BIG DATA, ANALYTICS AND THE EMERGING HEALTH INSURANCE MARKET

Transcription

1 Insurance & Wealth Management HEALTHCARE REFORM BIG DATA, ANALYTICS AND THE EMERGING HEALTH INSURANCE MARKET Thought Leadership Series 1

2 Healthcare Reform The future of Healthcare Reform promises big changes, uncertainties and new challenges for health insurers, providers and customers. Although some final details and rules of healthcare reform legislation (HCR) are still to be determined, modified or clarified, as the market evolves, certain new realities are likely to remain, aecting the way health organizations operate and interact with consumers. Key HCR provisions, such as the formation of insurance exchanges, significant underwriting limitations, pricing limitations and the individual mandate will not only generate new markets, but also increase challenges for insurers and their provider networks. Although it is not certain that 2014 will bring immediate impacts on the insurance market, with the Obama administration in place, attempts to make the HCR work will continue. And while some details, such as covered services, might be modified, a reversal of key provisions is unlikely. Health insurers in particular will need to revise long-standing business models to evolve from being business-to-business focused to becoming a consumer-centric organization. Therefore, most have already begun the process of rapidly adopting to anticipated post-hcr challenges and opportunities by putting necessary changes in place. While the list of challenges is vast, most can be grouped into three recognizable management functions: costs control management, risk management and growth management. Among these, cost management may be the foundational challenge that will aect future success. It is expected that most standard health insurance products, especially on the health exchanges, will be focused on providing coverage through narrow provider networks that only cover mandated services. Products will be fairly commoditized and will present limited pricing power because of it. Barring the influence of brand and small network dierences, an insurer s ability to provide a competitive, yet profitable, price will drive most long term growth opportunities on the exchanges and potentially o-exchange as well. Pricing products competitively will be directly correlated with an insurer s (and eventually the provider s) costs management ability. Closely related to cost containment will be the need to manage risks. With the restrictions on health underwriting and the take all comers HCR requirements, insurance marketing departments will be challenged to leverage data and analytics to identify and acquire lower risk segments to balance out the high risk segments, which are inevitably going to be added to their books Insurance & Wealth Management

3 Big Data, Analytics and the Emerging Health Insurance Market Figure 1: Analytics Funnel for Payor Operations Predictive Models Growth Analytics Costs Risk Optimization Integrated Data Finally, managing and fostering growth will become a critical science for most insurers in this new, highly competitive world. With distinct margin and medical loss ratio limitations in the HCR act, the ability to grow profitably over the long run will primarily be driven by top-line growth. Eective marketing and sales strategies will become a significant focus for those insurers looking to grow in the exchange markets. However, eectively managing growth not only entails acquiring the right risks and understanding the eects of networks on adverse selection; it also requires a strong, data-driven foundation on which to build an eicient marketing organization focused on brand, direct marketing, customer experience and retention. The role of analytics leadership and data-driven marketing in a post-hcr world: Post HCR, marketing organizations will be challenged to contribute to the three overall objectives of cost, risk and growth management. As insurance products commoditize, especially at the basic levels, marketing organizations will be required to drive incremental leads and sales and lower overall costs. While expenditure decisions should be tied to the overall profitability of products and segments using lifetime value, the general consensus indicates that the biggest membership growth will probably come from Bronze and Silver (commoditized) level insurance products. Due to this trend, it is critical for health insurers to start looking at data-driven strategies to better dierentiate products, eiciently target prospective members and actively work to retain desirable members. Table 1. Role of Analytics across Marketing Functions Direct Marketing Customer Experience Customer Insights Branding Marketing Mix Analytics Prospect Targeting & Risk Program Targeting & Engagement Segmentation & Buying Behavior Segment Driven Messaging Digital Analytics Prospect Targeting & Risk Targeting for Paperless Engagement Digital Pathway Analysis Social Media & Online Branding Targeting Analytics Prospect Targeting & Risk Optimize Program Mix Media Channel Preference Media Mix Methods Based Brand Tracking SHIV GUPTA SENIOR DIRECTOR, MERKLE ANALYTICS SHGUPTA@MERKLEINC.COM MERKLE MERKLEINC.COM 2013 MERKLE INC. 3

