Next Up: Event Targeting In Politics
Candidates for public office love events. Country fairs, town halls, campus visits, and, of course, political conventions. In the old days of...
2 min read
Ray Kingman : November 17, 2016
Healthcare and pharmaceutical marketers will spend nearly $2 billion on digital advertising this year, a 15% increase over 2015 spending. But while these advertisers are ramping up their testing of digital, little has changed in the way they approach the challenge of building a target audience.
Historically, healthcare marketers have built audiences by identifying patients who have a particular disease or ailment. They use a sample to seed a predictive model that scores the relevant population on look-a-like indicators like age, life style, location and ethnicity. It’s a solid methodology used in several markets, but it’s overly simplistic when you consider how much useful, domain-specific healthcare and pharmaceutical data marketers are leaving on the table.
Healthcare and pharmaceutical marketers have the choice of building their target audiences from the provider side or the patient side. The advantage of the provider side is that it adds multiple layers of diagnostic validation data to the targeting process that can’t be replicated with patient side models alone.
Think of it this way: the patient-side digital targeting model is often driven by inferences gained from online indicators like contextually relevant activity, which means we are inferring interest and relevance based on a disease or medical condition based on a drug purchase or discussed on a web page. That action is projected onto other anonymous users who happened to follow similar algorithmic paths in their page views. For all the firepower that goes into generating these intent algorithms, all inference hinges on loose behavioral associations that can’t be validated or repeated.
By contrast, publicly available provider data, also anonymous to comply with privacy laws, is far more deterministic. Doctors and pharmacists know with far greater certainty what drug correlates to which disease and the frequency of a particular disease or condition in a specific area. Applying physician specialties data and treatment procedures to prioritize the distribution of marketing information helps make online outreach more relevant to the population, reduces waste and, in turn, helps to bring down healthcare costs.
Too often healthcare and pharmaceutical marketers have shied away from doing any real targeting either offline or online because of privacy concerns. This is a completely appropriate instinct. HIPAA compliance is very real, and also very concrete about what is sensitive data and how patient identities must be treated.
Patient-side predictive models are built from highly sensitive data, however, they can be compliant if they generalize the patient sample into a cluster of look-a-likes in the form of cookied anonymous targets. Still, cookies are also considered problematic because they claim to be one-to-one with a user or individual, even though there is little chance of tying back any cookie to either a disease or to the person.
The methodology using provider-side data is more privacy sensitive. While the physicians, specialties, diseases and/or pharmaceutical remedies are all real, the data has never been reported or connected to an individual. In fact, nowhere in a provider-side solution is an individual ever identified or targeted. Any outreach the digital advertiser makes is to serve ads on content being consumed by anonymous viewers to a “broadcast segment” of opt-in viewers (like television) that never has less than 250 individuals. A served ad can never be tied to an individual and the minimum population counts meet or exceeds any HIPAA standard.
Provider-side data can ultimately provide a privacy-safe baseline that is both more informed and a more repeatable scheme for prioritizing the outreach of each healthcare campaign.
By bringing definition to audiences in a privacy-sensitive way, provider-side data connects the dots, making it more efficient for digital marketers and other stakeholders. The data can also tell us where more doctors are needed and where specialists would be most useful. It will inform insurers of the macroeconomic trends in providing patient care, and bring greater understanding and efficiency to public health challenges.
The old adage is true: the doctor really does know best. Now, it’s time we shared that knowledge.
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