As we are witnessing the end of the Era of Third Party Cookies and Mobile Advertising IDs, we can take a look at the new scenarios. They are not yet fully defined, but they surely stand for an epochal revolution for Advertising and Digital Marketing.
Speaking of targeting, the situation is not very clear, but on the performance measurement side we begin to glimpse the common intent that unites the various vendors with their different proposals.
In fact, what will replace the former digital marketing measurement system? How can marketing strategies be optimized in the future?
Let’s first sort out the fundamental concepts in order to better understand the scenario.
First Party Data is all the data a company ows: from information on online user behavior to the location of the physical stores of that brand, from product production times to paid campaign performance by Advertising.
While First Party Data belongs to the marketer, Third Party Data is the information collected and sold by third-party platforms. For example, Google Ads and Facebook Ads have up to now supported the measurement capabilities of companies through Third Party Cookies.
A Third Party Cookie is a small text file on the user’s browser, saved in a different domain than the one the user is browsing at that moment. For example, while browsing the biteky.ai site, Google saves a unique identifier through its pixel, which allows the user to be recognized on the google.com domain. With this simple trick, Google – but also Facebook, Criteo, Microsoft, LinkedIn with their domains – can follow users’ activities and above all measure the performance of advertising campaigns, thanks to the data they collect.
But Third Party Cookies are soon to disappear: Google Chrome will in fact be the last browser to dismiss them; while on Safari, Firefox and Edge they are already no longer supported.
Advertising platforms are hijacking the performance measurement infrastructure towards First Party Cookies, according to the browsers’ block for Third Party Cookies. In this way they continue to measure what happens after the click on the Adv, even though they are still facing difficulties in measuring post impression conversions.
Moreover Apple, in response to these tracking tactics adopted by the Adtech world, has introduced limitations to First Party Cookies as well:
- all First Party Cookies last a maximum of 7 days.
- if the url contains a parameter that identifies the click of a single user (for example in the case of Google Click Identifier) the associated cookie will last only 24 hours.
Therefore, the ability to track the performance of advertising campaigns is definitely compromised on this browser.
For Native Apps on smartphones, the problem lies in the Mobile Advertising IDs (MAIDs), that are available only if the user decides to share them, which in fact drastically reduces the effectiveness of the campaign tracking system for native smartphone apps.
To make up for the ban of Third Party Cookies and MAIDs, Adech platforms have introduced Alternative User IDentifiers, but these are not privacy oriented solutions, since they still follow the user like Third Party Cookies, and they are definitely less precise and effective. In fact, they are based either on the user’s personal data (such as email or telephone number) or on other signals collected by the user’s browser or operating system.
New privacy-oriented tracking ways
Obviously, Digital Advertising needs to rely on a safe and effective measurement methodology, without compromising on user privacy.
To date, thanks to a convergence of technological choices by the Big Tech Companies, the measurement of campaign performances shifts from tracking the individual user to sending aggregate data to Adtech platforms.
Apple launched the first technology of this type with SKAdNetwork and Private Click Measurement, which have been available on the market for almost three years, and they will soon reach the fourth release with the new iOS expected in September.
Google has followed with its Attribution API, embracing Apple’s philosophy and expanding its capacity with new functions, so useful that Apple added them to SKAdNetwork 4.0, debuting during the WWDC in June 2022.
How to continue advertising while respecting privacy?
In a world where privacy is gaining more and more ground as an essential value for users, measurement methodologies must necessarily change in order to survive.
As seen before, there are valid proposals (and some ready-to-use technologies) that can inaugurate a new way of measuring performance.
Of course the old Digital Advertising tools are still available, platforms such Google Ads, on which we have relied so far, but they will soon face tracking limitations dictated by both technological choices and privacy regulations.
In the meantime, all vendors are working to support their measurement methodologies with First Party Data.
What does all this mean for advertisers? The platforms will keep evolving, but we will not stop advertising and we will not stop measuring performance: we will have new different methods, and they shouldn’t be less effective.
We will have to learn new ways of working and adapt to a world that changes in a blink of an eye.
In such a heterogeneous environment, it becomes crucial for the advertiser to be able to combine data coming from the various platforms: this is great potential for the “new” hybrid methodologies, such as the Marketing Mix Models.
These technologies analyze the performance of all online and offline promotional activities, using safe data compliant with the user’s privacy, such as clicks, impressions, GRP, investment and revenue; and through statistical methods they provide a detailed view of how the different marketing actions contribute to the expected result.
In this brief and non-exhaustive overview, we have listed many new solutions: we do not lack alternative proposals, even though we still don’t know which ones will be established in the future.
Basically, it is not enough to collect First Party Data, but it is necessary to know how to interpret and activate them for very specific purposes. However, the collection is key: the more accurate and relevant the data, the more personalized and effective the following marketing actions will be.
Thanks to the application of Artificial Intelligence, every company will be able to predict the behavior of its audience, obtaining essential information on the customer journey. For example, they will understand in advance which customers are worth investing in because they are likely to make a purchase, or the churn rate on a specific product or service.
To turn a company into a Data Driven company, first of all you need to aligned the necessary information with the business objectives, combining data of different kinds: structured and unstructured, internal and external, traditional and alternative.
This is the role of Artificial Intelligence models, the true protagonists of the Next Advertising Era.
