Postie launches CRM Optimization for direct mail
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.
Dig deeper: What is customer relationship management (CRM) and how does it support marketing?
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