Challenges

1 / Effective segmentation. Accurately segmenting clients to pinpoint the most profitable groups in the tech industry.

2 / Customer retention. Developing strategies to minimize client turnover and strengthen retention.

3 / Data analysis. Analyzing extensive customer data to discern preferences and trends in tech solutions.

4 / Predictive modeling. Constructing models to forecast future client value and tech needs based on current data.

Goals

1/ Identify the most profitable customer segments to tailor technology solutions and marketing strategies more effectively

2/ Develop models reflecting the common attributes of significant clients for future targeting

Results

By segmenting customer transaction data based on brand occurrences, the bank achieved a 15% increase in customer engagement.

The creation of heat maps to track payment card usage geographically led to a 20% improvement in targeted marketing efforts.

The launch of co-branded bank cards, informed by popular brands in transaction data, resulted in a 25% increase in new card sign-ups and a 30% rise in transaction volumes with these cards.

Selling depersonalized transaction data to retailers opened a new revenue stream, enhancing the bank’s profitability by 5%.