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Do You Even Data

A data-driven marketing blog

Want to learn how you can translate incredible data list information into killer marketing campaigns? Want to better understand how data research and models can enhance the data you already have?

9 Tips for Email Marketers Worth Repeating

Despite new marketing channels, like Instagram or Snapchat, email remains a great marketing tool. It’s fairly low-cost, highly measurable and provides swift feedback on your audience. These traits have made it a resilient channel in the face of emerging options. Despite its power and popularity – and the many, many guides available – email marketing can still be tricky. To boil it down, here’s a handy checklist to keep nearby. Like a preflight checklist for pilots, it’s nice to review the basics, no matter how pro you are. 9 Important Things To Consider Before You Hit Send Track Results. This seems painfully obvious, yet it needs to be said. It helps to be prepared. Consider ahead of time what you want to know, and what’s most important. How many people opened the email? How many consumed content? How many clicked through to your site? How many of the visitors that clicked through went on to take a desired action on your site? Be aware that setting up tracking goals and tools in your email software and on your website take time and forethought. Hook ‘em Fast. Give your reader a good reason to open your email. Imagine that your audience is sitting with their finger hovering over the delete button, eager to condemn any new email to the trash – because they are. Use the subject line to grab attention and always try to establish a) the purpose of your message and b) why they should care. Mobile Matters. Be sure that your email is compatible with being read on a mobile device as well as on the computer. Most emails are now read on mobile. If you’ve ever opened an email on your phone and had it render poorly, you know how annoying it is. Make sure you’re not making a bad impression. What Do You Want From Me? Make the call-to-action (CTA) clear, relevant, and pain-free. Don’t have too many CTAs. Be straightforward about the main thing you’d love for your reader to do next. (And yes, make sure that the content, landing pages, or site pages that you link to are also optimized for the mobile experience.) Be On Time. There are days of the week and times of day that perform better than others, but be sure that you’re tracking and analyzing results based on the time of day of the recipient, not of the email service provider (ESP). Make A Plan. In particular, create a content plan for your email campaigns. You can think of the content plan as needing to address seven main marketing factors: Who, What, Why, Where, How, Frequency (How Often), and Volume (How Much). You can always make modifications to the plan based on results or regional influences. Be Patient. Building a strong reputation and growing engagement with your audience takes time. There’s no good way to rush things, you’ll only hurt your progress. But consistency is important. Your email marketing can flourish if you stick with it. Multiple and steady impressions generally achieve better results than a “one-off” or “stop-and-go” approach. Success is achieved by steadily building an email presence and reputation with your audience over time. Target, Target, Target! Email provides quick results on things like opens and click-throughs. Maximize results by testing email variations to a portion of your audience (enough to get statistical significance) and roll-out the winners. Testing email is fast and cost efficient, so don’t skimp on testing against various segments and sub-sets of your audience. Be Cool. Email is regulated by the FTC and it is in your best interest to learn and follow the rules set out by the CAN-SPAM Act. CAN-SPAM applies to all commercial email messages, including those to your own database or to any lists rented, purchased or otherwise acquired. The rule makes no distinction between B2C and B2B; if you’re including email in your marketing mix, you need to be knowledgeable. See the main requirements below, or you can get the complete guide on the FTC’s website. Don’t use false or misleading header information. Don’t use deceptive subject lines. Identify the message as an ad. Tell recipients where you’re physically located. Tell recipients how to opt out of receiving future email from you. Honor opt-out requests promptly. Monitor what others are doing on your behalf Regardless of tactic, marketers looking to acquire new customers must build accurate profiles of current and past customers, as well as identify prospective future customers. Thankfully, technology is dramatically improving this part of the puzzle. In particular, datadecisions Group has developed automated predictive models that, for the first time, let B2C marketers understand their customers and find prospects – faster, easier and more accurately than previously possible.

datadecisions Group Acquires "Reach" the Platform

Mike, why did DDG acquire the “Reach Platform”?

