Customer Engagement in the Insurance Industry: An Unexpected Approach Delivers Unprecedented Results

This is a story about not giving a customer what they ask for…and why it was the right thing to do. And that’s not the only eyebrow-raising aspect of this story.

The customer in question is an insurance company, but not your typical insurance company. Focusing on commercial and industrial property insurance only and guided by the belief that most losses can be prevented, the company takes a proactive approach to property loss prevention. They use research and engineering expertise to help those they insure do everything they can to be resilient because resilience mitigates risk.insurance customer engagement

Another oddity: This company is NOT interested in attracting new customers. They are already engaged with the customers they want, and their only goal is to increase the loyalty of those customers, which requires building strong relationships. And this requires proactive engagement—a level of insurance customer engagement that would enable them to predict the customer’s needs.

The issue they were dealing with was getting information from an overwhelming set of 70 customer data sources. While data was plentiful, it was very difficult to access and work with, and the company had not fully engaged with its customers in a very long time.

Every company needs (and hopefully wants) to engage with customers, but insurance customer engagement is difficult. It’s a very soft metric—difficult to measure. While B2C companies have been doing this for some time now, we’re not so advanced on the B2B side. Companies are still struggling to engage with their customers in a more effective way because they’re sitting on mountains and mountains of data pointing them to different types of engagement. They have no way to rationally organize that data and unearth predictive patterns.

In the case of this insurance company, the challenge was in finding out as much information about a customer to understand how to ensure them for various things—building a new plant, for example. What information would the company need to study, how would they study it, and how would they identify the patterns that would tell them what to do next? The company wasn’t even sure which of their 70 sources of data to keep, much less what to do with that data.

Here is where we, the partner trying to win their business, acted, well, oddly.

The company originally wanted three things: a plan to migrate the 70 marketing communications data sources and multiple marketing technology platforms to a standardized platform, a process for managing customer data, and a recommendation for a marketing technology solution that would optimize insurance customer engagement.

We listened to their issues and requests and then said “no.” Instead, we proposed a data strategy around Microsoft Dynamics 365 Customer Insights. We suggested that what they really needed was technology to tell them what data they should be using—to organize that data—rather than having to pull it all into one place. That, we said, could be accomplished with the cloud computing power Microsoft offers. By recognizing patterns in data, conclusions can be drawn and decisions made about which data sources to use.

We suggested the best approach would be to start with a few data sources to look for patterns using Customer Insights, then adding more data sources little by little, making the data richer and richer, and revealing more and more patterns. The result would be the baseline for a customer data platform (CDP), sharing first insights and data combined from data sources and delivering a data-agnostic CDP that extracts, combines, and delivers new insights on customer behavior.

They weren’t expecting that answer. What they were expecting is what big consulting firms tend to do: tell them how to run their business and then sell them technology to run it that way. But they liked the idea. “Instead of giving us what we wanted,” said the CMO, “you gave us what we needed.”

And this…

Next, we proposed something else they had not considered but needed. The CMO had a bit of a mountain to climb. She not only had to find technology for insurance customer engagement; she had to get the entire organization, which had not been engaging with customers, to get on board.

Knowing this, we proposed doing a “road show” internally to build support from the organization (and more specifically, the executive team) for the plan, making the case for using data more effectively and demonstrating the benefits of using Customer Insights to do it.

Again, the CMO said it was what they needed, not what they asked for.

And this…

Since the first two projects would take some time, we again suggested something the CMO didn’t ask for: we could help build out the marketing data so she and her team could begin benefitting immediately from the new platform.