Over the next 12-15 months, third-party cookies will be removed through digital marketing channels.
Experienced advertisers know they need to start developing a game plan for the future without cookies, but what will happen to those who don’t adapt to these changes?
Above all, marketers will suffer from signal loss, which will negatively affect how we measure campaign performance, optimize campaigns over time, create audiences for ad distribution, and drive growth in our digital channels.
The industrial maritime change with the lion’s share of attention is the withdrawal of third-party cookies in Google Chrome.
Of course, other browsers, including Microsoft Edge, Apple Safari, and Mozilla Firefox, have previously restricted third-party cookies. Chrome is more monumental simply because of its market share.
SimilarWeb recently published a study that showed that Chrome is the most popular browser in the world 62% web traffic.
To sum up from mine previous articleGoogle Chrome will remove third-party tracking cookies around the third quarter of 2023. This is an approximate time frame for this monumental change, but it gives us a goal to ensure that our digital marketing campaigns are ready.
This may sound like the distant future, but many of the measurement solutions needed to replace third-party cookie functionality could require a lot of time and effort from development teams.
This type of support usually requires a few cycles to be prioritized on project plans.
Getting started in the next few months will be beneficial in the long run.
Look at it this way: your future self will be grateful for your thoughtfulness and proactivity!
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What happens when marketers don’t build new measurement frameworks?
Marketers have been using third-party cookies to monitor their media performance for more than two decades. This method is not perfect, but it was a standard practice that is expected to evolve strongly over the next 12-15 months.
From a digital marketing perspective, one of the most important impacts is the loss of conversion measurement. This loss of performance data includes sales, declarations, purchases, revenue, and other business measurements, as these actions are likely to be limited.
If marketers do not develop their own measurement practices, their accounts will rely on algorithmically driven modeled conversions.
Successfully enabling automation within PPC is key to achieving positive results.
One of the most powerful algorithmic elements is smart bidding. Algorithms that promote cost-per-acquisition (CPA) bids and return on investment in advertising (ROAS) need strong data signals to optimize performance.
The data that stores these algorithms must be reliable so that accounts are optimized for the most valuable actions, and this conversion data must be large enough to promote machine learning.
Data loss means that bid algorithms will not work properly, resulting in reduced PPC efficiency. Let’s try to avoid this!
Multiple conversions will be algorithmically modeled as a result of signal loss
For advertising platforms like Google and Microsoft, there is too much at stake (i.e. money) to leave marketers with no other option to recover lost data.
When marketers create new measurement frameworks through enhanced conversions (EC), Google Analytics 4, or offline conversion tracking, these are taken into account. Observed conversions.
This mix of first-person and user-matched (EC) data is created through registered actions performed by visitors to our site.
Try to collect as much of your observed conversion data as possible.
There is an alternative Modeled conversions in Google and Smart Goals in Microsoft Ads. According to Google, modeling conversions are:
“When Google shows simulated conversions in Google Ads, we anticipate attributed conversions. In most cases, Google will receive interactions with ads and online conversions, but it lacks a link between the two. The modeling we do is modeling whether the interaction with the Google ad led to an online conversion, not whether or not the conversion occurred. ”
Even after these extensive privacy changes, Google will continue to gain mountains of data per user: search history, browsing history, and any other online activity when someone is signed in to their Google Account, especially if users are logged in to Google.
Google will not be able to install tracking pixels specifically for this user, but it should have enough data to algorithmically predict which media interactions are leading to conversion for the advertiser.
Microsoft Ads is working on a version of the conversion model. This product is called Smart goals.
According to Microsoft:
“Smart Goals uses Microsoft Advertising machine learning models to identify the best sessions on your site. If you have the UET tag set correctly, the smart target will review all the sessions on your site to determine which of these sessions can be considered “conversions.” Smart targets use multiple signals to identify conversions. Some of the signals used include session duration, pages per session, location, device, and browser. ”
They’re basically similar to Google’s modeled conversions. Both rely on machine learning to a large extent to understand user behavior and possible reactions to paid media exposure.
Marketers need to provide a number of additional signals to keep all modeled conversions as accurate as possible.
With the loss of user-level data, the modeled conversions will be part of the measurement landscape in 2023.
This brings us back to creating a strong framework for providing as much data as possible about the observed conversions within the platforms, which will help inform the simulated conversion algorithms.
Marketers have the time and tactics to design new measurement frameworks
The possibility of restoring your measurement framework may seem daunting, but you have the next few quarters of time to figure out which solutions are best for you and your business.
Now is the time to start evaluating your current processes, review the new measurement tactics currently available, and start building a plan.
In my last article, we laid the groundwork for what this metamorphosis means for the digital marketing landscape and approx when it has to happen. This article was discussed why adapting to these changes must be a strategic priority.
Next time, we can start making a plan how you can build a measurement framework and a target audience focused on privacy for 2023.
The opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Personnel authors are listed here.
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