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Unlocking the Power of Patient Personas and Attitudinal/Behavioral Segmentation

By Susan Perkins and Joel English, BVK

There is an age-old marketing saying that goes “I know that 50 percent of my advertising is working, I just don’t know which 50 percent.” This speaks to an inherent weakness in mass marketing, which broadcasts a message that is only attractive and motivational to a subset of the receiving public and forces us to live with its uncertainty and inefficiency.

Thankfully, the world of big data and the emergence of subscription and social channels as engagement vehicles have taken us to a much better place in accomplishing the concurrent goals of every marketing effort: maximum effectiveness and optimal efficiency.

A Breakthrough: Demographically-Based Disease State Propensity Modeling

An early breakthrough came with the availability of disease state incidence data, which opened the door to disease state propensity modeling. The ability to identify demographic variables that best predict the likelihood of contracting a specific disease was the starting point for healthcare CRM systems, enabling marketers to get closer to the ideal of “the right message, in the right place, at the right time, to the right person.”

This was a great advancement, but still not enough for marketers to achieve maximum effectiveness and efficiency. Savvy healthcare marketers have long known that people are far more than their body parts and disease states—that simply having a heightened risk factor for a disease doesn’t predict how someone will act if and when they are diagnosed with the condition. For example:

  • One high-risk person diligently researches and proactively engages in preventative and screening measures.
  • Another crowdsources with a wide range of people and then shares their learnings with their doctor to help inform the ultimate course of action.
  • Another waits until the disease is acute and then goes to the ER.

While risk/propensity-based efforts are more efficient than mass marketing, they address neither the behavioral aspects of decision-making nor the broader context of what people want out of the healthcare experience, both of which directly impact the care they seek and how they feel about it afterwards.

Enter Patient Personas

Intended to tell a more complete story, beginning with likely healthcare need but moving far beyond to attitudes, behaviors, and expectations that impact decision making, personas give marketers more dimensions to work with in their quest for maximum effectiveness and optimal efficiency. And they provide the ability to not only engage but to also design an experience to help ensure that the organization delivers what the target audience wants in order to build loyalty and advocacy.

Sound good? Absolutely. But there is one catch: Demographic profiling connects disease risk to self-reported or easily modeled demographic variables so marketers can, with reasonable efficiency, find the people they are trying to target (while largely excluding non-targets). Adding in attitudes and behaviors provides needed richness and dimension, but those features are far harder to identify in or affix to individuals in a population.

So how can a marketer connect attitudes and behaviors to concrete criteria that can be used to more effectively target an attitudinally and behaviorally-defined persona? Tailored messages can certainly be created for target segments and then communicated broadly, with the hope that the intended segments will find them and respond. Although that might be effective (if the right people find the messages), it is not the most efficient way to market.

Marketers also can intuitively discern some media planning variables that can help reach people that fit a target persona. The challenge is tying those variables to actual media habits and vehicles to ensure more accurate targeting.

The bottom line is, to truly benefit from the power of personas, research-based, persona-specific targeting methods are needed.

Diffusion of Innovation Theory and Early Adopters

Based on an intriguing body of work described as “Diffusion of Innovations Theory” (Rogers, 1962, 1971, 2003), BVK sought to understand healthcare early adopters and how this behavior might impact the healthcare services they use and how they access them.

A national study conducted in partnership with NRC revealed that healthcare early adopters comprise a unique and highly desirable attitudinal and behavioral cohort. Early adopters identified themselves as being:

  • More interested in new retail services
  • Healthier than other groups
  • More inclined to manage their health
  • More willing to shop around for healthcare services

Yet they also reported much higher use of healthcare services despite self-reporting as healthy. And, surprisingly, considering their willingness to shop around, they reported a desire to be loyal to one healthcare organization if it met their needs, and a willingness to pay more for better service.

Clearly early adopters are a highly desirable group. But how do you make them targetable and actionable?

An Attitudinal and Behavioral Targeting Process

To answer that question, a supplementary proprietary national survey with a representative sample of 4,000 US healthcare consumers was fielded.

Step 1: Identify Healthcare Early Adopters Within the Supplementary Survey. In one section of the survey, respondents reported whether they had done or were willing to do a variety of cutting-edge and emerging healthcare behaviors. Early adopters ranked in the top 16 percent in terms of having engaged in or willingness to engage in these behaviors. (Sixteen percent was the size of the early adopter segment in Rogers’ Diffusion of Innovations research referenced above.)

Step 2: Define the Healthcare Early Adopters Based on GfK MRI Survey Variables. Another section of the survey included more than 60 behavioral and attitudinal questions from GfK MRI’s Survey of the American Consumer. This is a national survey of 25,000 consumers that asks about their use of thousands of products and hundreds of brands in dozens of categories. It also asks demographic, lifestyle, and psychographic questions, as well as exhaustive and detailed questions about media usage.

A CHAID ( Chi-square Automatic Interaction Detector) “tree modeling” technique was used to identify those behavioral and attitudinal GfK MRI variables included in the proprietary survey that best predicted membership in the healthcare early adopter cohort and, importantly, to establish that the model performed well in terms of effectiveness and efficiency.

Some of the variables that best predicted healthcare early adoption included behavioral indicators such as a propensity to try new technology products and the most advanced medicines and to seek out information on new drugs. Other predictive variables included attitudinal indicators such as being open-minded and curious. This information adds revealing new dimensions for understanding the early adopter persona.

Step 3: Profile the Persona’s Media Usage. With healthcare early adopters defined, the next step was to uncover the best places to advertise to reach this group. GfK MRI’s extensive media usage information was used for this purpose.

Among other things, healthcare early adopters were found to be heavy Internet users and light prime time TV watchers, as well as heavy consumers of Spanish-language media.

Applying the Research

As healthcare marketers develop research-based personas, it is essential to gather more than descriptive and demographic information to flesh out an understanding of those personas. Behavioral and attitudinal information provides a better understanding of the target audience’s motivations and mindsets, and with that understanding, effective messages and service offerings can be developed.

Gathering information about media consumption is essential as well—the methodology described above is one way to back into detailed media usage information. Putting all of this information together will get you far closer to achieving maximum targeting effectiveness and optimal efficiency.


Susan Perkins is the Market Research Director at BVK. She can be reached at susan.perkins@bvk.com.

Joel English is a Managing Partner in BVK’s healthcare practice, and a principal strategist in BVK’s Brand+Lever brand consultancy. He can be reached at joel.english@bvk.com.

Image by Gerd Altmann from Pixabay

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