Customer analytics empowers the insurer of the future
Integrating data analytics deeply into the sales journey is the key to survival for the modern insurance carrier.
We enable you to actively steer your business on a forward-looking individual customer level and act as a fully data-driven, customer-centric organization.
We develop a 360-degree view for each customer and with the bigger picture in mind…
- …to improve the top and bottom line by realizing each customer’s potential.
- …to assess and steer your portfolio according to the future value of each customer.
How Munich Re enables you to keep up with your peers
Taking the right decision for each individual customer at every interaction is a key lever for increasing growth and profitability. With Customer Analytics from Munich Re you can boost your analytics journey and see an immediate impact. Our goal is to work with you to develop a 360-degree view of your customers leading to optimal decisions along the whole customer lifecycle.
We act as a sparring partner to identify the best first steps and develop a roadmap for your journey towards becoming a data-driven and customer-centric organization at the appropriate pace.
The combination of your data with external data and the application of advanced analytics techniques allows us to come up with the important answers around all customer interactions. To discover who will be the most profitable customer in the future, we take into account loyalty, sales potential and risk.
On this basis, we create a Customer Value Score which predicts the net profit attributed to the entire expected relationship with a customer. We then accompany you every step of the way on your journey towards the ultimate goal of embedding a holistic view of your customers into your business decisions – no matter where your current data or data science capabilities stand.
Selected use cases
With our customer and product analytics, we answer questions like:
- How big is my potential portfolio cancellation risk?
- What drives my customers to cancel and which levers do I have to avoid for increased effectiveness?
- Who are the top 100 customers I should contact to pitch a promotion?
Selecting the best analytics approach, we predict the likelihood of a customer leaving your company’s services within the next weeks/months. This information can be combined with the overall value of the customer to define the next-best action with one objective in mind – keeping your most valuable customers that will drive your future profit.
Our approach and your benefit:
- Provide your customer team with all the relevant information needed to target your customers most effectively
- Help you reduce marketing efforts while increasing customer satisfaction
- Increase your success rate significantly, which will lead to increased revenues for all retained customers
We were able to immediately boost retention rates in the most attractive customer segments by 3-5% points after the first models were implemented into our operations. We will build on this basis and look forward to further improving and extending the work with Munich Re.
Our advanced cross- and upselling models identify and predict individual preferences based on the customer’s purchasing history. A second analytical model is then used to define the next-best action to target high-value and/or high-potential customers with the right product at the right time.
With this advanced analytics approach, we are able to identify:
- What products, if any, your customer is most willing to buy
- Which customers are most likely to buy another product
- How to convince customers to buy additional products
This customer-analytics method will provide your customer service team with all of the relevant information they need to create a strategic customer segmentation in order to coordinate their marketing activity with focused interventions. The result? Reduced marketing efforts and increased customer satisfaction. Plus, your conversion rate will see a significant increase leading to higher revenues.
Munich Re took over the task to implement analytical customer loyalty and cross-selling models from scratch based on our specific data situation and needs. This has accelerated our analytics journey by far more than one year.
Have you ever asked yourself?
- What revenue will a customer provide in the coming years?
- Who are my high-value and high-potential customers and how can I keep them happy?
- What is the best path to maximise my value for a single customer?
This is where our complex analytics technique really delivers. We answer these questions by creating a segmentation of your portfolio based on the Customer Lifetime Value (CLV). This value is a prediction of the net profit attributed to the entire relationship with a customer for multiple years.
With our detailed CLV prediction, you instantly gain a better understanding of your customer needs and therefore gain a more comprehensive customer view. The estimation of the net present value of your business also gives you a long-term picture on how to better manage and steer your portfolio and is relevant for all business areas within your company, ranging from product design, marketing and pricing to sales and claims.
Munich Re combined a variety of individual analytical models. For the first time, we were able to gain insights into a predictive view of each single customer as a whole with all of their products and characteristics and use it in multiple business areas of our company.
We understand that in order to have successfully organised distribution management, you need a solid data foundation and up-to-the-minute monitoring. Munich Re makes sure that all of your company’s relevant data are available, transformed and prepared in actionable visualisations.
Our dynamic, automated and cloud-based web service answers client questions like:
- Which distribution channels are most efficient and effective?
- What does the performance for each channel look like?
- How satisfied are my customers with the service via different channels?
- Data transformation and processing are taken care of to achieve best results
- Transparency regarding the performance and business coming through each distribution channel is increased
- Actionable insights are gained on customer acquisition visualised in a dynamic way and adjusted to your needs
Munich Re has relieved us of the strenuous and time-consuming work of data consolidation and processing, which enabled us to gain a holistic picture and derive first actions based on it.
By leveraging your company’s policy, sales and agent data, we create a strategic customer segmentation for the personalisation of campaigns, website design, policy definition and more. We label these clusters to increase the usability for your marketing department on the respective sales channels, e.g. millennials without cars or leisure seekers (highly risk averse).
This analytics approach will answer your questions on…
- Is there a way to differentiate customers and target them in groups?
- Are there customers more willing to pay than others? If so, who are they and how can they generate more revenues for us?
- Are there potential customers that could provide me with revenue if I were to offer them a slightly lower price?
How this helps you
Target-group optimisation enables your marketing department to approach the right customers at the right point in time and thus improves efficiency and reduces costs. It supports your strategic definition of the best marketing tactics and increases the surplus achievable by every single customer.
Within a few months after we delivered data to Munich Re and began with regular feedback loops, Munich Re supported us in integrating the first analytics results into our operational processes to start testing the impact.