30 second summary:
- In the digital marketing space, the discussion of privacy and cookie changes has focused heavily on programmatic and paid social networks
- Here’s what to learn about what search marketers can expect and how to prepare
In the world of digital marketing, targeting, measurement, and optimization essentially relies on the ability to closely track user behavior and performance across the web. However, as we all know, platforms like Google and Apple have introduced privacy-driven initiatives in recent years that make targeting and metering difficult for advertisers.
When discussing the impact of these changes, much of the conversation focused on programmatic and paid social media, which are arguably the digital channels that are having the greatest impact. What has not been discussed in detail is the impact on search engine marketing. How should advertisers adapt their paid search strategies to these new realities?
Before we dive into action items, let’s summarize the latest updates and how they affect paid search campaigns.
Chrome’s privacy updates will have a bigger impact than iOS.
In 2021, two important data protection changes are the top priority for search engine marketing specialists. App Tracking Transparency (ATT), introduced by Apple’s iOS 14.5 update, requires a user to log in before a company can track their data across other apps or websites. Fortunately, for most advertisers, the impact of this update on search engines is limited. Advertisers can see Universal App Campaign (UAC) volume fluctuations, and search properties with a larger app-based audience (e.g. YouTube) will experience some degradation when measured and targeted. By and large, however, the ATT update is more of a problem for programmatic advertisers than search engine marketers.
Google Chrome’s retirement of third-party cookies, rolled out in 2023, will have a bigger impact on paid search. From a targeting perspective, Search Ads Remarketing Lists (RLSA) without data on user behavior in non-Google products are becoming less effective. In the third quarter of 2020, RLSA made up 20 percent of clicks on Google search ads for Merkle advertisers – so this is a significant segment of traffic. In addition, there will be new measurement challenges, especially for companies that rely on proprietary reporting technologies.
While iOS 14.5 is already a reality for advertisers, there is more than a year left to prepare for Google to set third-party cookies. There are several steps search marketers can take now to optimize performance in a more privacy-centric environment.
1. Use first-party data audience solutions for targeting
Effective target group segmentation and targeting will continue to be of vital importance in future searches. Google offers several in-platform options for audiences, such as: B. Ready-to-buy and common target groups who are not dependent on third-party data and can be used by advertisers without limits.
However, there is a greater chance for companies to differentiate themselves by developing a strong audience strategy with Customer Match that uses their own first-party data. Many advertisers already use customer matching to some extent, but the data may not be updated regularly or it may not be segmented in detail. Moving away from third-party cookies is the perfect boost to fine-tuning a first-party data strategy.
First, advertisers should evaluate the quality of their first party data. How comprehensive is the data collected? Are there a lot of duplicate records or is there a reliable, unique record for each customer? All of the slicing and dicing in the world will not help if the data you are working with is fundamentally flawed.
Next, marketers should evaluate ways to meaningfully segment their customer lists – a single “email subscriber list” is no longer enough. Smart segmentation is always important, but it becomes even more important as it will enable Google to tailor similar audiences.
After creating segments, plan to update these audiences frequently. Determine a suitable frequency for updating customer comparison lists and determine who is responsible for them. Currently, this can be done through the Google Ads API or within the Google Ads user interface.
Once you have a foundation for your audience strategy, review your approach quarterly to make sure the segments continue to align with the attributes that are important to your customers and your business. This also creates a natural check-in point to confirm that the lists are being updated as expected and that all traffic is receiving. If necessary, the target audience bid adjustments should be adjusted to reflect current performance.
On the subject of bidding …
2. Try Smart Bidding or convert it to use Google’s proprietary signals
While we as advertisers have less user data available without third-party cookies, Google still has a wealth of information about its users and their behavior on Google’s own websites. With Smart Bidding from Google Ads, advertisers can leverage these audience signals to use machine learning to reach the right person at the right bid. That’s not to say that segmentation isn’t important in smart bidding – it still is. One of the many signals that the bidder will consider is all of the audiences that a particular user belongs to, including the audiences for the customer match.
Advertisers can and should use custom audience segmentation via Google Analytics, Looker or the Google Cloud Platform (Big Query). And they should automate the pushing of defined customer groups for Google marketing activation in order to maximize the business data with Google’s Smart Bidding.
Whatever your advertising goals, there is likely a Google Ads Smart Bidding strategy out there that fits your business needs. For search marketers who are new to Smart Bidding, it would be wise to start testing in early 2022 to iron out any kinks and develop a full Smart Bidding approach before 2023.
3. Familiarize yourself with new reporting methods
We’ve talked a lot about adapting to the changes in targeting, but privacy updates also pose reporting challenges. There will be a measurement gap that advertisers will need to fill. Fortunately, Google Ads offers solutions to fill the gaps with improved and modeled conversions.
Optimized conversions improve the accuracy of reports by using an advertiser’s hashed first party data to link a conversion event to an ad interaction. Advanced conversions are powerful in that they create a one-to-one connection between an impression or a click and a purchase. On the other hand, modeled conversions find their strength in scalability; Google has been using them for several years to report on cross-device conversions. When used in combination, advertisers benefit from the precision when there is a one-to-one relationship, while intelligently estimating conversions in areas where they are not.
As data protection regulations increasingly cloud the reporting waters, the stakes are higher to work with Google to fill the loopholes. If you rely primarily on proprietary technologies for reporting, consider using Google’s metering system for a more complete picture of performance. Understanding the full impact of search is critical to effectively optimizing and allocating budgets. Note that Google’s general website tag or tag manager is required to track conversions accordingly.
4. Monitor universal app campaigns for changes in performance
Advertisers using UAC to drive app downloads through paid search should closely monitor the performance of these campaigns. So far, Merkle has observed a slow downward trend in tracked installations due to Apple’s ATT update. To avoid the impact of ATT, some advertisers are increasing their investment in Android or shifting their spending entirely to it. UAC can still be an effective channel for marketers, but decreased visibility on iOS may require bid or budget shifts to meet performance goals.
Privacy updates are changing the way marketers approach targeting and measurement. Don’t panic – just make a plan. With the right adjustments, search engine advertisers can work effectively with the industry. More than ever, advertisers need to value first-party audiences who are search-driven to increase customer engagement, experience, and marketing ROI. Using this first-party data in conjunction with machine learning-based bid strategies and modeled and enhanced reports will lay the foundation for future-proof search campaigns for privacy updates in the years to come.
Matt Mierzejewski is SVP of Performance Marketing Lab and Search at Merkle Inc.
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