Mobile Gaming Use Cases/MonetizationProduct Manager

Do product recommendations on the web shop checkout page increase AOV by more than 12%, and which recommendation algorithm (collaborative filtering vs content-based) performs better?

Evaluate cross-sell recommendation effectiveness on the web shop to optimize the recommendation model and placement strategy

Metrics & KPIs

AOV liftrecommendation click-through raterecommendation conversion ratealgorithm comparison

Required Data

Recommendation display eventsadd-to-cart from recommendationsAOV dataalgorithm variant tagsA/B test data

Data Sources

MonetizationA/B TestingData Warehouse

Works with tools like

RevenueCatStripeGoogle Play ConsoleApp Store ConnectOptimizelyFirebase Remote ConfigLaunchDarklySplit.ioSnowflakeBigQueryRedshiftDatabricksClickHouse

How Bruin answers this

Bruin

Bruin AI Data Analyst

Do product recommendations on the web shop checkout page increase AOV by more than 12%, and which recommendation algorithm (collaborative filtering vs content-based) performs better?

Bruin connects to your Monetization, A/B Testing, Data Warehouse and runs the analysis automatically.

It tracks AOV lift, recommendation click-through rate, recommendation conversion rate and delivers the answer in seconds, in Slack, Discord, Teams, Google Chat, WhatsApp, Telegram, email, or your browser.

Bruin for mobile gaming

Use cases across every team in your studio, from monetisation to LiveOps, product to engineering. One AI that speaks your data.

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