# How PropGPT increased proceeds per user by almost half with a simple price increase test

> How PropGPT increased proceeds per user by almost half with a simple price increase test

Source: https://superwall.com/case-studies/propgpt

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January 17, 2026 

#  How PropGPT increased proceeds per user by almost half with a simple price increase test 

PropGPT tested a 43% price increase and lifted proceeds per user by 47.5% with minimal conversion erosion.

![PropGPT app icon](https://superwall.com/_astro/icon.DsUesuDG_ZOrPiE.webp) 

PropGPT [ View on the App Store ](https://apps.apple.com/us/app/propgpt-ai-sports-picks/id6645884227?uo=4) 

TL;DR

 PropGPT ran a simple, high-stakes price point A/B test, raising its weekly subscription from $6.99 to $9.99 — a 43% increase. The variant cohort that saw the $9.99 price delivered a 47.5% increase in Proceeds Per User (PPU), with only minimal conversion rate erosion at the higher price. 

## Intro

 PropGPT is a sports betting assistant app, where users pay for valuable, data-driven insights on player props and game outcomes. In this competitive niche, maximizing the revenue captured from each user is crucial for profitability. 

 The PropGPT team wanted to validate a fundamental question: Would increasing the subscription boost revenue from each user in the long term? 

## The challenge

PropGPT needed to determine their price elasticity:

* **Revenue uncertainty.** The team suspected they were leaving money on the table with their current weekly rate, so wanted to test a higher price without risking their user base.
* **Hypothesis.** They believed their value was high enough that a 43% price increase wouldn't deter conversion, but would increase revenue from every new customer.
* **Risk mitigation.** Before deploying to their whole base, they needed an A/B testing environment to split traffic, test their hypothesis, and measure Proceeds Per User (PPU).

## The solution

PropGPT executed a simple, but high-stakes, price point A/B test:

* **Control cohort.** Saw the existing subscription price of $6.99\.
* **Variant cohort.** Saw the proposed new price of $9.99, with identical images and copy.

 They A/B tested two distinct cohorts of users simultaneously, allowing them to measure the financial impact of the higher price on conversion and subsequent revenue. 

## The results

 The experiment provided a definitive answer to the price elasticity question and a massive gain: 

* **PPU soared.** The variant cohort that saw the $9.99 price point delivered a 47.5% increase in PPU.
* **Hypothesis validated.** Conversion rate erosion at the higher price was minimal, showing the trade-off was more than worth it.
* **Value maximized.** By increasing price, PropGPT successfully captured the maximum possible value from their audience.

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