4 Healthcare Reform 1. Direct marketing functions will face the challenge of increasing sales leads, while lowering overall cost per lead and conversion. This will require developing ever greater precision around the most appropriate target audience by product. With the incorporation of targeting, response and conversion models along with regular review of targeting data, direct marketing organizations can decrease current cost-per-lead / costper-sale values by 30% or more. In addition to increasing leads, direct marketing functions will have to take on the role of attracting good risks to help oset the introduction of high-risk populations into the book of business. This will involve the development of risk and lifetime valuebased targeting models in addition to response, conversion and media optimization models, if not already in place. 2. Customer experience must become the first step in eective costs management and retention. Organizations need to develop a dierentiated and optimized member experience with the ability to capture and measure data related to cost-of-care initiatives, including health management program enrollment, engagement and its outcomes (costs savings and retention). Once the proper data history is established, the application of predictive analytics can be used to help refine audience targeting and improve program KPIs. In addition, customer engagement initiatives should utilize predictive retention models to proactively identify desirable members with high attrition potential. In the initial stages of exchange development, identifying existing members who are going to be dumped onto the exchange by their current employer will present an additional opportunity to retain members. 3. As buyer behavior evolves within and outside of the exchanges, customer research and insights departments will be challenged with redefining market segments (along with their profitability). Regular studies evaluating the purchase process or a more robust buyer pathway analysis will provide valuable insights, not only on brand consideration and perceptions, but key moments of truth in the purchase cycle where marketing-savvy insurers can exercise influence. A complete view of the buyer pathway analysis should include a review of the digital pathway, from search or display ads to company websites and the online application process. Additionally, customer insights research, including media consumption studies, can be used to gain an understanding of media and sales channel preferences by segment. 4. Finally, as the market becomes ever more competitive, with providers and other related businesses, as well as small new players exploring the insurance space, marketing departments will need to become experts at creating strong, research-driven dierentiation strategies and have to be able to tightly measure and manage the returns on branding expenditures. In order to understand if branding makes the right dierence, it is important to capture regular measures of brand equity and brand health (such as recognition, consideration and dierentiation). Regularly incorporating brand measurement into marketing mix studies will provide a secondary, non-survey-based measure of brand eectiveness. 4 Insurance & Wealth Management

5 Big Data, Analytics and the Emerging Health Insurance Market Utilizing the right analytics to support the marketing initiatives above will help organizations develop a strong system of measurement and ROI analysis to identify opportunities for improved marketing eiciency, overall risk reduction, growth and channel optimization. Some key analytics initiatives should be considered: 1. Targeting & Optimization Analytics Suite: Targeting and channel optimization analytics have been practiced by direct marketing organizations for many years. This suite of analytic tools includes targeting, response, cross-sell and conversion models (by marketing channel), which provide marketers with the ability to identify low response segments and re-deploy resources towards targeting high-response segments or other areas of marketing, where funds may be better utilized. Merkle found that implementing this suite of models can result in 10-30% program savings over a short period of time. As insurers book of business evolves, insurers may also find the need to promote a more profitable product to improve their overall medical loss ratio. In these cases, an established data-driven targeting program will provide an agile ability to target the most appropriate prospects for the product. Finally, direct marketing must address the challenge and need to help reduce portfolio risk by targeting better options though risk-based models and other key performance indicators. 2. Digital Analytics Suite: Digital channels aord an even better ability to improve targeting and eiciency. This is driven by the ability to target in real time, on a lead-by-lead basis. With the introduction of instantaneous bidding, marketers can make individual-level targeting decisions and decide what price to pay in real time, based on the cookie history of a prospect. Response data can be available in a very short period of time, enabling marketers to continually improve digital targeting eorts. 3. Marketing Mix Models: Marketing organizations generally have some type of direct attribution tracking program. Often the call center is responsible for capturing or assigning promo codes based on a caller s promotion description. Aside from the reporting errors associated with this method, direct attribution also fails to take into account halo eects that certain channels may have on the overall media mix. Due to highly targeted b-to-c campaigns employed by health insurers, such as Age-in and Med Advantage programs, there has traditionally been a strong reliance on direct mail. However, Merkle s media mix optimization (MMO) research has shown that media channels, such as direct response television (DRTV) and online display, which tend to have lower direct response, may be critical drivers of direct mail response. With the addition of a growing under-65 market, insurers will need to rely on a broader media mix that is not only segmented appropriately, but also utilizes all marketing channels in an integrated manner to increase the overall response rate. Using marketing mix models, marketers are better able to understand how their current marketing mix aects overall lead volume (direct and indirect) and can help marketers rebalance their marketing spend across various media channels to improve lead generation eiciencies. MMO models can also provide a measure of brand eects on lead volume, which is generally diicult to do through brand tracking and survey based measures relying on self-reported purchase intent. SHIV GUPTA SENIOR DIRECTOR, MERKLE ANALYTICS SHGUPTA@MERKLEINC.COM MERKLE MERKLEINC.COM 2013 MERKLE INC. 5

