Predict. BSI customer value with a secure view into the future

Together we make you more valuable to your customers – and your customers more valuable to you. In order to achieve this strategically, there are twelve BSI Customer Values, three of which are focused on better understanding end customer Lena: The values of understanding build your knowledge and even predict her needs. Nine further BSI customer values aim for genuine customer proximity and added value.

In this series, learn how the twelve BSI customer values help companies on the way to perfect customer relationships. We start with a value from the area of understanding: Predict. Nils Schiffer, Product Owner for Insurance at BSI Software, explains the specific added value that Predict creates for end customer Lena, how companies can benefit from it, and why this value is a key enabler for other customer values.

Predict is one of the most demanding customer values within the values of understanding. Essentially, it is about making informed predictions at the right time so that customers can be served in the best possible way.

With Predict, we support all roles that involve customer contact – in service, consulting or marketing. Whether preparing for an appointment, handling an incoming call or delivering hyper-personalized content: Good predictions help identify relevant next steps early on and orchestrate them effectively.

Customer values should always be understood as concrete added value with a high level of expertise that works in two directions: for end customer Lena as well as for the company. All use cases contribute to one goal – the perfect customer relationship. Predict acts as an enabler for other customer values, such as Tell, Propose, Help or Protect.

Lena benefits from Predict in many ways. If we recognize early on what she will need in the near future, we can support her proactively and at the right time – whether it is with suitable offers or with specific advice for everyday life. However, Predict not only helps with commercial interaction. It also enables practical services: for instance, a reminder that an ID card is about to expire or a warning to close the windows when a storm is approaching. Lena feels understood, supported and well cared for.

Particularly in the insurance business, Predict also plays a key role in protecting Lena. Changes in her life situation – such as building a house or having a baby – can be responded to at an early stage. This makes it possible to predict whether she might be at risk of being underinsured or whether the desired standard of living is secure in the long term.

When companies know that Lena will need support in the foreseeable future, they can be there for her even before she actively asks for it. From a company’s point of view, Predict means anticipating the behavior of the customers and their AI assistants at an early stage, acting in a context-sensitive manner and thinking ahead in a targeted way.

The operational benefits are clearly measurable. Service, marketing and sales costs are reduced because interactions are more focused – exactly where Lena’s attention is. At the same time, customer loyalty, referrals and satisfaction increase.

Predict also has a positive effect on the share of wallets – i.e., the proportion of a customer’s total spending potential that a company covers – and enables significantly more precise trigger marketing.

Particularly in the insurance business, customer contact is rare and often sensitive. Many customers do not actively contact the company for years. When interaction does occur – for example to report a claim – that moment is crucial. Predict ensures that the right next best offer is suggested at the right time. Without this support, valuable potential remains untapped.

A current example comes from the insurance sector: A large German insurance company is already increasing the Predict customer value in its lead management and lead routing. New customers are automatically assigned to the most suitable customer advisors in the agencies. 

Various parameters are taken into account in lead routing, such as geographical proximity, category or the agency’s current capacity. The aim is to find the best possible match between the individual and the agency to ensure high-quality advice.

In the future, additional parameters will be added, such as personal interests or hobbies. The result is a clear win-win situation: for Lena, for the agency and for the company.

With BSI Elements, it is already possible today to expand the Predict customer value in concrete terms. The technical modules can be downloaded and activated directly in the BSI Customer Suite – with fast time-to-market and even faster time-to-value.

The debriefing agent, for example, is already available. Imagine the following customer scenario: You were at Lena’s and on your way to the next appointment you tell your digital assistant what you learned. The debriefing agent automatically documents your voice memos, structures the most important findings and gives you specific ideas about what the next sensible step is. This allows you to continue working seamlessly as soon as are you back at your desk – and to present Lena with a tailor-made offer in no time at all.

We are currently seeing very high demand for the debriefing agent. Additional agents will play an even greater role in the further development of the BSI Customer Suite. These include the lead agent and preparation agent which, in future, will strengthen Predict in sales and service processes.