Case Study
Optimizing customer targeting with AI
We helped a leading bank cut marketing costs by 43%, improve targeting accuracy, and generate 26,212 direct sales with AI-driven automation
The problem
Identifying an opportunity for smarter marketing
Driving sales with AI-powered predictions
Building a data-driven predictive engine
Our goal was clear: use AI-enabled process automation to improve how the bank matched customers with products, optimizing marketing spend while increasing sales and campaign performance.
Our solution
By analyzing historical data, automating customer profiling, and refining targeting accuracy, we helped the bank streamline marketing efforts and focus on high-value prospects.
AI-driven customer-product matching
We developed a predictive AI model that analyzed demographic, behavioral, and transaction data to identify which customers were most likely to engage with specific products. This shifted marketing from broad outreach to highly targeted campaigns.
Building a data-driven predictive engine
Our AI system processed key customer insights, including past transactions, purchase trends, and campaign responses. It uncovered trends invisible to human analysts, allowing the bank to focus its marketing spend on high-conversion opportunities.
Testing and refining for accuracy
We ran discovery experiments using multiple AI algorithms, refining the model until it achieved high accuracy in predicting customer-product matches. Once optimized, we deployed the solution into production and continuously improved it using live campaign data.
Results
Faster ID verification led to higher completion rates for banking and government applications
Improved customer experience by eliminating delays and manual document submissions
Enhanced security through end-to-end encryption and digital signatures
Before working with us, the bank’s traditional marketing methods resulted in low engagement and high costs. With AI-driven predictive modeling, they matched customers to products with higher precision, focusing only on the most likely buyers.
This approach cut campaign costs by 43% while still reaching the right audience. AI-powered automation drove 26,212 direct sales, significantly outperforming past campaigns.
By optimizing marketing spend and improving targeting, the bank achieved a 736% return on investment, proving that AI-driven automation delivers faster, more cost-effective growth.
This AI-powered system is now a key part of the bank’s marketing strategy, continuously learning and refining its approach to maximize future performance.