6 Healthcare Reform Data Management Strategy The ability to develop a cost-eicient, optimized organization must have its foundations in an eective data management strategy supporting a connected view of prospects and current customers/members. Merkle refers to this strategy as Connected CRM. Not to be confused to traditional CRM programs, Connected CRM refers to the ability to identify, serve, and retain customers based upon their value better than competitors through orchestrated customer interactions that improve financial results, create competitive advantage, and drive shareholder value. The result allows marketers to track, measure and optimize customer relationships across the complete lifecycle, including prospecting, acquisition, engagement, retention and remarketing. Each stage captures distinctly critical data for the customer experience. The table below outlines key pieces of information that should be captured. Table 2: High Level Data Capture by Lifecycle Stage Prospecting Acquisition Retention & Engagement Re-Acquisition Multi-sourced prospecting data Contact History (Online & Oline) Sales Disposition Data Transaction Data LTV/ Targeting Scores Risk Scores Personal Identifiers Contact History Program Response Engagment Measures Response & Engagement Channels Program Outcomes Net Promoter Scores Customer Satisfaction Personal Identifiers LTV Cross- Sell History Product Purchase History Channel Preferences Program Engagement History Address Preferred Contact Method Prospecting & Acquisition: Aside from compliance with Centers for Medicare & Medicaid Services (CMS) and other regulatory bodies, eectively managing prospecting and acquisition data provides additional advantages. Using a multisourced database with the broadest footprint and a large list of predictive variables will be important for expanding the prospect universe and developing better response, conversion and risk scores. For most companies, the real and achievable challenge is to also capture valuable sales disposition information, which can be used to coordinate remarketing eorts through targeted online ads or relevant direct mail. Retention and Engagement: For most companies, this may be the biggest data challenge and opportunity. A wellexecuted retention and engagement data program should capture all aspects of member communication, from simple explanation-of-benefits (EOB) statements and account service to disease management programs. This information has the greatest potential to drive costs savings and achieve high member satisfaction. Insurers must begin to capture and understand response, level of engagement, eects on usage, and member satisfaction of channels and programs. Once captured, this information can be used to reduce communication costs by substituting digital channels for routine communications, or to reduce costs of care by better understanding how members would like to participate in their care management. 6 Insurance & Wealth Management

