Customer retention through newsletter personalisation

Increase the acceptance and conversion rates of newsletter campaigns and transactional mailings through highly personalised recommendations and content designed to match reader preferences.

Customer mailings are only successful with relevant content which offers real added value. Newsletters with convincing content will reduce cancellation rates, increase subscriptions and improve purchase conversion rates.

The first step in doing this is to divide recipients into interest groups and to  personalize the approach to each individual recipient. Today an individual approach means more than to personalize the address. Rather, it means to offer content with a high individual relevance.

The starting point for personalising mailings is an analysis of the click, shopping basket and purchasing histories of each addressee. This information can come from any CRM system or from an on-line shop.

The prudsys RDE | Newsletter module uses this data and data from its customer behavior knowledge base to automatically prepare product and content recommendations for the recipients. Since recommendations are personalised they have the highest relevance for each recipient and therefore increase the long-term conversion rate of your mailings. In cases where no profile or transaction data is available for an individual recipient, the system switches to the top seller mode and then optimises and fine tunes recommendations as time goes on.

For this, the module RDE | Newsletter records customer reactions to the recommendations in newsletters and passes the recommendation rules in real-time to the customer behavior database. If little or no historical data is available, newsletter offers will be optimised continuously so that the reaction of each recipient to a recommendation will influence the content and recommendations of the next mailing opened.

If prudsys RDE is running in an online shop too, the recommendations will always be based current customer behavior patterns. Any changes in purchasing behavior (caused for example by changes in the weather) will automatically trigger updating of the underlying recommendation rules. If the recipient is already logged on to the online shop, the system will take into account the current interests of the customer and make sure that recommendations are not made for articles which have already been ordered.

The Newsletter Personalisation function can be used with any mailing system for HTML newsletters. Personalised offers made in newsletters can also be included subsequently in transaction mailings (e.g. invoices, order confirmations and mailings by ordinary post).

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