Insurance technology and data have evolved, making it much easier for insurers to understand their portfolios, market segmentation, and targeting efforts. These capabilities offer a tremendous competitive advantage in terms of increased revenue per policyholder, average policy size, and strike rates.
The portfolio of every insurance company contains a series of stories — discrete groups of policyholders — that have collectively driven profitability over a period of years. Each of these groups is different, reflecting a unique set of characteristics and matching profitability. These groups became established in the portfolio over time and persist through ever-changing competitive landscapes, including insurer and competitor rate changes. These groups give a company its unique brand and general customer profile.
Marketing programs typically focus heavily on quantity with little ability to focus on the very profitable customers. Television and social media campaigns are often directed away from quality because they’re heavily based on price reductions: “Customers who switched from company A to company B saved an average of X dollars.” This style of marketing, which relies on quantity at the sacrifice of quality, is prevalent in most insurance markets worldwide. Quality experiences are often ignored until after prospects join the insurer’s portfolio, when they can be targeted through underwriting processes and analytics such as customer lifetime value (LTV).
How do you move in a more targeted, data-driven direction? You can focus on a quality marketing process by looking at two key points of information:
Operational intelligence: Start by leveraging the knowledge and understanding that your staff and intermediaries have accumulated from many years of collective experience. Operational staff have developed a series of hypotheses relating to the profiles of insureds that are either profitable or not profitable. These hypotheses are generally described in relatively simple terms of three to five variables. With a set of variables defined for each hypothesis, you can test the profitability by using analytics.
Portfolio intelligence: Use analytics to uncover the secrets embedded in your portfolio. An insurer’s operational portfolio represents the collective value of millions of macro- and micro-decisions made by insurance staff, executives, product managers, actuaries, underwriters, agents, and insureds over time. You can mine your portfolio so that it discloses these secrets.
To identify lists of potential quality marketing campaigns, perform these steps:
Determine the variables: Determine all available variables that can be used in a marketing campaign.
Define and apply the variables: Run the variables through predictive models to target profitable segments and policyholders. For best results, use a description of each customer group limited to a small, simple set of variables that can easily be used in a marketing campaign. There are typically three or four variables that include geographic and major risk attribute markers. For example, you can search for older homes (> 8 years) at ZIP codes with low elevations (under 1,000 feet) that will point to a combined ratio of 78% (compared to a portfolio combined ratio of, say, 98.4).
Identify marketing campaigns: The analysis returns a series of potentially profitable marketing campaigns with credible customer groups with combined ratios 20% less than the portfolio average. Each possible campaign is listed with measures of reliability and persistence over several years.
Prioritize opportunities: Sort the list of possible campaigns to select a set of the most practical and profitable opportunities or targeted subgroups.
Leveraging the operational and portfolio intelligence of a company helps insurers develop a series of marketing campaigns that will return an increased percentage of profitable prospects. After underwriting, these prospects also become profitable policyholders. By doing this, insurers can improve their combined ratio and avoid most of the typical “race to the bottom” strategies in which marketing campaigns focus primarily on quantity and price-driven decisions.