Case Study: Ecommerce Company achieves 25% monthly revenue growth and optimized ad spend with Ezappsolution

Ecommerce Company - Customer Case Study

Ecommerce Company, a U.S.-based online retailer, struggled with basic CRM campaigns using Salesforce and other third-party tools, facing high customer churn, low engagement, and limited customer lifetime value (LTV) and app downloads. To address these issues, they adopted Ezappsolution's AI Campaign Management to improve app downloads and maximize business revenue.

Ezappsolution implemented an AI-driven campaign and forecasting platform with a serverless data lake and ETL on AWS, optimizing omni-channel spend across Google PPC, Facebook and ad networks and allocating budget automatically. The solution used deep learning for chat discovery, personalized recommendations and multiple ML models (reinforcement learning for ad-channel optimization, Markov chaining for spend allocation, random forest to reduce churn, logistic regression to boost app downloads, and linear regression for LTV and 3-month sales forecasts). Results included 2 of 10 recommended products being purchased, a 45% lift in revenue from recommendations, a 25% increase in overall monthly revenue, reduced churn, optimized ad spend and higher subscription and app-download rates.