Although information systems were initially conceived to assist in mathematical calculations, over time their use became more widespread in the storage and processing of information, and for some years now the main work of data scientists has been to analyze and discover hidden information within this data that companies have at their disposal.
We know that the client portfolio is one of the most important assets for an insurance company, and the main objectives of companies with respect to this are: the attraction of new clients and the loyalty/retention of current clients. While recruitment activities aim to increase prospects and potential customers, loyalty focuses its strategy on retaining them, and to this end establish communication channels to avoid possible leaks.
But before we can develop strategies to reduce the rate of customer churn, we need to be able to identify the users with the greatest tendency to churn, and to do this it is important to know how the customer has interacted with the company in order to understand the causes of their churn.
On the other hand, another of the main objectives of insurance companies is focused on customer satisfaction. This is where companies face another challenge, which is to change the consumption habits of their customers and with them, to increase the communication channels that users use to relate to their insurance company.
The digital transformation and customer habits
The digital transformation opens up a communication channel between customers and the company, and in this new channel the customer expects to be treated well. The close and direct treatment with customers that was formerly maintained through "corner stores" to give an example, can be maintained and recovered through digital mechanisms.
The digital transformation allows us to recover the essence of knowing the customer and his needs.
In many cases insurance companies can no longer compete on price, but instead can assess their customers' risk based on their actual behaviour. In addition, insurers must increasingly be able to focus on providing customized, flexible, value-added service products that involve working with customers proactively to avoid or reduce losses and manage risk.
Do you make use of all the data currently stored in your organization?
Within the data that a company collects from its customers, it is important to define three main categories:
- Structured data: this category includes personal data, which is normally collected by the company as a result of an economic transaction, contracting a service or in the event that the client participates in some action aimed at attracting leads.
- Unstructured data: this group includes data obtained, for example, from user interactions on social networks, logs of the systems owned by the company and recorded in order to solve technical problems.
- Semi-structured data: this is data that has a defined part and a non-defined part, a case of this type of data is the contents in XML format.
In addition, all this data can come from various sources such as:
- Websites and Social Media: the information generated when surfing a website, by the interaction of users in social networks, etc.
- Those generated by the people who interact directly with the companies: they can be called in a Call Center, E-mails and contact forms, among others.
- Transactions performed within the companies' systems: such as claims, receipts and billing.
All this data collected, in many cases is used for internal issues such as troubleshooting their systems or for verification of the status of their services, and it is this data that can provide more value than it currently generates.
In addition, one of the advantages of Big Data technologies is that it allows the processing and analysis of large volumes of data, of different kinds. Some of this data is ignored by companies due to the difficulty of being analyzed.
Finally, insurance companies that handle large volumes of information can improve their overall performance, and some of these improvements are related to strengthening the relationship with their customers, implementing strategies to prevent leakage and the progress of their internal processes that currently do not have a positive influence on improving their relationship with consumers. Managing and analyzing a large volume of data with the aim of influencing their business processes or strategies can transform the business models of insurance companies, and for this it is necessary to find ways to use the information to improve these models.
