How a Bank Achieved the Same Marketing Results with a 98% Smaller Audience

As third-party cookies disappear and acquisition costs continue to rise, financial institutions are facing a new reality: broad digital targeting no longer guarantees efficient growth.

A national bank confronted this challenge while trying to grow credit card applications among non-banked consumers. Traditional digital targeting methods could deliver scale, but lacked the precision needed to predict which consumers were most likely to qualify for and actively use a credit card product.

The opportunity was not simply to reach more people. It was to reach the right people.

Challenge

The bank needed to improve customer acquisition efficiency in a rapidly changing advertising environment shaped by cookie deprecation, tightening privacy regulation, and rising media costs.

Existing targeting approaches created several limitations:

• Large audience pools with low qualification rates
• Increasing wasted media spend
• Limited visibility into real-world consumer financial behavior
• Reduced effectiveness of third-party audience targeting

At the same time, strict privacy and compliance requirements limited how customer data could be used across organizations.

The bank needed a privacy-compliant way to improve targeting precision and customer acquisition performance using first-party data.

Insight

The breakthrough came from combining banking intelligence with real-world consumer spending behavior.

Working through Omnisient’s privacy-preserving data collaboration platform, the bank collaborated securely with a leading grocery retailer to analyze anonymized customer overlap and surface audiences with a high propensity for credit card usage.

Rather than targeting broad demographic audiences, the collaboration focused on analyzing behavioral similarities between the bank’s existing credit card customers and the retailer’s loyalty members.

Strategy

The strategy centered on replacing broad-reach targeting with predictive precision targeting.

Instead of marketing credit cards to millions of consumers indiscriminately, the bank focused media investment on anonymized audiences demonstrating characteristics associated with high-value prospective cardholders.

This enabled the bank to:

• Reach non-banked consumers matching ideal customer profiles
• Reduce audience wastage
• Improve media efficiency
• Maintain compliance with privacy regulations

The retailer also benefited by increasing the value of its retail media network and loyalty ecosystem through privacy-safe audience collaboration.

Execution

Using Omnisient’s Data Clean Room environment, the bank and retailer securely combined anonymized customer intelligence without exposing or exchanging raw consumer data.

Omnisient’s platform analyzed common patterns between existing credit card users and retailer loyalty members, then applied machine learning models to create a lookalike audience of prospective customers who were not yet banked by the institution.

The anonymized audience was activated across the retailer’s retail media network, including social media and Google advertising campaigns, promoting the bank’s credit card offering.

The retailer’s retail media network was then used to measure campaign effectiveness and attribute applications back to media activity.

Results

The campaign demonstrated the performance potential of privacy-safe first-party data collaboration in a cookieless environment:

• 74% reduction in cost per lead
• 728% return on investment
• Significant improvement in audience precision and acquisition efficiency
• Reduced reliance on third-party cookie targeting

Impact

The collaboration showed how first-party retail and banking data can be used together to create a more predictable and efficient customer acquisition engine.

For the bank, the campaign unlocked access to new prospective customers while lowering acquisition costs.

For the retailer, the initiative increased the commercial value of its loyalty and media network assets.

For consumers, it enabled more relevant financial product offers delivered in a privacy-compliant way.

More broadly, the campaign demonstrated how financial institutions can adapt to a cookieless world by shifting from broad audience targeting toward privacy-safe, behavior-based predictive marketing powered by first-party data collaboration.