Case Study
Using 1st Party Data to Drive Credit Card Sales in a Cookieless World
Cross-Industry Collaboration: Retail Media Network and Banking
Objective
To enable Africa’s largest bank to target non-banked customers with a high propensity for credit card usage using Africa’s largest retailer, retail media network and drive mutual growth through privacy-preserving data collaboration.
Overview
As third-party cookies are phased out and data privacy laws tighten, financial institutions face increasing challenges in targeting new customers while maintaining compliance.
Africa’s largest bank, faced this challenge when marketing credit cards to new customers. By partnering with the largest retailer in Africa, and leveraging Omnisient’s privacy-preserving data collaboration platform, they were able to overcome the challenges posed by the phasing out of the 3rd party cookie and unlock a new pool of potential credit card users while ensuring regulatory compliance.
Through Omnisient’s platform, the bank and the retailer performed a data overlap analysis to identify potential credit card applicants within the retailer’s extensive customer base of 30.5 million loyal shoppers representing 80% of the South African population.
By securely combining data from both companies, Omnisient enabled a privacy-preserving collaboration that allowed the bank to efficiently target customers who were not already banked.
Using Omnisient’s machine learning capabilities, a lookalike audience was created based on the retailer’s loyalty members who shared similarities with the bank’s existing credit card holders. This anonymized audience was then targeted through digital channels to encourage credit card applications.
- Retailer dataset: Customer data from the retailer’s rewards members who showed a low credit risk and high propensity for credit card use based on their spending behavior, in-house affluence indicator, and deeds office data.
- Bank dataset: Credit card holders and their creditworthiness profiles.
When the anonymized datasets were overlapped, Omnisient helped the bank view the number of non-banked customers in the retailer’s loyalty database who fit their ideal credit card customer profile, demonstrating the size of the opportunity.
These insights allowed both the retailer and the bank to realize mutual benefits from the partnership, with the retailer’s customers gaining access to financial services and the bank acquiring new customers.
Execution
By encrypting and securely combining customer data in Omnisient’s Data Clean Room, commonalities were identified between the bank’s credit card users and the retailer’s customers. Omnisient then applied machine learning to create a lookalike audience of the retailer’s customers who were not yet customers of the bank but demonstrated similar behaviors to existing cardholders.
The lookalike audience was assigned a new encrypted key to ensure privacy. This anonymized audience was then targeted via social media and Google ads with a focused campaign promoting the benefits of the bank’s credit cards, such as ease of application, speed, and security.
The bank leveraged the retailer’s media network to measure the effectiveness of the campaign and attribute credit card applications directly to the paid media efforts.
Results Achieved
74% reduction in cost per lead
By precisely targeting the right audience, the bank dramatically reduced acquisition costs.
728% return on investment (ROI)
The privacy-preserving data collaboration enabled highly efficient customer acquisition, far exceeding the bank’s expectations.
Impact
For the bank
This innovative collaboration resulted in a large pool of new credit card applicants at a lower cost, enabling the bank to extend its reach to non-banked customers in a secure, privacy-compliant way.
For the retailer
By providing customer insights that the bank used to offer credit services, the retailer reinforced the value of its loyalty program, while helping its customers access financial products.
The consumers
Customers benefited from access to a trusted credit card provider that met their needs in a secure and convenient manner.
This case study demonstrates how Omnisient’s privacy-preserving platform can help financial institutions overcome the challenges of third-party cookie deprecation and strict data privacy laws, while still driving business growth through first-party data collaboration.
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