Banking customers today demand a more individualized approach to their personal finances. Demographics, psychographics and “big data” correlations are no longer sufficient to understand needs, build loyalty and drive revenue. Banks, credit unions, mortgage lenders and financial advisors each need to engage in “right-timed” conversations with their customers that are more prescriptive, relevant and contextual.
A top 10 US financial institution, with over $300-billion in assets, wanted to move beyond behavioral targeting towards truly customer-centric engagement and activation with more personalized products and content offerings. Their digital team sought to implement a scalable approach that focused on individual customer attitudes to present the right product to the right customer.
Leveraging our survey widget on a top 10 bank logout page, Discourse Analytics collected non-cognitive attitudinal data on more than 780,000 bank customers, totaling more than a 10% engagement rate. Nearly a third of customers responded to more than 40 questions.
Based on the attitudes, Discourse Analytics leveraged its platforms Machine Learning capabilities to recommend specific products to each of the bank’s customers. The product recommendations included everything from paperless statements to specific account types, and more than tripled the Lifetime Value of the targeted customers.
The digital marketing team identified five products to offer this group of customers on the basis of their attitudinal profiles:
- Credit Tracker to be offered to reactive customers who were uncomfortable with personal finance and preferred to be in control;
- Mobile Wallet to be offered to technologically savvy customers who felt self-sufficient in terms of managing their finances;
- Mobile App to be offered to technologically savvy customers who were proactive and felt comfortable;
- Personal Savings Account to be offered to those customers who felt financially comfortable and were reactive;
- Advisory Content developed by the Bank’s personal finance experts for delivery to those customers who harbored some concerns about finance and did not feel self-sufficient.
With a view towards understanding the effectiveness of mindset-based product offers, an A/B test was configured with one group receiving offers on the basis of traditional approach, and the other group receiving offers on the basis of attitudes developed through conversations. The results shown in the table below indicate a significantly higher response rate from attitude-based targeting.
|Credit Tracker||25%||Most people had credit tracker. The promotion activated the last group of obstinate holdouts|
|Mobile Wallet||54%||Significant lift in response primarily those that were tech savvy|
|Mobile App||65%||Same as Mobile Wallet|
|Savings Account||-10%||Learned that this was more of a function of how long they have been customers, and had less to do with mindsets|
|Financial Education||19%||The responses showed a way for the bank to win customer loyalty and be seen as a service organization|