Privacy took a swing at measurement
The world of digital marketing is under scrutiny. For decades marketers, brands and tech vendors have been tracking internet users and their behavior without any form of transparency. Which data was collected and what it was used for was none of the user’s business. All of this is changing. Both governments and private actors are stepping in in order to protect the privacy of internet users. Governmental regulations such as GDPR (EU) and CCPA (California law) are impacting how personal data can or can’t be used. In the private sector we see initiatives such as Intelligent Tracking Prevention (ITP) developed by Webkit and deployed through Safari (Apple). ITP is protecting user privacy by restricting how cookies can be used for tracking.
All of this means that users are more conscious about how their data is being used and that these practices are more regulated than they used to be. But how does that impact the way your data appears in your marketing platforms, and how does this impact your KPI’s?
Here’s why your KPI’s are shifting
As marketers we’ve been using something called deterministic measurement. Deterministic measurement is -- technically -- described as a measurement model where no randomness is involved. Everything that serves as an output was actually measured and used as an input. In the world of marketing deterministic measurement can be explained as simple as taking only the data into account that has actually been measured. And -- as a marketer -- you might understand, this is where it becomes both tricky and interesting.
KPI’s are based on measurement. In order to be allowed to measure, collect and handle data users have to provide consent. Users who do not consent are not being tracked. This impacts deterministic measurement as instead of tracking 100% of the population, we’re now tracking only the part of the population that has opted in. This means that KPI’s will oftentimes be impacted negatively. However, we’re still spending the marketing, communication, media and operational budgets. As a result your KPI’s get impacted. But are they really? It’s the story of a tree falling in the woods but nobody's around, does the tree still make noise when it comes crashing down? Similarly you can ask the question -- If conversions aren’t being measured in the context of consent, does that mean conversions didn’t happen? If conversions can’t be measured, but they’re still happening, do they really impact my KPI’s? Using a deterministic approach requires you to answer -- yes, your KPI’s are shifting. What can’t be measured, can’t be reported. So does this mean all KPI’s are going downhill from here?
Enter probabilistic measurement
Not really. Tech vendors such as Facebook and Google are trying to provide clarity on what’s really going on with your KPI’s. They do this by introducing probabilistic modelling on top of deterministic measurement models. In short -- The vendors try to estimate how much you were not able to measure (using benchmarks, etc) and try to fill the gaps based on the data you were able to capture. They do this by looking at your deterministic data and extrapolate from there. This is where elements such as Google’s Consent Mode come in play. By creating an overview of the proportion of what can’t be measured and what can and by combining this with deep analysis of the measured data a full image can be constructed. The objective here is to help the entire advertising and marketing ecosystem as a whole. Users should have a good experience, marketers should still be able to optimise their campaigns and publishers should be able to have control over their inventory to match the users with the right content. In the end this is what allows the internet to be (at least for the most part) free to users.
A new mindset
All of this requires a new mindset. 20 years ago everything was done on either gut feeling or market research. Today many marketers won’t make a move unless data is 100% accurate and checked 15 times. Tomorrow we’ll have to let go of the obsessive behavior. Three years ago we wrote an article called “My web analytics data is not perfect, and I’m OK with it”. Today that idea needs to become part of the mindset of marketers. You should still strive for qualitative and perfect data, but in the context of measurement you have to be OK to take decisions knowing you don’t know everything. Otherwise you might as well stop your measurement activities all together. This evolution spells interesting times in the world of marketing. Elements such as attribution will need to move from an almost science to a more high level and global analysis form. The industry is changing and tech providers are trying to help marketers out. The real question is -- Can marketers change the way they are at ease with how their data is evolving?