# Paywalls picked by demographic: +83% MRR in 30 days

- Outcome: Won
- Page type: Paywall (App)
- Elements: Paywall timing, Paywall design
- Date shared: 2026-02
- Test run by: [Flirt AI](https://liftarchive.com/practitioners/flirt-ai/)
- Commentary by: LiftArchive (our analysis, not theirs)
- Original source: https://superwall.com/case-studies/flirt-ai
- Page: https://liftarchive.com/test/flirt-ai-demographic-targeted-paywalls/

Flirt AI grew MRR 83% in 30 days after showing paywalls chosen by demographic data from onboarding, with trial-to-paid up 20%. The AI dating reply app ran three paywall variants at once and shipped product and pricing changes at the same time. The result was published as a Superwall case study.

## Result

**+83% MRR in 30 days; +20% trial-to-paid**

- MRR: +83% within 30 days.
- Trial-to-paid conversion: +20%.
- These figures cover the paywall test plus product and pricing changes together, so no single change can claim them.

## Control

The app's earlier paywall, shown to all users.

## Variant

Three paywall designs with different copy, imagery and CTAs, with the one shown picked by demographic data collected in onboarding. Product and pricing changes shipped alongside.

## Why it likely won (our reading)

- Copy and imagery aimed at the core audience may have made the value clearer to the people most likely to pay.
- Product and pricing changes likely added to the revenue gain on their own.
- Higher trial-to-paid suggests the new paywalls drew more committed trial users, not just more of them.

## Caveats

This was bundled: paywall targeting, design, product and pricing all changed, and the MRR figure covers 30 days of growth rather than a clean split. No sample size or significance was shared. Superwall sells the paywall and testing tool used here, and its published case studies can lean positive.

## How to run this test

- Hypothesis: If we use an onboarding answer to show each group a paywall with copy and imagery made for them, then trial-to-paid will rise because the offer will match what each group wants.
- Primary metric: Trial-to-paid conversion per segment
- Guardrail: Trial start rate
- Guardrail: Proceeds per user
- Guardrail: Refund rate
- Who should test it: Apps that already ask a demographic or goal question in onboarding and have a few clearly different user groups. It is less useful if your audience is uniform or traffic is too low to split three ways.

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Credit: Flirt AI ran this test and owns the result. Summary and commentary by LiftArchive (https://liftarchive.com/test/flirt-ai-demographic-targeted-paywalls/).
Usage: Free to use, quote and build on, with credit and a link: name the practitioner or organization that ran the test and link to its LiftArchive page. The results belong to the practitioners who ran and shared them; the summaries and commentary are LiftArchive's.