Customer data management for insurance companies

Reliable customer data accelerates the go-to-market of digital offerings.


Customers are demanding digital closing paths that lead quickly and easily to the conclusion of an insurance policy. Insurtechs are living the data-based customer journey, while established insurers are challenged. The quality of customer data at digital touchpoints is becoming increasingly important.
 

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Today, insurance companies operate in a digitized world in which customers demand the highest standards, for example in terms of personalization and service, but also the ability to communicate at any time via any channel and any device on any matter. In this respect, the role of industry companies is changing from pure insurers to true life companions. They must be able to recognize life moments at an early stage and provide 'predictive' support, so to speak.

But digitization also means that personal contact is declining and shifting to the virtual world. In this respect, the data of customers and prospects at digital touchpoints is of enormous importance. After all, only this data is available to understand customers in terms of their needs, desires, and expectations. That's why the data must be quality-checked and reliable. Otherwise, just about everything that can go wrong on the basis of data will go wrong, be it an unsuccessful approach or incorrect advice and billing.

"Digitizing the insurance business means using customer data intelligently to implement a data-driven customer journey through knowledge."

How data quality supports:
 

  • Efficient customer processes:
    If customer and prospect data is well-maintained, reliable, and fit for purpose, the processes that handle it will also work.
  • Customer Insights:
    Having lots of data is all well and good. But you have to know how to use it. Only when data is well maintained does it reveal its knowledge. From this comes information that can be used for business, such as upselling and cross-selling.
  • Relationship management:
    High data quality enables personalized offers and services. By being able to identify needs, preferences, habits and life phases, it is possible to act individually and carefully.
  • Efficiency booster:
    Internal processes and workflows can be improved and automated. Data analyses help to identify and eliminate bottlenecks and inefficient processes. Automation also helps to reduce costs.
  • Holistic view:
    If data can be consolidated and made available centrally, data silos can be broken up and, above all, redundancies eliminated. On the basis of multiple Golden Records, if necessary, various aggregations lead to expanded views and options for action.

Insurtechs are ahead of established insurance companies, especially when it comes to digitalization. This is because their business model is based on digital processes from the outset. In this respect, for example, digital sales channels without media discontinuity, embedded in a lean website and using analytical techniques, are part of the basic equipment. It is well known that data is crucial. But not only that. What is also needed is the corresponding competence to deal with the data and to use the knowledge it contains in a useful and value-adding way.

"The consolidation of the data of our group partners and the creation of a group partner ID were decisive target factors for us in the project. Here, we could fully rely on the expertise of Uniserv."

Sven von Dirke, Project Management, W&W


           Read success story  

"The consolidation of the data of our group partners and the creation of a group partner ID were decisive target factors for us in the project. Here, we could fully rely on the expertise of Uniserv."

Sven von Dirke, Project Management, W&W


           Read success story