Recruitment of Insurance Agents in 2018

I participate in many insurance industry meetings where the primary “pain” is the lack of new recruits for the field force.   Just this week, one firm noted a 20 percent shortfall in year to date recruitment.  Recruitment has many facets; in addition to a wide range of impacts on the financial outcomes for our marketing campaigns.  I will merely touch on three areas where I spend the majority of my time assisting Audience Identification Omnichannel Campaigns Business Intelligence from CRM system Custom Audience The first flaw I normally observe is the lack of attention and effort to correctly build the audience for the insurance offering.  Often, the responsibility is delegated to an individual agent—go get us a list of XXXX.  It is assumed that this is an easy and unimportant task.   Wow, it is the item with the most impact on the campaign’s success. Best practice audience creation requires:  -the determination of the significant data points that drive a decision. May require market research data and intensive modeling of large scale data aggregation -the data collection, data integration and database to match the audience identified in step 1 Agents are very bright folks but they are not data or analytical experts.  They may try to fulfill this role but they normally fail miserably and resent the firm that places them in that position. And the impact is a multiplier not a percentage.  Our DDG target audiences pull 3.5 to 10X compared to the in -house mailing list because we use propensity and predictive modeling. Omnichannel Campaigns Even though most firms operate in a silo fashion the consumer data needs to be organized in a single view scheme.   Then when consumers engage with our brand we have the ability to recognize them and respond in a personalized fashion.  The consumer might: Mail an inquiry Email the customer service center Search the website for a quote Click a Facebook ad Walk in a brick and mortar location If she/he did walk right up to your desk, could you actually engage them: - using real data about them—turning 66 today -their current or previous policy ownership—term life with approval to convert to whole life, -the trigger event that caused them to walk in—purchased a new home using a jumbo mortgage Now normally, we are seeking to mail, email or call them as our system recognizes that a trigger such as birthday, marriage, move, child birth has occurred.   Due to the scale of this effort we need automated campaign tools that implement our business rules on a 24/7 basis.  Again, if you are forcing the individual agent to select his campaign tool, set business rules and manage this process the effort is approximately 99 percent doomed. The platform that DDG implements depends on your marketing scheme as they systems have very different strengths and weaknesses. Closed Loop Marketing I am purposefully using an old vernacular here.  It is critical to build that an information process that tracks Consumer engagement-date and request Agent response-date and presentation Meeting date—did we meet face to face Sale details—closed for policy form with these premium dollars Many CRM tools exist today.  The key for recruitment is the presence of a system to help agent time management.  The ability to view the outcomes in business intelligence dashboards maintains the agent focus and morale.  In addition, if the customer service center is utilizing the same system then you reduce churn and increase customer satisfaction. Conclusion An insurance firm that generates a constant flow of interested to buy/qualified to buy prospects, maintains a continuous stream of communication with those consumers and assists the agent in sales time management will not suffer a recruitment shortage.    