7 Big Data, Analytics and the Emerging Health Insurance Market Re-Acquisition: Good data to support re-capture decisions can help to reduce costs. The truth is that valued members will leave and insurers will need to recognize who they are, why they left and what their usage and product history is. This information will allow insurers to re-target attractive ex-members with messages suited to their needs, such as, price or provider network changes. In other cases, ex-members who were not suited for the insurers coverage and provider network can be suppressed from prospecting lists in the future. Channel Integration: Finally, marketing needs to be able view prospects and members across all channels (online and oline) in which they might choose interact with you. The benefits of channel integration are two-fold. First, it helps develop a better understanding of how various consumer segments use marketing channels in their purchase cycle. For example, does visiting a certain webpage increase the likelihood of a call center conversion? If so, understanding the dierentiating web content may lead to better conversion in other channels as well. Second, marketers need to capture attribution across channels to understand the eects of online channels on oline sales, or visa versa and to better balance budget allocation across channels on a segment level. Conclusions While there is some uncertainty of how HCR will aect the healthcare industry in the long run, there is reason to believe that the genie is not going back into the bottle anytime soon. Despite the challenges ahead, HCR will also present many new opportunities for savvy insurers who are adept at managing costs, risk and growth. In order to eectively meet these management challenges, the adage you cannot manage what you cannot measure will need to become a central mantra and feed the development of strong, data-driven decision making within health insurances companies and their associated provider networks. A robust data collection strategy, combined with creative use of analytics, and integrated marketing strategies can greatly aect how well a company optimizes its programs and its competitive agility in the marketplace. SHIV GUPTA SENIOR DIRECTOR, MERKLE ANALYTICS SHGUPTA@MERKLEINC.COM MERKLE MERKLEINC.COM 2013 MERKLE INC. 7

8 About the Author Shiv Gupta Senior Director, Merkle Analytics As Senior Director, Merkle Analytics, Shiv consults on analytically driven strategies, including marketing optimization and executing on data-driven strategy. Shiv currently leads Merkle s eorts to define analytic strategy for health insurance clients in the post Healthcare Reform world. Shiv has over 14 years of experience developing and executing analytics driven strategies for fortune 100 companies across multiple industries, including retail, consumer packaged goods, insurance and energy. He is also an expert on the concepts of customer equity, lifetime value and the use of predictive modeling to support growth strategies. Shiv has been broadly recognized for his innovative approach towards retention and profitable growth strategies. His work has also been highlighted in trade and professional magazines such as Target Marketing and Loyalty Management. Prior to joining Merkle in 2011, Shiv was co-owner of an independent insurance services company, where he developed a ground level understanding of the health and P&C markets experience which informs his ability to provide pragmatic and eective advice to his current clients. In his last client-side role, Shiv was director of insights and innovation at Farmers Insurance (the third largest personal lines insurer in the US), where he led the development of new marketing analytics and ROI functions. In addition, Shiv also led the eorts to acquire and retain high lifetime value customers and was recognized as a Frost & Sullivan Growth Best Practices business leader for Shiv also brings significant experience leading analytics in the retail and CPG verticals, including: CRM program optimization and ROI Retail pricing analytics, including seasonal markdown strategies and market basket analysis In-store and call center customer experience analytics Shiv is an MBA graduate of the University of Chicago- Booth School of Business. About Merkle merkleinc.com linkedin.com/company/merkle facebook.com/merkleinc twitter.com/merklecrm flickr.com/photos/merkleinc youtube.com/user/merklecrm 4/13 Insurance & Merkle, a customer relationship marketing (CRM) firm, is the nation s largest privately-held agency. For more than 20 years, Fortune 1000 companies and leading nonprofit organizations have partnered with Merkle to maximize the value of their customer portfolios. By combining a complete range of marketing, technical, analytical and creative disciplines, Merkle works with clients to design, execute and evaluate connected CRM programs. With more than 1,700 employees, Merkle is headquartered near Baltimore in Columbia, Maryland with additional oices in Boston; Denver; Little Rock; Minneapolis; New York; Philadelphia; Pittsburgh; San Francisco; Hagerstown, MD and Shanghai. For more information, Wealth Management contact Merkle at Merkle or visit