Why mass mail to a large random audience when you could mail to a relevant audience based on automated analysis of CRM data?
Postie, the direct mail platform, has unveiled a new CRM Optimization engine that uses machine learning to automate the analysis of brands’ CRM data to identify best audiences for direct mail campaigns. Early usage showed CRM Optimization-identified audiences three-times outperforming audiences pulled randomly from the CRM data.
Why we care. Direct mail? Really? Yes, really. Direct mail items are often seen by all members of the household and they are persistently observable until someone throws them away. In other words, they have potential advantages over digital ads. But direct mail can only be helped by some digitally-savvy, data-driven strategies happening in the background.
Postie is one of the relatively few vendors seeking to bring data to direct mail. Mailing the right audience is surely better than mass mailing a random audience. Of course, the brands that will benefit from machine learning analysis of their CRM data are brands with a lot of CRM data.
Additional capabilities. Postie’s CRM Optimization engine offers the following capabilities beyond identifying best audience segments:
- Personalized recommendations on products and offers to send to audience segments.
- Continuous learning from campaign performances to optimize ad spend.
- Insights into customer behavior4 and preferences based on analysis of years of transaction and mailing data.
The machine learning algorithm improves in accuracy over time, said Postie in a release, and is expected to improve engagement, especially with high and consistent spenders, and reduce churn.
The post Postie launches CRM Optimization for direct mail appeared first on MarTech.
About the author
Kim Davis is currently editor at large at MarTech. Born in London, but a New Yorker for almost three decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020. Shortly thereafter he joined Third Door Media as Editorial Director at MarTech.
Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.
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