When approaching healthcare advertising, there are many considerations an advertiser must navigate regarding data cleanliness and privacy. Advertisers face strict guidelines when targeting potential and current patients. The future is becoming more consumer privacy-focused as we march toward advertising in a cookieless world. At Dstillery, we find these changes exciting and fundamental to our core values as thinkers. So we approached the creation of our healthcare targeting solution, Custom Patient Targeting, with the current and future state of ad targeting in mind.
Custom Patient Targeting is fundamentally a product that satisfies two needs in the healthcare space – consumer privacy and intuitive, cookieless targeting that is based in AI learning, not contextual or behavioral targeting methods. Let’s dive into how Custom Patient Targeting utilizes data and how we build seed sets for clients that help them meet and exceed their campaign goals.
Dstillery’s Privacy-Forward Data
When building Custom Patient Targeting, we focused on perfecting what we knew to be a meaningful industry-standard – data privacy. After vetting various partners, Dstillery exclusively partnered with PurpleLab, a leading real-world data (RWD) provider in the healthcare industry. PurpleLab has access to 40 billion medical and pharmacy claims capturing 350m+ patient lives and 98% of payer data. PurpleLab’s sources for claims data are derived from a network of 11 “Open Claims” sources. These are organizations involved in the generation, transmission, or processing of medical and pharmacy claims from providers to insurers.
Dstillery has found that using search data from our opted-in panel has been truly predictive of patient definition. Using anonymous patients searching for specific drug names, symptoms, and co-morbidities in the largest search engines as seeds have been proven to provide strong performance. Combining this data with ICD-10 codes provides the most accurate definition of a patient for a majority of our customers. In parallel, we identify the anonymous devices that have searched for desired search terms and extract the top targeting features from the Search-only model. As a final step, we combine the best targeting feature from both models to create a single model.
A New Era of Healthcare Advertising & Targeting
The result is a privacy-safe, waste-reducing, cookieless healthcare targeting solution that can scale and transform to adapt to any campaign KPI. This blended data for your model ranks high in AQ, or audience quality, a key measurement in the healthcare targeting space. Dstillery uses the best possible data to guarantee the best possible results. Custom Patient Targeting is a breakthrough method for healthcare brands to reach the right patients. It provides a level of precision targeting that is unheard of in the industry, reducing campaign waste drastically. If you’re thinking about using Custom Patient Targeting, don’t think — do.
Thanks to our unique approach that allows us to be more precise compared to modeled condition segments, Custom Patient Targeting is more effective at finding net new patients at a lower cost of media than all other healthcare targeting products today.