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A Path to Insurance Distribution Leadership: New Channels and New Data for Innovative Outcomes

A Path to Insurance Distribution Leadership: New Channels and New Data for Innovative Outcomes

Creating New Paths in the Distribution Management Maze 

Distribution channels – what consumers use to shop for, buy, pay for and use insurance – may be the most tangible part of most consumers’ experiences with insurance.  While the details of the product are obviously important, once the policy is purchased, most people file it away and forget about it.  Many consumers couldn’t find their policies if you asked them.  And how many consumers do you think have actually read their policy?

In today’s digital world, it’s less about the product and more about how customers interact with insurance that will determine an insurer’s success.  Increasingly, consumers’ expectations are being set more by the Amazons, Apples and Googles of the world than by similar insurers. Insurance has the unfortunate distinction of dealing in a product that most consumers only own because they have to, not necessarily because they want to.  So, insurers start perceptively behind on the product side compared to Apple, Google and Amazon. People use/shop/buy from these places because they LOVE to, not because they must.  Besides their product issues, the experiences insurers deliver through their channels are also no match for digital retail giants. At least, not yet.

What can insurers do?

As insurers, we can copy pages from the Google playbook and get better at using data and analytics to improve our distribution channels – the experiences we deliver and their effectiveness and efficiency in business operations.  Majesco’s recent research report, A Path to Insurance Distribution Leadership: New Channels and New Data for Innovative Outcomes, provides some useful insights into both of these areas, drawing on the first-hand experiences of CIOs who shared their thoughts at a roundtable discussion this past June.

On the consumer side…

Insurers can use data and analytics to segment customers and develop the right products for their needs and, crucially, offer these products through the channel/channels that best meet the preferences and needs of each segment. Predictive models can be used to further the precision with which to target prospects and customers for new purchases, cross-selling or increasing the stickiness of relationships for improved retention. By tracking customers’ paths across channels and collecting the data they’ve provided and consumed, insurers can ensure they have a seamless, connected experience, no matter what path they take.

On the insurer side…

Insurers have a wealth of data!  They just need to use it like Google!  Insurers have details on sales, retention, costs and profitability that they can track down to the channel and individual producer level. While most companies have always used this data to track performance, they can go even further and get additional insights on their producers by applying the same techniques we just discussed for customer data – namely segmentation and predictive modeling. Segmentation allows insurers to more efficiently apply training/development resources and match producers to markets/customer segments that best fit their potential. Predictive models can be used throughout the producer lifecycle to forecast performance and future success of individual producers as well as to anticipate future commission and incentive costs.  Analytics can also be used to steer prospects and customers to the sales and service channels that optimize business outcomes like new business, retention or lifetime value.

While the benefits of using data and analytics in insurance distribution are obvious and compelling, it is easier said than done. There are at least three components that must be solidly in place in order for any effort to have a chance to succeed.  Companies should first identify their top priorities and opportunity areas and use these to define an overall data and analytics strategy. After the strategy is secured, the focus can turn to the acquisition of internal and external data that will be needed to fuel the analytics and modeling identified in the strategy. A distribution management system can be a key enabler here, by providing rich, granular data on channel and producer performance. At the same time, a sound data governance strategy must be put in place to ensure the quality, integrity and comprehensiveness of the data.

A final important consideration is how the analytics will be operationalized. Again, a distribution management system can play a key role here by being configured to gather and track the needed data and execute business rules created through analytics and models built by using the data.

The insurance industry may currently lag behind the Apples, Googles and Amazons of the world in both product engagement and distribution experience and effectiveness. Insurance, however, has an enviable amount of data, talent and technology at its disposal. Leading companies in our industry are leveraging these assets and may very likely be the next ones pointed to with admiration by consumers and other industries for their excellence in distribution.

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