Insurance data analytics for cross sell using Pentaho

Description

Complete 360 view of Customer in a single click using advanced Data Mining features. Additional Information apart from the basic demographic information, such as Social Media information, is collected to maintain a Customer Database.

This information can be used to build relationship with the Customers. Customer Grouping with Advanced ML Algorithms for Cross-Sell and Up-Sell recommendation based on Statistical Predictions and Real-time Alerts for the currently subscribed products.

Challenge

• Data is distributed across multiple systems stored in different formats, no central repository of information that can be analyzed by business analyst, data scientist to access the data and make more informed decisions for the business and support decision-making.
• Monitor changes in buying patterns and behavior of the customers based on various demographics, geographies & psychographics profile and recommend suitable products to the existing customers.
• Identify the Target Products and prioritize the best products to cross-sell each client, and get this information front and center for your sales and customer service team.
• Determine the probability of cross-selling a product to the existing customer, predict the right time to pitch the products to existing customers based on inter-purchase time of similar customers.

Solution

• The solution provides customer insights for the insurance to locate Cross-Sell and Up-Sell opportunities. Customer segmentation by identifying the right customers based on various factors such as age, marital status, policy details, agent info, claims, mode of payment then determining the probability of cross-selling a product to policyholders using to cross-sell and up-sell models.
• The analytics platform enables you to get a single, unified view of the customer by quickly integrating data across a variety of systems and details which products or services being used, how their usage behavior has changed, whether the policy is up for renewal, having this data at every step along the customer journey will increase the chances of a cross-sell/upsell.
• Use Predictive Analytics to Provide New Product Recommendations, This knowledge is valuable for the product marketing team to create product and pricing bundles. Also, valuable to provide to customer support teams, so they can make real-time cross-sell or upsell suggestions based on each customer’s specific situation.

Benefits

• Data and analytics can help insurers identify whether a customer is a retention risk and the correct action to mitigate that risk. Effectively target customers, leverage existing policyholder data, and achieve the greatest benefit from cross-sell and up-sell efforts.
• The model recommends which Product or riders to sell to which existing customers, based on buying behavior of other customer in a similar cohesive group using algorithms and business rules.