  • 4 min read
  • Nov 1, 2018 3:00:07 PM

Center of Influence Sales or Data Driven Marketing

Surprisingly, 2018 marks the 40th year of selling and marketing in my career. My original on the job training focused on sales methods and techniques.  Naturally, I was introduced to the concept of center of influence for life insurance production.    So, at the risk of boring you already here is a quick list of those original audiences recommended to me: Family, friends                                 CPA/Lawyer Doctor/Dentist Business owners or leaders Government, school, church officials I observed many of my enthusiastic fellow newbies start building their networks of contacts.  I also monitored the level of failure to reach the minimum goals.  Most of the new recruits did not succeed. Luckily, I was tasked with a national direct mail effort by the CEO within 30 days of my recruitment.  And it opened my eyes to the ability to reach out to highly qualified contacts who I did not know.  In my small world, I was always the number 1 salesperson due to this knowledge.  I normally state that if I had to depend on my center of influence that I would have failed miserably.  I grew up in a rural area with lower socioeconomic conditions and very small population.  There were 8 students in my grade throughout my K-12 education.  In a job of numbers, that was very "slim pickins” Utilization of data, technology and analytics afforded me an infinite universe of influence by comparison. After careful consideration of my firm’s product, my product knowledge and the economic concerns at that moment in time, I could select the audience most likely to: a. need my services b. to listen to my presentation c. buy the policy and d. refer other buyers. Let me pause for a couple of different examples Challenge Agent, 22 years old.  New BBA in Finance.  No family/friend network.  Life Insurance firm—Good Brand recognition, excellent disability policy and cash value life products. Method Selected the Surgeons in the radius area by the year graduated from Medical School.  Used direct mail to present a major business issue for them—disability would cause a disruption in their cash flow which would possibly lead to loan defaults. Outcome The mailer produced a 1 percent response, 10 doctors inquired.   All 10 set up appointments and purchased disability policy.   Then each doctor offered a referral to their fellow doctors in their practice.  In this case that was an average of 5.  The agent had an ever- expanding circle of strong income professionals who would need his cash value solutions after the original loans for their medical school and practice were paid off.    Challenge Agent, 30 years old.  BBA in Marketing, making a career change. Senior market insurance services—Medicare supplement and retirement products Method Targeted the turning 62,63, 64, 65,66, years old audience in the radius area.  Used direct mail to invite them to a seminar on Medicare.  Medicare choices are extremely confusing to most consumers compared to their use of group health policies for most of their lives. Outcome 20 to 40 attendees per session.   50 percent would request a follow up meeting by submitting a complete financial profile stating their primary concerns.  The close rate for Medicare Supplement policies is very high.  And the same consumer also seeks the alternatives for their retirement funds—money management, cash value policy or annuity.  The agent has an ever- expanding circle of satisfied seniors with retirement funds who eagerly recommend his services.   Today, I have many more resources at my disposal to create a. custom audience b. write a personalized message c. conduct an omnichannel campaign d. predict the premium production I recommend that you build your center of influence by using data driven marketing.  Direct Mail is the foundation of that effort as legislation has restricted initial contacts by phone or email.  In the current digital age some young marketers dismiss the use of direct mail.   I smile as I know that effective direct mail drives my digital flow of inquiries and  initiates my center of influence.   Happy Hunting, as my original sale manager used to say!        

  • 4 min read
  • Oct 31, 2018 2:55:28 PM

Nested, Stacked, or Ensembled? Improving Policyholder Acquisition for Life Insurance Companies

