in campaigns, not in your binary, so the people who own conversion can run experiments directly — test anything, fast, with no app release and no engineering queue.
What you can do with Superwall
Split-test two or more paywalls against each other. In a campaign experiment, add two or more paywalls to an audience and assign each one a presentation percentage so real traffic is divided across your variants.
Run holdouts to test whether a paywall helps at all. Set your paywall percentages below 100% to create a holdout that shows no paywall to a control group, so you can measure whether a paywall increases or decreases transactions.
Target the exact users you want to test on. Audiences let you filter by subscription status, app version, placement parameters, event frequency, or a 0–99 user seed for clean A/B splits.
Build every variant without code. The paywall editor is no-code, with templates, advanced UX components, and AI-assisted building — so a growth team can produce the next variant without engineering.
Compare variants on the metrics that matter. The experiment results view breaks results into Paywalls, Placements, and Graphs, defaulting to Proceeds Per User, with confidence intervals to gauge how each variant performs against the others.
How it works
Register placements once. Engineering registers placements in the SDK for the moments where a paywall could appear. After that, everything is configured remotely.
Pick an audience. Create or select an audience to decide which users are eligible for the experiment. Superwall evaluates audiences top-to-bottom until a user matches.
Add your variants and split traffic. In the Paywalls tab, add two or more paywalls and assign each a presentation percentage. Percentages total 100% unless you intentionally go under to create a holdout. Assignments are sticky per user, so the test stays clean.
Read the results. Use the results view to compare proceeds per user, trial starts, subscription starts, and conversion rate. Hover any metric to see confidence intervals.
Iterate without a release. Drop a losing variant by setting it to 0%, refresh assignments after changing percentages, build the next variant in the editor, and re-run — no app build required.
Proof from customers
Across Superwall's customer-research calls, paywall A/B testing and experimentation is the most-cited demand signal by a wide margin — the thing teams bring up first when they describe why they switch. The recurring story: their paywall hit a ceiling, and shipping the next test through an app release was too slow to learn anything.
What customers consistently say they want is the ability to test paywall copy, design, offers, and pricing quickly, see all the variants at a glance, and iterate without an engineering queue. Superwall's campaigns, holdouts, and results view are built directly around that job.
Use cases
Copy and layout tests — pit two paywall designs against each other and ship the higher-converting one.
Offer and pricing tests — compare trials, intro offers, and price points as separate variants in the same experiment.
Holdout / value-of-paywall tests — prove whether a paywall lifts or hurts transactions before rolling it out.
Segmented experiments — run different tests for new vs. returning users, by app version, or by user seed.
Continuous iteration — keep a paywall improving over time instead of resetting it once per release.
Get started
Start your first experiment with the Starting an Experiment guide, learn the building blocks in the Campaigns overview, or create an account at superwall.com.