Proactive and pinpoint: successfully addressing insurance customers thanks to AI

By using AI, insurers can optimize their marketing processes and achieve a higher hit rate when targeting customers appropriately.

Author: Florian Müller

Cost pressure in the Swiss market for traditional basic insurance remains high. For insurers, the up-selling and cross-selling of supplementary insurance is therefore becoming increasingly important. To be successful, insurers must understand their customers' needs and proactively address them with suitable offers. However, the decision-making processes for an optimal marketing approach are complex, as they have to take into account a variety of criteria, including those related to risk management.

By using AI, insurers can optimize their marketing processes and achieve a higher hit rate when addressing customers appropriately. The goal is to show customers what they are really interested in. The benefits are a better customer experience, as well as higher cost efficiency of marketing activities. The following paragraphs describe how this can be achieved.

Key decision points in campaign marketing

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Figure 1: 3 decision points in campaign marketing more efficient thanks to AI

1. AI-assisted target group selection

A key challenge in campaign marketing is to select customers for marketing activities. If insurers are too careless in their selection process, there is a risk that customers will be offered products that are not approved by the subsequent underwriting process and therefore cannot be concluded. Such negative effects on the customer experience must be avoided at all costs. Conversely, however, too strict a selection can unnecessarily limit the market potential. Predictive models can take these aspects into account and determine an optimal target group.

2. Product affinity prediction

Another challenge is selecting products that the customer is actually interested in. AI can also support insurers in this decision. For example, the affinity of customers for certain products can be predicted on the basis of purchase decisions. Amazon or Netflix, which made such recommender models popular in the first place, serve as models here. For example, customers can be selected on the basis of their affinity for target groups, which are then specifically contacted as part of a larger campaign. Or insurers automate the process and set threshold values for affinities, which then trigger individual marketing activities for individual customers.

3. Personalized communication

The success of marketing activities depends to a large extent on whether insurers succeed in tailoring communications to the individual interests of their customers. Relevant aspects of communication include the topic addressed, the style of communication, and the channel and timing of communication.

With AI, insurers can identify patterns in past marketing activities that provide insight into the best way to approach different customers. An AI model can learn these patterns and generate suggestions for communication design, such as a combination of optimal communication channel and proper timing of approach. In this way, insurers can personalize communications for each customer individually. At the same time, they have the opportunity to gain new insights and better understand their own customers. The prerequisite for this is that the history of marketing activities is documented and insurers measure the success of the activities.

Conclusion

AI offers insurers opportunities at various points to increase the efficiency of their marketing processes. The three decision points in marketing (target group selection, product affinity, and personalized communication) outlined in this blog entry offer insurers promising and proven approache

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