Insurance companies are planning to introduce multiple artificial intelligence (AI) applications over the next few years. If all goes to plan, the industry will experience new products, better marketing, and reimagined customer experiences, all with major contributions from AI. Insurance CMOs have a major stake in this evolution considering how these technologies are positioned will affect brand perception, engagement, and other marketing outcomes. One of the first applications of AI to market is virtual assistance which, according to Forrester, about 25 percent of global insurance companies expect to launch by the end of 2018.
Virtual assistance (chatbots, virtual agents, digital assistants, etc.) makes it easier for customers to answer questions and perform many transactions. It also reduces costs by reducing the number and duration of human assisted calls.
In theory, this should be positive for both the insurance company and the customer. So how should your brand introduce these capabilities?
Some of the early adopters, like Lemonade, have made virtual assistance part of their brand. These companies are following in the footsteps of GEICO, Progressive, and Esurance which embraced online quoting as part of their personas more than a decade ago. Given the historic success of this model, it won’t be surprising to see more companies adopt a similar approach.
But that might not be the right path for all companies.The answer will therefore be different for the company that serves an ultra-preferred vs. non-standard audience; millennials vs. 50+, teachers vs. military, employees, and so on. The answer might even be different for existing customers vs. prospects.
There are many ways to understand the receptiveness to new technology and how it impacts a carrier’s target market. Primary research can supply much of the basic data, but CMOs need to take an additional step to get at underlying motivations. One data-driven approach is to tie individual-level customer and prospect data back to third-party demographic, attitude, media, and behavioral data. Analytics teams can then look at patterns of technology adoption and attitude and align those to their own transactional data (which customers call, which transact online, how often, why, etc.). This approach can be used to create segments and assign them to specific adoption tests.
Another approach is to blend quantitative and qualitative research. This can include methods designed to understand both rational and subconscious behavior drivers. Merkle has used these methods to understand that millennial insurance decisions are often tied to motivations including “being respected by others,” “personal achievement,” and “enjoyment of life.” In contrast, the broader market tends to make decisions based on other motivators like “safety and peace of mind.”
Using this approach, CMOs can plan for the introduction of virtual assistants by understanding the relevant connections within their target customers’ mental maps for insurance decisions. Virtual assistance could be positioned to millennials as a tool to help them both make smart decisions quickly and become more insurance-savvy in the process. A more general audience positioning could center on getting answers quickly and ensuring customers have the (otherwise unappreciated) coverages they need for their unique life situation.
I welcome your thoughts on this topic. My next post will discuss the strategic use of humans in the age of virtual insurance assistants.