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Editorial

Using Performance Max in Google Ads

5 minute read
Pierre DeBois avatar
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Updates to Google Ads feature Performance Max offers marketers a way to enhance their search and digital ad campaigns.

Google Ads has been available to marketers for 22 years — if it were a person, it would be a sophomore in college. Yet changes to Google Ads features over the years has sometimes left marketers feeling as they needed a college degree to understand the feature benefit.

In recent years Google has looked for ways to simplify the campaign workflow so that the benefits from the features were clearer. Its latest update is a goal-based campaign, Performance Max. It aims to simplify the decision-making behind managing campaign assets and reach so that marketers can stay focused on the messaging that sets up a great customer experience.

What Is Performance Max?

Performance Max is a Google Ads feature that streamlines campaign adjustments in all Google advertising channels. With Performance Max marketers can access their Google Ads inventory from a single campaign. Doing so eliminates the need for specialized ads for specific channels, reducing the planning time and organizing the workflow with the ad inventory in mind.

Performance Max ad campaigns are selected in the Google Ads account. Analysts navigate to the marketers, provide the ad copy and its associated headline, logo, image and video assets. Using smart bidding based on the marketer's goal, Google applies machine learning to create a combination of the ad assets into an ad copy. The ad is then served across all the Google main channels: search, display, YouTube, maps, Gmail and discover.

Google rolled Performance Max out of its beta last November, adding Performance Max features to Google Ads Editor. Marketers naturally start a campaign in the editor, then select conversion goals settings. Each setting is meant to refine how Performance Max adjusts the campaign. The settings are meant to account for potential triggers where an ad may have a best chance for gaining a click — where the offer may lead to conversion. For example, there is a location-based setting.

Related Article: How Google Improved Data Blending in Google Data Studio

New Performance Max Settings

Since the emergence from beta, Performance Max has introduced additional settings. The newest four Performance Max settings were just released in July — Data Exclusion, Optimization Score, Seasonality and Explanations. Data Exclusion is a diagnostic indicator, identifying dates in which conversion issues were encountered within Google Ads. This allows the analyst to better address conversion rate accuracy during a critical campaign period. This is especially important if the data is exported for an advanced analytics model because data errors erode predictive models.

Seasonality allows marketers to make atypical adjustments for seasonal campaign bidding (I explain how to consider seasonality marketing in this post). Smart bidding already accounts for seasonal campaigns in its ad campaign settings. But marketers should stay alert to adjust when unusual real-life events may coincide with a seasonal campaign already planned. 

Learning Opportunities

Optimization Score gives an indicator for improvement in ad performance. It is meant to reveal recommendations that lead to better results. The fourth new setting, Explanations, notes fluctuations in campaign performance.

Where Performance Max fits in the Google Scheme of Things

Performance Max is central to operating a smart shopping and local campaign workflow. The Google Ads editor allows for offline and bulk edits to campaign ads, so incorporating the Performance Max campaign feature is a natural application for streamlining campaign tasks.

The introduction of Performance Max also reflects on Google's grand plan to remove third-party cookies from consideration of its marketing ecosystem (although Google did report a delay in its plans to eliminate third-party cookies from the browser). Third-party cookies have been used as influencing mechanisms for linking a customer's view of website content to a customer's view of an ad. The tech industry is moving away from cookies as a digital advertising mechanism, incorporating more systems that rely on machine learning to create real-time insights on digital ad campaigns.

Related Article: How to Use Keyword Density in a Modern SEO Strategy

Quest to Manage Real-Time Conversion Performance

The most important benefit from Performance Max is having transparent controls for centralizing audience access across Google related channels. Google has been working to add transparency to the supporting measurements of Performance Max campaigns. For example, the latest update to GA4 added Performance Max as a dimension. To access it, analysts will need to review the Cross Network channel grouping in the Traffic acquisition report. The addition allows for a clear monitoring of the campaign elements. For example, Performance Max can reveal which creative combinations are making the more impact to performance, allowing teams to optimize campaign creatives to drive campaign ROI.

Marketers need to allow their campaigns time to run. The settings in Performance Max operate with machine learned programmatic in mind. Machine learning models training on an abundance of data to maintain tolerances for a setting. The campaign period acts as the training data, so the number of days become the best ways to training the settings. 

No matter what marketing is planned marketers should consider applying Performance Max to their digital ad campaigns. Doing so will help marketers better manage real-time conversion performance and raise the quality of their marketing strategy.

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About the Author

Pierre DeBois

Pierre DeBois is the founder and CEO of Zimana, an analytics services firm that helps organizations achieve improvements in marketing, website development, and business operations. Zimana has provided analysis services using Google Analytics, R Programming, Python, JavaScript and other technologies where data and metrics abide. Connect with Pierre DeBois:

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