Merkle worked with a banking client to develop a multi-product consumer loan engine. Prior to working with us, the client managed a variety of creative packages that were developed independently. There were four key challenges we worked with the bank to solve:
- Targeting and Offer Arbitration: Customer relevance was a concern, in that a household could receive multiple offers that were competing for mindshare within a short period of time.
- Brand Consistency: With creative packages being developed for various lines of business, the direct mail packages lacked consistency from a brand voice perspective.
- Media Integration: The bank wanted to improve conversion rates as customers moved through the purchasing funnel by offering a consistent dialogue across media and channel.
- Production Efficiencies and Flexibility: The bank wanted to improve production efficiencies (and be able to vary quantities rapidly across product lines) to support rapid cycle testing.
To help in arbitrating the correct product offer and contact cadence for each customer, the bank worked in partnership with Merkle’s banking and finance strategists to deploy product-level response models to predict booking and balance.
An arbitration engine was then built by the bank to prioritize and arbitrate between primary and secondary products to offer. A palette of three key product offers were developed: home equity lines of credit (HELOC), auto refinance, and unsecured lines of credit.
Key Program Components:
- Targeting: Both prescreen data and invitation-to-apply data were used. The combination of data allowed for the greatest targeting efficiency for consumer need and creative messaging while maintaining high campaign approval rates and ROI.
- Modeling: The bank developed customized product-level models drawing on known customer information, promotional history, consumer credit data, and mortgage and property data.
- Arbitration Engine: We deployed a business-rules approach to arbitrate offers by product. The intention was to get the right combination of offers to the right customer at the right time. The engine used a combination of general business rules, value (profit/revenue proxy), and propensity (model scores).
- Messaging Strategy: Using the appended data, we segmented customers and tailored messaging and offers within each product
- Creative: Creative templates were developed for banners, direct mail, and email communications. Some of the tests around creative included:
- Retargeting and prospecting display ads – A/B testing gives quick insight to performance
- Button testing of language and color resulted in using the brand’s blue color and “learn more”
- Data-driven image optimization has shown to improve performance
- Template based is a cost effective approach allowing us to test offers, language, charts, response channels, and message structures
- Vertically stacked to render across mobile devices
- Subject and pre-header testing of a variety of massages
- Always rely on strong direct response tactics – bullet proof buttons and large text and messaging hierarchy
Through the development of product-level response models and value-based arbitration, we were able to effectively optimize what product and offer to serve to households, substantially improving marketing ROI. In addition, the customized offer messaging improved response and conversion substantially in historically low-utilized, low response segments.
As direct mail programs mature, we will leverage the wealth of appended data to create segmentation, allowing us to improve future targeting by tailoring marketing communication and applying it to the bank’s prospect universe. This will allow us to acquire similar households that will be highly profitable, establish foundational relationships with the bank, and create opportunities for future cross-sell programs.