By: Kevin Elwell
Without a strong digital signal to measure success, pharma brands often need to trust that ad impressions are going to the right audiences. When working with a fast food restaurant, an agency can measure app downloads and compare that to impression data. For pharmaceutical and medical device products the conversion rate is longer, the data is more sensitive, and third-party verification is more important.
As the Vice President of Client Success at Swoop, I work directly with brands to create audience segments. Our goal is to connect the right people to the right messages and to ultimately improve healthcare outcomes. As more AdTech companies offer to create segments and measure campaign performance in house, I’ve seen the impact of not including relevant data sources. While it may seem more convenient to have one vendor create, manage, and measure outcomes, this approach can lead to a conflict of interest, missed data points, and an overestimation of performance.
If you’re taking the test and writing the answer key, all you’re saying is “I agree, I did a good job.” The risk of trusting the data source for measurement comes from missed opportunities, wasted marketing spend, and overestimating ad performance. Using a third party to verify that the data is strong, audience segments were built correctly, and impressions are reaching the right audience prevents pharma brands from leaving impressions and potential script lift on the table.
In this blog, you will learn why there are discrepancies between data sources, how to encourage accountability in measurement, and how to test audience targeting more accurately.
Measurement companies can build solid audience segments, and audience segmentation companies can measure performance. But, as we’ve established, when you’re grading your own homework, the rubric can miss key information because it's inherently biased. Without malice, a company will always be better at measuring its own outputs.
Trust in a measurement platform is everything in our industry because this data drives important decisions that could impact health outcomes. Established measurement companies have put a lot of effort into their measurement product and building trust through transparency. Issues arise when newcomers with great tolerance for risk to accelerate growth and drive investment rounds launch products that don’t match the measurement standards of incumbents. Marketers should always pay attention to numbers that don’t agree, and ask questions about measurement methodologies.
It’s not inherently a bad thing when data partners have different match rates. Every company uses different data sets and different match methodologies. But it is a mistake to not use a third party to verify the data is trustworthy and measuring what a brand intends to measure. Missing data sources could lead to reduced reach and potentially leave impressions and script lift on the table. Measurement data from third parties teaches us how to structure future segments, can provide guidance for structuring creative, and provide options for future campaigns.
Healthcare data is obfuscated. There will never be the same transparency in healthcare as there is in other categories because healthcare information is sensitive. Not only does healthcare exist vastly offline, but it also involves the most regulated data in online spaces. Advertisers need to understand the limitations of measurement options when working with healthcare’s limited real-world data, but still hold AdTech partners accountable.
The first step in building accountability with your partners is insisting on knowing what’s going on under the hood. Companies will always maintain some secrecy to their methodologies, but there should be transparency when it comes to what is being measured, and what kind of expansion and mapping is going on within that measurement.
For example, not every impression can be matched back to health data. It’s just how online to offline, real-world data mapping works. Understanding how much projection is in a measurement is crucial. Is the data you’re seeing representing five people out of a segment of thousands? That can drastically skew the implied performance of the segment overall.
Do you know what ID space your measurement partner uses to navigate between media exposure and health data? Different ID spaces are going to disagree, and it is important to understand which ones your partners use and how they use them.
With data we can trust, we can build and test targeting methodologies. But if a brand’s strategy can’t be measured accurately, then the results of the best idea in the world won’t look good on paper. That’s why it is so important to make sure your campaign goal aligns with what you are able to measure.
The test, learn, and iterate methodology only works when we can accurately run tests. From targeting parameters to messaging specific populations, understanding the granular level of data is where the magic happens.
We can build a lot of cool targeting parameter segments of specific classes of patients. But sometimes when brands go outside of the box in granular targeting and test new ideas, teams will forget to measure those new ideas separately. For example, a segment that uses simple targeting with a large audience that’s proven to perform shouldn’t be measured in one lump with a test of a smaller, more nuanced segment. The results of the test are hidden and the team can’t learn anything about this new audience when the measurement side of the equation isn’t set up correctly.
When experimenting with new targeting, it's important to control all testing variables, including measurement, and understand that it can take months before you can see the true outcome of a new audience in the healthcare sector.
More than any other category, healthcare marketing requires validated, transparent, and trusted measurement of campaign results. Brands should be able to rely on measurement partners to paint a clear, accurate picture of how ads are reaching and engaging the patients and caregivers that need the latest treatment information. When AdTech companies try to grade their own segment performance, they may be missing important data without even realizing it.
This inaccurate reporting could lead to wasted marketing spend, missed opportunities for connecting with patients and providers, and reduce the trust brands have in their partners. Pharma brands need clear messaging and communication from all measurement providers, whether its first-party or third-party data. It has to be clear which key indicators are used to determine if an ad reached the right person on the right platform and what is the source of truth.
With transparent, accurate measurement brands and AdTech partners can innovate together, drive better health outcomes, and improve campaign performance across all channels.