30 second summary:
- Within the digital marketing space, the conversation about privacy and cookie changes has focused heavily on programmatic and paid social
- But how will the deprecation of third-party cookies and new privacy regulations affect paid search?
- Here’s what search marketers can expect and how to prepare
In the world of digital marketing, targeting, measurement and optimization are fundamentally based on the ability to accurately track user behavior and performance on the web. However, as we all know, in recent years platforms like Google and Apple have introduced privacy-centric initiatives that complicate targeting and measurement for advertisers.
When discussing the impacts of these changes, much of the conversation has focused on programmatic and paid social networks, which are undoubtedly the digital channels that suffer the greatest impact. What has not been discussed in great detail is the impact on search marketing. How should advertisers adapt their paid search strategies to accommodate these new realities?
Before we look at the actions, let’s recap the most recent updates and their impact on paid search campaigns.
Chrome’s privacy updates will have a bigger impact than iOS
There are two key privacy changes that are important for search marketers in 2021. App Tracking Transparency (ATT), introduced via Apple’s iOS 14.5 update, requires a user to have a consent before a company can keep track your data on other apps or websites. Fortunately, the impact of this update on search programs for most advertisers is limited. Advertisers may notice fluctuations in the volume of Universal App Campaigns (UAC), and search properties with a larger app-based audience (e.g. YouTube) will suffer a decline in measurement and targeting. In general, however, the ATT update is more of an issue for programmatic advertisers than for search marketers.
Google Chrome’s deprecation of third-party cookies, scheduled for 2023, will have a greater impact on paid search. From a targeting perspective, remarketing lists for search ads (RLSAs) will become less effective without data on user behavior on non-Google properties. As of Q3 2020, RLSAs accounted for 20% of Google search ad clicks for Merkle advertisers, so this is a significant traffic segment. There will also be new measurement challenges, particularly 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’s withdrawal of third-party cookies. There are several steps search marketers can take now to optimize performance in a more privacy-centric environment.
1. Rely on proprietary solutions for the data audience to reach
Effective audience segmentation and targeting will continue to be key in research going forward. Google offers several options for in-platform audiences, such as in-market and affinity audiences, which do not rely on third-party data and can be leveraged by advertisers indefinitely.
However, there is a greater opportunity for organizations to differentiate themselves by building a solid audience strategy using their proprietary data with Customer Match. Many advertisers already use Customer Match to some extent, but the data may not be updated regularly or may not be segmented in detail. The transition from third-party cookies is the perfect impetus to fine-tune a first-party data strategy.
First, advertisers should evaluate the quality of their proprietary data. How complete is the data collected? Are there many duplicate records or is there a reliable unique record for each customer? All the slicing and dicing of the world won’t be useful if the data you’re working with is fundamentally flawed.
Next, marketers should consider opportunities to segment their customer lists in meaningful ways – a single “email subscriber list” won’t cut it anymore. Smart segmentation is always important, but it will become even more critical as it will allow Google to create similar, more personalized audiences.
Once the segments have been established, there must be a plan to frequently update those audiences. Determine an appropriate cadence for updating customer mailing lists and determine who is responsible for doing so. Currently, this can be done via the Google Ads API or within the Google Ads interface.
Once you’ve laid the groundwork for your audience strategy, review your approach quarterly to make sure segments continue to align with attributes that are important to your customers and your business. This also creates a natural check-in point to confirm that the lists are updated as expected and that they are all receiving traffic. If necessary, the public bid modifiers should be adjusted to reflect current performance.
On the subject of offers …
2. Try or switch to Smart Bidding to take advantage of Google’s proprietary signals
Even though we, as advertisers, will have less user data available to us without third-party cookies, Google will continue to have a great deal of information about its users and their behavior on Google-owned properties. Google Ads Smart Bidding allows advertisers to leverage these audience cues to reach the right person at the right offer with machine learning. That’s not to say segmentation isn’t important with Smart Bidding, it still is. One of the many signals that the bidder looks at is all of the audience a particular user belongs to, including the customer’s matching audience.
Advertisers can and should leverage custom audience segmentations via Google Analytics, Looker, or Google Cloud Platform (Big Query). And they should automate the push of a defined customer audience to Google marketing activation to maximize business data with Google’s Smart Bidding.
Whatever your advertising goals, chances are there is a Google Ads Smart Bidding strategy that fits your business needs. For search marketers not yet using Smart Bidding, it would be smart to start testing in early 2022 to iron out any nodes and have a full Smart Bidding approach before 2023.
3. Get familiar with new reporting methods
We’ve talked a lot about adapting to upcoming changes with targeting, but privacy updates also create reporting challenges. There will be a measurement gap that advertisers will need to close. Fortunately, Google Ads has solutions to help fill in the gaps with advanced and modeled conversions.
Advanced conversions improve reporting accuracy by using hashed proprietary data from an advertiser to link a conversion event to an ad interaction. Advanced conversions are powerful as they create a one-to-one connection between an impression or click and a purchase. Modeled conversions, on the other hand, find their power in scalability; Google has been using them for several years to generate cross-device conversion reports. When used in combination, advertisers gain the benefit of accuracy where a one-to-one connection exists, intelligently estimating conversions in areas where it doesn’t.
As privacy regulations increasingly muddle the waters of relationships, the stakes are higher to work with Google to fill the gaps. If you rely primarily on proprietary reporting technology, consider using Google’s metering system to get a more complete picture of performance. Understanding the full impact of research is critical to being able to optimize and allocate budgets effectively. Please note that the global site tag or Google tag manager is required to properly track conversions.
4. Monitor Universal App Campaigns for performance changes
Advertisers using UAC to incentivize app downloads via paid search should closely monitor the performance of those campaigns. So far, Merkle has observed a slow downward trend in monitored installs following Apple’s ATT update. To avoid the effects of ATT, some advertisers are increasing their investments in Android or shifting their spending entirely. UAC can continue to be an effective channel for marketers, but reduced visibility on iOS may require offering or budget changes to meet performance goals.
Privacy updates are changing the way marketers approach targeting and measurement. Don’t panic, but put a plan in place. With the right adjustments, search advertisers can effectively rotate along with the industry. More than ever, advertisers need to value search-driven proprietary audiences to increase customer engagement, experiences and marketing ROI. Using this proprietary data, along with machine learning-based bidding strategies and modeled and improved reporting, will create a foundation for helping future privacy update-proof research campaigns for years to come.
Matt Mierzejewski is SVP of Performance Marketing Lab and Search at Merkle Inc.
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