What is affecting attribution tracking and what are the options available in a cookie-less world? Andy Houston, Group Operations Director shares his views on the impact of the current environment on attribution tracking, and three options that brands can take.
In our previous article on understanding marketing attribution 101, we looked into the importance, challenge and future of attribution. Here, we dive deeper into the impact of what’s happening around us today on attribution tracking.
In addition to the tech giants that have built up walled gardens that made cross-channel attribution more challenging, there are three other drivers:
- Different behaviours of browsers when it comes to their approach to privacy and tracking mechanisms
- Ongoing legislation changes, primarily in Europe but also starting to appear in the US and across Asia
- Changing user sentiment tarring many things that might not be related nor intrusive with the same brush
Quantifying the impact on a third-party cookie-based solution
To find out the extent of the impact of the current environment, we analysed a solution based on a cookie ID against a Hybrid Attribution solution and its impact in each browser and device type. The analysis was done in the UK where iPhone and Safari penetration (with the abundance of iPhone) is high on mobile, while Chrome has a higher penetration on desktop.
The results clearly demonstrate the challenges of a third-party cookie attribution system versus a potential hybrid approach.
Here’s attribution based just on third party cookie IDs tracked:
The impact of this on the device was felt:
We also compared this against Google Campaign Manager and it seems that even Google is struggling to achieve any attribution on Safari.
Whilst Apple has certainly decided on the privacy that is best for its users, it has also made it very difficult for aggregated attribution to happen on its browser, regardless of personal or non-personal information.
So, third-party targeting and attribution is no longer available in Safari. For regions where iPhone dominates, marketeers are flying blind in the fastest growing area of advertising revenue and customer engagement – the mobile. Even then, given Chrome has the largest share of the total browser market across all devices, the second (Safari) and third (Firefox) largest browsers don’t allow third party cookies at all.
It is clear then that other options need to be sought.
Option A: Moving from third-party cookies to first-party world
Facebook, Alphabet and Microsoft all released a first party tracker soon after Apple’s initial release of ITP.
The different treatment of first party and third party cookies is not insignificant. Both browsers and legislation recognise some instances of this type of cookie to be more essential in the effective operation of a website. As a result, they don’t immediately block or delete it. Even Safari, with the latest release of ITP 2.1 allowed them to exist on the browser for seven days.
But, while first party cookies might be helpful for tracking activity on a single domain, they become less useful when trying to attribute customer engagements to conversions across multiple touchpoints on multiple domains.
Without the different activities being linked to a specific browser holistically, as the ‘golden bullet’ for attribution it is limited as it really only can work for one channel (i.e. Facebook) and one domain (i.e. a brand using Facebook). Combine this challenge with Apple’s ITP 2.2, which now shortens first party cookie lifetime down to a rolling 24 hours, in itself it cannot support proper lifecycle attribution.
Option B: Moving from deterministic attribution to probabilistic attribution
In the absence of matching pseudonymous IDs in a deterministic way, with the advent of more sophisticated machine learning capabilities and to a lesser extent AI in the current environment (maybe more in the future), it has become easier to read and interpret signals that could imply statistically significant links between several events or scenarios.
With the average number of internet connected devices reaching an all-time high at 3.5 per household, much has been done in the use of probabilistic matching in an attempt to understand cross-device engagements by a single customer across their multitude of devices.
Historical data is critical in the process to develop machine learning, and for AI to identify trends and scenarios that can be linked together. The main challenge around this is volume. To be able to set probabilistic matching off in an algorithm, a lot of data is needed.
Much of probabilistic matching for attribution is based on leveraging multiple data points in the different browsers to triangulate to a specific browser.
Option C: Hybrid attribution approach
Hybrid attribution is a combination of both probabilistic and deterministic data signals that helps brands to achieve (1) relevant targeting for better performance and (2) determine accurate marketing attribution against all browsers, devices and channels.
About the author
Andy Houstoun has over 20 years of experience in delivering successful digital propositions, most recently as CCO of Larsson & Jennings, the Swiss Made Watch brand.
At Venda, the world’s largest on-demand e-Commerce provider which was bought by Oracle in 2016, he launched and optimised online propositions for clients including Jimmy Choo, TK Maxx and Urban Outfitters. Prior to this he was part of the founding team of Tesco.com.
As Product Director at Crimtan Andy oversees the product go-to market strategy with a core objective to deliver value and retention across our client base.
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