Programmatic Targeting Series Part 5: Understanding deterministic and probabilistic data

Programmatic Targeting Series Part 5: Understanding deterministic and probabilistic data

2018-09-27T17:36:44+00:00 September 25th, 2018|Healthcare Marketing|

Marketers of all industries are expected to accurately target the right audience, understanding what they want and exactly when they want it. This can seem like a difficult venture with all of the data floating around the world wide web. However, both deterministic and probabilistic data modeling make it easier to back up an online strategy, giving physician and health care marketers the ability to make use of valuable data, optimize claims processing, meet compliance requirements and solve master data quality problems.

As the final staple in our programmatic targeting series, we’ll discuss the difference between deterministic and probabilistic data and how programmatic advertising with HealthLink Dimensions can impact physician and healthcare marketing.

What is deterministic data modeling?
According to AppLift, deterministic data is the analysis of information that is perceived to be accurate on input. Also known as first party data, an example of deterministic information is when a patient signs up for an email subscription, or simply logs in to his or her patient portal and inputs name, address, phone number and other personal contact information. This type of data most commonly relies on the definitive proof of someone’s identity. It’s valuable because it can be determined whether it’s true or false information – if the user inputs such information at one point, the publisher or portal can likely identify this same user the next time he or she uses the site.

Deterministic and probabilistic data are both beneficial for marketers.Deterministic and probabilistic data are both beneficial for marketers.

What is the probabilistic data approach?
Much like the name suggests, the probabilistic data approach relies on the probability that a user is a part of the target audience. Instead of relying on the user to input true data, the information is collected from random data points that the user hits while browsing, which are then compared to deterministic data, as explained by SpotX:

“Probabilistic data modeling identifies users by matching them with a known user who exhibits similar browsing behavior. By aggregating these data points and plugging them into deduplication algorithms, detailed audience profiles can be achieved from incomplete information.”

Programmatic Targeting with HealthLink Dimensions
While deterministic data allows advertisers to quickly find the target audience, physician and healthcare marketers can benefit from probabilistic data when utilizing programmatic advertising. The information collected while users browse the web, such as cookies, GPS locations and more make it easier for the system to identify the user and predict his or her next move. This allows marketers to understand what the consumer – or in this case, the patient – is looking for before he or she even logs in.

With Programmatic Targeting from HealthLink Dimensions, you can refine your intended audience by filtering out specific criteria, such as age range, treatment behavior, hospital affiliation, gender, geographic area and more. With a programmatic advertising strategy, you can better identify your audience and deliver the right message at the right time.

For more information on how programmatic targeting with HealthLink Dimensions can help you reach your healthcare audience, contact us directly today.