Marketing
Predictive Upselling
Build better predictive upselling models based on customer behavior by unlocking previously inaccessible datasets for analysis.
Challenge
- Semi-structured customer data across dozens of data stores.
- Deploying a data analyst to each location too costly while centralizing risks regulatory concerns and losing consumer insights in context.
- Existing ML models poorly account for small but impactful variances in upgrade demand after different product and service releases.
Solution
- Devron works with data science teams to train sophisticated algorithms on decentralized data.
- Data Science teams gain additional insights on customer behavior while keeping PII safe at the source.
- Real-time insights allow Sales to adjust upgrade offers 67% faster to predict and respond to new release demand.
Outcomes
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Greater Customer Wallet Share
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Increased Revenue
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More Data for Analysis
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Reduced Time to Insight
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View Additional Use Cases
Marketing
Expanding Banking Loan Base
Banks desire to expand their customer loan base to drive revenue, manage risk, expand services per customer, and maintain competitiveness. As a result, banks are turning to AI to better segment their customers for new and cross-selling opportunities and to improve their overall customer acquisition process.
