American Automobile Association (AAA) Life wanted to develop an integrated, closed-loop, cross-channel marketing platform to scale up its prospect acquisition, cross-sell, and customer journey programs. Campaigns were taking longer and it required a lot of effort to segment and target customers.
38M+
customers/members integrated and 146 million prospects/affiliates
2.5B
individual model scores across 7 segments in the marketing database
90%
reduction in database update timeline
customers/members integrated and 146 million prospects/affiliates
individual model scores across 7 segments in the marketing database
reduction in database update timeline
The brand’s ability to measure and report on campaign performance was also limited by a lack of Salesforce SMEs and lacked consistent insights to improve performance, thus resulting in a delay to bring campaigns to market (usually 30+ days).
Merkle developed an integrated customer/prospect database in Amazon Web Services (AWS) using Amazon Redshift. In this case, summaries were built for club membership, product ownership, product eligibility, declinations, promotions, and customers (owned and insured). The team also rebuilt seven-eight integrated models/segments for targeting to run on the new data platform which resulted in the continuation of all the client’s acquisition campaigns. The customer data integration enabled by Merkle hosted connected recognition solution.
A new reporting solution was developed using Tableau® on AWS to drive attribution, reports, and insights for performance measurement. Merkle and AAA Life worked together to understand the clients’ needs and design a custom solution which included crafting a solution that has “dynamic engine” or “campaign execution process” (or set of processes) that utilizes meta data to execute complex DM campaigns with dynamic SQL.
The implementation of AWS hosted solution using AWS Lambda reusable created micro-services: Interaction, real time Merkury Identity™ , real time Adobe® Marketing Cloud, Amazon DynamoDB logging and Amazon Redshift loader (using Amazon Kinesis for performance).
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