Most marketers are currently shopping for third party measurement technology to meet advertisers’ demand for media transparency. According to a US based CMO study performed by Deloitte, CMOs plan to increase their investment in marketing analytics with a whopping 476%.
The choice of which vendor to work with relies on methodology, technology, output of insights, scalability, usability, price and many other factors. This makes it a complex exercise for marketers to decide which vendors to work with. The purpose of this article is to equip marketers with 10 fundamental requirements for audience verification, so marketers know which questions to ask when exploring the space.
There is a lot to filter through
I have experienced that audience verification was reduced to taking a screenshot of the ad appearing on the page (!). In many cases, I have seen marketers try to verify themselves by applying behavioral modelling techniques to their own cookie sets. Others try to verify against their own unweighted survey data. Others position viewability to be the same as audience verification. Some provide a device graph, de-duplicating identifiers to people. And some provide cookie based behavioral estimate over the demographic profile of people exposed.
If I tried hard enough, I could probably list 50 shades of audience verification. If you don’t know what questions to ask, all of the above might sound compelling, but they will all fail to provide reliable and accurate results.
So, what constitute the fundamentals of audience verification?
Let me try to make it clear that third party audience verification is about 10 core essentials:
1. Measurement must be people centric, not cookie centric. Connecting device IDs and cookies across devices, browsers and apps is fundamental for providing a realistic measurement of people. According to a recent AudienceProject study, people in the UK have access to more than 7 connected devices. So, if you are just counting cookies, you are over-counting.
2. Measurement must include the profile (often demographics) of the people who were exposed to or engaged in the ad creative.
3. Measurement must include the reach percentage achieved in the advertiser’s target group.
4. Measurement must be done against a single source of data. Cooking up a measurement across multiple independent sources of data will pollute the results and prevent you from measuring double coverage across data sets.
5. Measurement must be independent third party. Marking your own homework is not exactly in tune with the spirit of transparency.
6. Measurement must be validated against deterministic data – not probabilistic data.
7. Panels should be carefully weighted to represent the true online population, not the composition of the panel providers’ user-universe.
8. Measurement must provide an affinity score on how effectively the campaign exposed or engaged the target audience in relation to the target group’s incident rate in the online population.
9. The workflow must be smooth and preferably automated, so you avoid drowning your ops team in tedious work.
10. Results must be real time. You can’t take action on insights if you get them after the campaign has finished.
The combination of technological complexity and lack of human ability to tell the differences can lead to poor decisions and a lack of adoption of technological innovations. Recently, Kantar Millward Brown released research showing some 57% of agencies and 52% of advertisers perceive the need for mostly human insight to keep up with emerging advertising technology, and this lack of insight is holding back advertisers from embracing programmatic media buying.
I hope this article enables you to ask the right questions as you explore which audience verification vendor and technology you should work with. If you are interested in hearing more about the topic of media transparency and audience verification, don’t hesitate to reach out.