Life insurance companies that utilize direct mail marketing have relied on traditional response models to more efficiently target consumers for whom their products are relevant, attractive, appropriate and affordable.  The actuaries at life insurance companies have applied sophisticated data science for years to establish risk, premiums, marketing allowances and more. The actuaries at these companies learned a fundamental truth about consumers: people are different demographically, behaviorally and socio-economically.  Women generally live longer than men.  Smokers represent an extremely high risk.  There are  high risk activities that some consumers enjoy more than others.  In terms of  health outcomes heredity has a role, body mass index has a role, and overall lifestyle has a role.  Of course, these factors can be unique to each consumer. Paradoxically, the same principles that insurers use to accurately underwrite or deny life insurance policies also apply to the marketing of those policies.  Why?  Both analytic processes are attempting to predict an outcome; in the case of direct mail marketing, the outcome is a positive response to a marketing campaign and ultimately a sale.   Consumers’ responses to marketing are based on different factors.  These factors reflect who they are, where they are, how they behave, their attitude toward the world around them, their family situation, and what comprises their overall lifestyles.  This is why “one size fits all” or “out of the box” predictive analysis does not work well when it comes to predicting response behavior. There are methods that utilize multiple segment-based models to determine which models—or combination of models—yield the highest response for a given audience.  This methodology is alternatively referred to as ensemble modeling, model stacking, or nested modeling.  Each of these specific approaches has subtle differences that are meaningful to nerdy data scientists, but their outcomes are the same:  build and combine models that yield the greatest lift across diverse, heterogeneous population by determining market segments or geographic segments and refine the modeling parameters within each of those.  Today, we’re going to focus on a nested modeling methodology. Nested models are founded on the premise that different consumer characteristics—whether they be geographic, demographic, lifestyle, attitudinal or behavioral—result in different reasons why people respond or do not respond. The problem with this approach is that the more ingredients that get added to the model soup recipe, the more diluted the outcome of that recipe becomes.  It’s like the old data science joke analogy about the fallacy of marketing to the average consumer: you’re standing in a bucket of ice water with your head stuck in a hot oven.  On average, you feel just fine! Nested models use the same group of predictors, but instead reserve the most differentiating variables to effectively distribute the target audience into more homogeneous population cohorts.   Each group is modeled independently, and then reassembled into a single target audience with optimum response propensity. As we said, variables with significant value differences across different groups make good candidates for nesting within the overall ensemble.  In the example below, we see that consumers’ state of residence is a meaningful separating factor because of very different population attributes.  In the example below, we are focusing on the 64+ population. Nesting is not necessarily limited to a single variable split; indeed, the modeler can further refine and tune the final model through multiple levels of nesting.  This has become a far more feasible approach than in the recent past due to fast (usually cloud-based) computing resources and statistical software applications that facilitate builds like this.  In our example, we find that we can leverage many of these demographic variables to optimize response for our life insurance direct marketing campaign. How does this approach work in reality?  The effectiveness of response models is measured by lift, a statistic that demonstrates how much mailing efficiency the final model yields with actual response rates.  In the chart below, “global model” is the application of a single, traditional response model.  “Individual state models” refers to models constructed like the diagram above demonstrates, and “best model for each case” selects the higher of the two resulting propensity scores for each prospective consumer. The bottom line is that with a smart, thoughtful nested modeling approach, an insurance company would realize enormous savings in its direct marketing costs.  Reach us to see how our approach can benefit your business.

  • 4 min read
  • Aug 15, 2018 12:58:11 PM

The 2019 Medicare plan enrollment period may be exhausting!

First, the consumer will have from October 15th to December 7th, 2018 for AEP.  Then from January 1st to March 31st, 2019 there will be an open enrollment period. What communication plan do you have to first indicate that you would like to be the healthcare provider and then insure they are satisfied with their choice? At DDG, we segment this audience into market segments*: Consumers who wish to become a Medicare Advantage Member:  1,049,182 Individuals who prefer to purchase Medicare Supplement Insurance:  1,255,367 Persons who desire PDP (Part D) only:  937,833 Dual Eligible individuals:  488,602 Special Needs Persons (SNP):  6,621,042 Turning 65**           3,342,487 Turning 66**           3,342,487 Turning 67**           3,236,222 Movers***                1,305,457 These audiences are very useful in AEP campaigns—direct mail and Facebook.  We call these custom audiences-dataFaces.   However, OEP will present a different challenge.  Our market(ing) research does indicate that many consumers can not accurately describe the form of Medicare coverage they possess. Do you have a Medicare Advantage Plan? Does it include prescription drug coverage? Did you purchase a Medicare Supplement policy? Are you dependent on only Medicare Part A and Part B? Thus, it is certainly understandable that the member can become very dissatisfied with their coverage during the following months.  For example, did the individual consumer grasp that the PDP selected should match the prescription drugs that they are currently using? Does your customer service groups have training that enables them to assist the consumer in making the choice that optimizes their satisfaction?   Or does your member learn that they had choices from their neighbor and thus becomes irate that your firm did not explain. To measure your risk of “members switching” you can consider both a. market research and b. churn analytics.   Obviously, the goal of the two exercises is different but both can provide you with keen insight for member behavior in OEP.

  • 3 min read
  • Aug 9, 2018 3:51:22 PM

3 Million Consumers Who are Likely to Enroll in Medicare Advantage

These consumers are likely to enroll in or switch a Medicare Advantage program during this year’s AEP.