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Improving purchase conversion from 8% to 12% in a gaming app

A gaming platform learns a highly contextual insight: a significant % of new users churn from the purchase (aka deposit money) screen as they do not know how to withdraw their money from the app.

July 14, 2022
Rahul Mallapur

A gaming app increased purchases aka daily transactions by 50% by sharing information with users in the purchase flow.

The key actionable insight

Many new users were dropping off on the purchase screen because they did not know the rules to withdraw money from the app.

🕹️ In real money gaming apps, users play gaming tournaments for money and stand a chance to win more money than they put into the game. These tournaments consist of games of skill such as fantasy sports and casual and tabletop games like Carrom. Two of the biggest Indian companies in this category include unicorns - Dream 11 and MPL.

Every real-money gaming app has differing deposit (money in) and withdrawal (money out) rules and is personalized to each user’s activities. For example, a user on signup will see a min withdrawal limit of ₹10, and on winning a game the withdrawal limit can jump to ₹20. (higher withdrawal limit pushes winners to put more money into the app and play higher stakes)

As apps are continuously changing (experimenting) these rules, users are skeptical of depositing money as their money might be stuck if the withdrawal limits are too high.

Quick background

ABC (company name withheld), a Series A funded startup with over 300k MAU, had a purchase conversion of 8%, i.e. of the 100 users who landed on the purchase screen, only 8 users made a purchase. This conversion is critical: having a direct impact on the revenue and business, and indirectly increasing engagement as more people in a tournament more the fun.

purchase purchase

The product team iterated on multiple fronts over weeks to increase the purchase conversion. Experiments like personalizing pack sizes based on games played, running discounts to time-box and push purchases, or highlighting the platform trust by showcasing user reviews created short-term and little improvements.

Discovering the insight

The first study contained two questions asking users if they intended to purchase and what could be improved. Answers to the first question filtered out the high intent users (4-5) and just exploring users (1-3).

The open-ended second question helps in hypothesis generation and often serves as a portal to learning the rational and emotional motivations of users. Almost 35% of the high intent users (defined based on answers to question 1) answered.

Other highlights included no support for Paytm (a wallet) payments, very high pack sizes, and needing Hindi translation support.

A second study was launched to quantitatively evaluate how many users faced similar issues. This survey contained multi-choice, with each insight being an option. Of the 1000 users who responded, 43% had dropped as withdrawal rules weren’t clear and 18% had dropped because of no Paytm support - which the team was already working on.


A withdrawal rules card - a card that concisely mentions the withdrawal rules placed at the bottom of the purchase screen.

Impact of the insight

The withdrawal rules increased the purchase conversion from 8% to 12%. A 50% increase in purchases was achieved with only a few hours of product and engineering teams!