The Challenge of the Optimal Newsletter Frequency

Sending out more newsletters doesn’t save sales targets. While category managers, CEOs, and CROs seem to insist on using newsletters to make up for spontaneous revenue problems, CRM managers are worried about the impact of high newsletter frequency. In fact, over-contacting can significantly harm open and click rates, unsubscribes, and reputation damage.

 

Goal and Approach of Predictive CRM for Newsletter Optimization

1

Reduced Newsletter Frequency

The goal is to identify those customers with an increased risk of unsubscription and to contact them with less frequency

2

Predictive Model

CrossEngage’s No-Code Predictive Model Builder can be used to create an unsubscription score for early identification of at-risk newsletter contacts

Implementation and Possible Test Design

In particular, the precise identification and reactivation of customers at risk of churn and the targeting of customers with a high affinity for advertising created an astonishing uplift.

Implementing Test Design

1. Predictive Model

CrossEngage’s No-Code Predictive Model Builder can be used to create a predictive model for the unsubscription use case without any programming knowledge. It evaluates customers in terms of their individual risk of unsubscribing from a newsletter.

 

2. Segmentation

Based on the scoring, the audience management function creates a high-risk unsubscription segment that is immediately available for campaigns and testing.

 

Find out all about the unsubscription use case and learn how an international e-commerce company managed to save an additional turnover of €725,400 by saving valuable newsletter subscribers.

Newsletter Use Case
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