Three ways to evangelize AI-driven personalization as an insurance marketer

This article summarizes and extends ideas from a conversation between MetLife CMO Michael Roberts, former Aetna CMO David Edelman, and former AXA Group CMO Amy Radin. Watch the full conversation here.

Insurance marketers and their customers have incentives that are fundamentally aligned – after all, the best possible outcome for both the insurer and the insured is if a loss never occurs in the first place. Insurers don’t merely need to sell products – they need to help members minimize their losses, live healthier lifestyles, be safer drivers, and protect themselves and their families. When marketers focus on changing behavior, the purpose of the insurer and member align. This leads to healthier customers, less loss, and a more robust bottom line.

Marketing with purpose

“At MetLife,” Michael Roberts explains, “purpose has always been at the center of what we do and how we operate.” This sense of purpose – to help customers lead healthier, happier lives – drives insurance marketers to try to change customer behavior. These behavioral changes are not superficial – opening a particular email or buying a particular product – but fundamental. Health insurers want their customers to get regular preventative care. Auto insurers want their customers to make safe choices on the road. And to belabor the obvious, changing behavior is hard.

The challenge for marketers is creating lifecycle campaigns that educate members while influencing behaviors in the complex ecosystem of modern insurance. Most members don’t bother looking through welcome packets and rarely engage with insurers until they’re in a dire situation. Every member has different incentives, lifestyles, and situations. Any attempt to help members  change behaviors will require real relationships between marketer and customer built on real 1:1 personalization.

David Edelman explains, “we felt [at Aetna] that insurance companies should be changing their perspective from just providing an insurance product to actually helping people minimize their losses in the first place. And for health insurance companies, that meant helping people be healthier and actually building a relationship with members where we were a partner in helping people stay and get healthy.” The question, of course, is how marketers can build such relationships. 

For the CMOs we spoke to, AI has been an important part of the answer. “We all know as marketers,” says Amy Radin, “that one of the most difficult but important challenges we face is helping the people we want to serve with behavior change. The marketers I've worked with have wrestled with that their entire career and it's even more complicated today. AI can play a role in helping to make progress on that critical goal that not only helps us enable our purpose as insurance marketers, but also strengthens the business model underlying everything that we're trying to do.” 

But when it comes to AI, most enterprises can tell war stories of failed projects and abandoned solutions. How can marketers make sure AI implementations are a success rather than a cautionary tale? In this blog post, we outline three key strategies insurance marketers can use to evangelize AI in their organizations.

Start with the commercial outcome

New investments, and the effort required to implement new technologies, will require support from across the business. Building excitement and buy-in around a new initiative should start with the commercial outcome that initiative is going to achieve. Edelman says, “It starts with the marketer really understanding the economics of their business. The more you're grounded in the logic of the business, and bring that into the way you describe opportunities, the more powerful you'll be – you'll get more support, especially from the CFO’s organization.” 

Typically that approach means starting with one or two use cases and a clear story of the value they will bring the business. When Edelman served as CMO of Aetna, the organization recognized a challenge that needed solving. Most members weren’t familiar with basic health insurance concepts. Company research showed only seven percent of people understood the fundamentals of premiums, co-pays, co-insurance, and in network vs. out of network care. Members were going to out of network doctors or the emergency room when they could have visited urgent care. It was costing time and money for both Aetna and its members.

To help reduce costs, Aetna created a series of AI-driven, personalized videos that targeted members with helpful information for new members such as who in their family was covered, how to set up new primary care relationships, and member benefits that aligned with age and family structure. As Edelman says in the webinar “it was a total home run; 70 percent of people watched the three and a half minute video. Calls to the call center went down by 20 percent and net promoter score went up.”

Edelman and the Aetna marketing team used AI personalization to align with commercial outcomes: to reduce member costs through personalized educational campaigns. Once that use-case was off the ground, they proved that personalization and marketing innovation was worth the investment.

Be journey-aligned and experiment driven

If AI initiatives are going to impact the business, they need to be aligned to customer journeys, and to improving the outcomes of those journeys for the marketer. Personalizing without alignment to desired customer behavior, Roberts says, would be an “exercise in randomness.” Instead, by aligning personalization with the customer journey, marketers can build campaigns that help members and the business. 

Once marketers align their personalization strategy to their customer journeys, marketers need to continuoulsy experiment. AI learns from data. The more marketers experiment with every variable, the more targeted their strategy becomes. As Roberts says,, “If you don't have a sense of what the customer journey is overall, then you have nothing to align to. And if it's not experiment driven, then you'll never have the mechanism in order to confirm the assumptions that were in that initial business case that drives commercial outcomes.”

Avoid death by 1000 pilots

Before making significant investments in new technologies, most enterprises want to see a proof of value. Done well, this approach will build conviction that AI projects will deliver value. Unfortunately, organizations sometimes bounce from pilot to pilot without every implementing programs that drive results. 

Roberts explained that at MetLife, “I don’t call anything a pilot anymore. I call them phase one.” Scale should be considered at the beginning of any new marketing plan. Without forethought, marketers could find themselves in a perpetual cycle of pilots when they could be focused on quickly implementing 1:1 personalization across the business.

As Roberts explained, marketers need to change their mindset. “If you call a new experiment a pilot, then failure means the experiment is over. If you look at new campaigns as phase one, then you can reset your experiment, learn from it, and change. You either validate your hypothesis or change your strategy.”

By aligning personalization goals to business outcomes, constantly experimenting, and understanding scale from day one, insurance marketers can effectively implement artificial intelligence and change customer behaviors.