How Insurers Became Customer-Aware

A couple of years ago, I began to notice an interesting shift in the insurance industry: Insurers were becoming customer-aware! For those of you in the industry, you will understand the significance of this. I spent the majority of my career at two major insurers (life and property/casualty), and both of them referred to themselves as "product factories" – churning out whatever new products the actuaries could come up with and putting them in the hands of third-party distribution networks, agents and advisers to sell to a consumer. These factories tended to also be very good at operational service strategies, providing help and policy support to legions of agents and customers.

But the last few years have brought significant change to the industry: Insurers merged, acquired and divested their companies of certain noncore lines of business. Those changes were accompanied by overhauls at the product level, as well, with changes in offerings, benefits and coverage. Some of that product strategy shift is being driven by demographic shifts in the customer base. The market for life insurance, for example, in an insurer's core demographic – baby boomers – is fairly saturated. The Gen X and Gen Y demographic segments are underpenetrated, but these folks may not be in the market for a complex life product. Insurers have responded to that need by creating simplified products, but acquisition costs make it challenging to sell those products through traditional third-party channels. With the pervasiveness of web and social commerce channels, the way that Gen X and Y demographics want to transact business is very different as well. So there's a huge market of underinsured and noninsured people out there, but tapping into that market means enormous business and organizational transformation for the industry. Insurers needed to find a new way to directly engage and interact with these important demographic segments.

Rachel Alt-Simmons, SAS

So insurers became customer-aware, and some interesting things started to happen. The first was an organizational awareness: Insurers created new chief marketing officer (CMO) roles and brought in experienced marketing leaders, primarily from the financial services industry. These new CMOs quickly began to develop strategies to move insurers from being customer-aware to becoming customer-centric. The customer-centric insurer knows and engages with customers on their terms and anticipates their needs.

Many of the strategies started with operational transformations, with the contact center as the new customer-centric hub. Around the hub, disjointed marketing campaign strategies, customer relationship strategies, analytics, and operational strategies were synchronized (at least on paper!). For the first time, many insurers started to look at the full customer life cycle and how it flows through their infrastructure.

The contact center took on a new role as a profit center as insurers expanded their sales channels beyond traditional third-party distribution. While agents, brokers and advisers are still critical in the insurance industry, direct sales channels are being opened with customers, primarily through the contact center and web. The insurance customer representative of the future not only provides good service, but cross- and up-sells customers with the right offer at the right time. Yet these are only two channels: Customer-centric insurers leverage all the channels at their disposal – contact center, web, adviser, mobile, social, direct mail, email – in an integrated and coordinated way.

There's a lot of complexity there. A large scale transformation like this requires significant change. Organizationally, it necessitates a shift away from product silos to customer segments. Marketing planning and execution strategies need to be coordinated and streamlined. The underlying operational technology platforms and systems need to connect in a way that accommodates the customer-centric perspective. Cross-functional operational workflows need to be redesigned around a customer view. The customer data needs to be integrated, analyzed and modeled in a way to provide a complete view of that customer. Analytics and predictive modeling provide insights to help anticipate customer needs and behavior. The entire organization mobilizes around a customer-centric hub.

[Previously from Alt-Simmons: Finding a Common Analytics Language]

In a recent conversation I had with some industry friends, we talked through several enabling business strategies for our hub. Here are some highlights:

• Contact strategy: This is a critical (and sometimes neglected) component of the overall hub. The contact strategy outlines how you will interact with customers, what their preferences are, and the optimal sequence of events. For example, let's say you have a customer who comes in through the web, and you present an offer (e.g., upgrade coverage or contribution rates). If the offer is declined, you might elect to send a follow-up email or place an outbound call in a few days. If it is declined again, ensure that the customer doesn't receive that offer again (or for a specified period of time). The contact strategy takes into account things like customer needs and preferences, offer eligibility criteria and campaign response history to ensure that the right offer is presented to the right customer in the preferred channel.

• Marketing strategy and management: Marketing teams provide the heartbeat of the process by coordinating the design and execution of the marketing strategy. This includes customer segmentation and analysis (who is my customer?), campaign planning (what are our organizational goals?), campaign operating rhythm (how do I get that message to my customer?), and campaign performance management (how successful are our campaigns?). Sophisticated organizations use optimization techniques in their planning process to balance the trade-offs between eligible campaign populations and available offers.

• Model strategy and lifecycle management: Predictive models can anticipate the likelihood of a person to respond to an offer, or respond to an offer within a particular channel. Coupled with customer segmentation strategies, models can help you focus on groups of like people to understand and anticipate their behavior, facilitating custom messaging and content instead of taking a one-size-fits-all approach. Model scores, represented as a percentage likelihood to respond to a given event or fit a various profile, can be integrated as decision points within a rules or decision management architecture.

• Rules strategy and architecture: The decision making mechanism forms an important layer in the strategy. In addition to offer eligibility rules, underwriting or even fraud detection rules can be layered into the process.

• Data strategy and architecture: Of course, none of this is possible without data. Ideally, you have this perfect database with a complete view of your customers and everything you want to know about them in one place. Unfortunately, that's just not a reality for many organizations. But don't fear – many organizations take an incremental approach to getting out of product silos and into a customer-centric data view. One company started at the customer/product level, graduated to the customer level, and then into the household level.

While it may sound daunting, there are pragmatic approaches to increasing competencies in all of these areas and incrementally developing the organizational and technology frameworks to enable them. Few insurers have mastered all elements of this vision. You just need to frame your goals, identify your current capabilities, prioritize your high-impact opportunities, and test and learn along the way.

About the author: Rachel Alt-Simmons is the Senior Industry Consultant for Insurance at Cary, NC,-based SAS. Simmons has driven business intelligence initiatives at Travelers and Hartford Life and has been Research Director for Life & Annuity at research firm TowerGroup.