Data talk By Pete Tessier, Host, TheInsurancePodcast.com
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uring a casual mid-day scroll through Twitter, I recently came across a thread that talked about the perils of a scalable business model. It was a fascinating look at the how the model was built to capture the largest per cent of customers who may not have strong feelings of loyalty towards that particular business or service. I feel it’s worth discussing this topic because, as the insurance distribution model changes due to new technology, ideas, and market segmentation, the threat vectors appear similar. It’s no secret that insurance intermediaries, such as brokers, have been under threat for some time from other financial service models. Many have wanted a piece of the brokers’ proverbial pie; but, thus far, broker distribution has held onto its share. Seemingly, however, change is here. Insurance is a data-driven business and, with more technology allowing brokers to better understand their customers, the insurance experience has far improved. While the backbone of insurance and actuarial science sets the rates, underlying value, and offerings of insurance products, brokers are now able to add far better analysis to their own businesses, especially when it comes to building customer experiences and measuring them. The same can be said for those looking to disrupt the industry. Often, brokers will deploy customer service surveys based on their particular customers’ recent or overall experiences. The questions can ask about products, services, knowledge, and the value of the broker and brokerage. When it comes to responses and where the customers fit, for a broker, we can measure them
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off the average and how they deviate. In a visual sense, the graph would look like a bell curve. When looking at it more specifically, a bell curve represents where a data set falls in relation to a standard deviation from the mean. Revisit that customer survey the broker undertook and think of responses to questions. They more than likely ranged from ‘strongly disagree’ to ‘strongly agree.’ Statisticians know that, with standard deviations from the mean, a bell curve shows where the most respondents lie.
Here, we can see 68 per cent fall within a certain range of the mean. Add in the next bands and it moves to 95.4 per cent. This is who a brokerage is likely catering to when it comes to customer contentment and engagement. This is the mass that neither strongly agrees or disagrees — they are the average customer and the one who can be most influenced by the broker or competition. It’s hard to satisfy customers who are not strongly engaged with their broker or the service. Are those customers with the broker for specific reasons such as a unique product or service that is hard to find elsewhere? Is the broker convenient due to geography? These customers are the