Here are a few myths we hear most often when we talk to pharma marketers about consumer targeting:
I’m already doing it.
Well, yes, but “it” has generally been limited to search terms and contextual or endemic placements to deliver targeted impressions. While extremely targeted, these deliver finite limited volume, which media buyers have had to supplement with larger spends in broader reach media to achieve brands’ volume goals.
Yes and no. It’s expensive on a per consumer reached basis, but far cheaper when you follow that consumer across the conversion funnel through to a patient retained. Better targeting places your message in front of the most likely-to-convert patients, improving media efficiency and consumer response, and driving up marketing ROI.
There are consumer privacy issues.
Yes, there are consumer privacy issues when we target a consumer based on a derivation of their health status from their individual behaviors. But newer targeting techniques are giving us ways to do this in aggregate, and we as an industry stand to benefit greatly.
The Imperative For Consumer Targeting: Getting Even More Urgent
I have an appeal to the industry. We need to get smarter and our regulatory bodies need to get more comfortable with using targeting techniques to pinpoint where we should focus our marketing efforts and whom we need to engage to maximally benefit both the brand and the patient.
Why? Three reasons.
1. Specialized Drugs: Newer drug approvals are increasingly concentrated in specialty categories for smaller targeted populations. Of the new drugs approved over the past two years, 75% are only indicated for small populations. This is driving sizeable increases in demand for patient targeting across both the marketing and media fields.
2. Patient Outcomes: The new healthcare environment is all about patient outcomes. As patient outcomes become the new metric across the healthcare ecosystem, the basis for pharma reimbursement will shift from volume to value. Pharma marketers are going to have to move their focus from driving awareness and generating new scrips to producing positive clinical results. In this paradigm, DTC marketing will have to become more targeted, to find only those patients in the brand’s target profile who are likely to succeed clinically on drug.
3. Patient Service: Consumers get more value from products, messages and other offers targeted to their needs. As they receive tailored services from other industries, it is fast becoming the norm they expect, even for healthcare services. Many in the healthcare industry, however, believe that people don’t want to use digital services for healthcare due to the sensitive nature of medical care. A recent McKinsey article, “Healthcare’s Digital Future,” published in July 2014 (authored by Stefan Biesdorf and Florian Niedermann), dispels that myth. Their survey revealed that 75% of respondents to their survey—conducted across several countries—would like to use digital healthcare services. The issue isn’t that they don’t want targeted digital health content and services, it’s that the services available today don’t meet their needs or provide the level of quality they expect. Let’s change that.
Three Consumer Targeting Techniques We Should Become Familiar With
Most of the other industries that consumers interact with—automotive, credit cards, even drugstores—have started taking advantage of the growth in data sets, computing speed and analytics sophistication to be more targeted in their consumer outreach and more directed with consumer messaging, offers and engagement, at unprecedented levels of scale. It is time for us as an industry to do the same.
In addition to explicit targeting, where a user openly provides information about him/herself for a specified marketing-related use, three targeting techniques have proven successful in other industries and hold promise for healthcare.
Geo-demographic Targeting: Large consumer data companies such as Experian and Neustar aggregate geo-demographic data from sources such as the census, surveys, phone records, credit scores, subscriptions and DMV data on a large volume of the population. They package this data into well-developed publicly-available segments like “Elite Suburbs,” “Pools and Patios,” or “Kids and Cul-de-Sacs,” which marketers can use to either direct how they buy media, or to segment the consumer prospects they already have.
While demographics alone are insufficient to predict medical decisions or behaviors, we’ve seen its power in broad categories like pregnancy tests, cord blood banking, wound care and contact lenses.
Action-Based Targeting: Action-based targeting uses a person’s activity history in and across specific channels (e.g., browsing history) to divine future actions. On the web, site publishers track things like pages consumers visit, time they view each page, links they click on, and searches they make to create profiles on these consumers to better serve them with more targeted messages. Companies such as AudienceScience and BlueKai do this on a large scale, tracking audiences all over the Internet to classify them based on their browsing behavior. Additionally, the combination of action-based data across consumer touch points (e.g., call center, mobile, etc.) provides more holistic insight on actual consumer interest and can significantly inform and drive more targeted future marketing engagement relative to product, education and offer.
Even the simplest form of action-based targeting (i.e., based on browsing history) has historically been a minefield for pharma marketing because of patient privacy issues. No patient wants to be typed as having, say, heart disease, just because she read about anti-platelet therapy. However, we’re starting to see the reins loosen. Even some of the largest pharmaceutical companies are starting to explore this method of targeting, likely because of an increased need to better aim their media and message.
Transaction Targeting: This approach segments and targets consumers based on their purchases or other trackable transactions. Think about Catalina data, which consolidates consumers’ shopping data so that marketers can selectively promote to only those consumers who demonstrate behaviors that make them a high-value target for your brand. In addition to being available for direct promotions, Catalina is now able to package this data for digital media buying as well.
While proven in the CPG world, this approach is only relevant in pharma when there is a proven correlation between trackable past purchases and the probability that a consumer has the condition you treat (e.g., glucosamine purchases may indicate that the consumer may be a target for knee replacement).
The transaction data more relevant to pharma includes prescription, co-pay card redemption and other medical claims data. However, this information is only ever available for use in de-identified and aggregate form. Although we currently leverage this data in match-back studies for after-the-fact market research (i.e., what percent of patients got on brand Z?), it can never be used to profile or target a consumer directly (i.e., this patient made transaction Y so they are a good target for brand Z).
Two Emerging Techniques With Particular Value To Pharma
Propensity Modeling: I’m most invigorated by some of the novel work happening in predictive modeling. We’re starting to combine anonymized data from the targeting data sources described above (demographic, online activity and transaction) to create propensity models which we can use to better find and match specific health conscious consumers with the right health brands, messages and offers. While we would never disqualify a consumer from receiving health information, we can now use such predictive models to calibrate spending, customize messaging and deliver the right level of information per the propensity score. Read more about propensity modeling in a recent blog post at MediaPost.
Point of Care Targeting: An area I’m cautiously curious about is point-of-care. With EHR adoption increasing, a whole host of diagnosis code level targeting opens up, with the benefit of point-of-care clinical supervision. While we already see signs of this revolutionizing the doctor-patient relationship, a lot more work needs to be done to understand the role pharma or other third parties can play in delivering targeted patient value to improve patient outcomes. We’re only beginning to explore this avenue.
In closing, remember: Consumers want more targeted outreach, pharma needs it, and the technology and the smarts exist to enable it to happen—for the first time without the tradeoffs of price, volume and patient privacy. Keep alert as it unfolds.