Google Ads AI-powered Performance Certification

Avoid linking a Google My Business or Google Merchant Center feed 

Use the maximum number of text, image, and video assets possible 

Limit the number of ad extensions within an asset group 

Establish conversion tracking after a campaign has been running for two weeks 

Diagnostic insights

Keyword planner

Target simulators

Ad strength rating 

It lets leaders spot low performers more easily.

It fosters competition across the organization. 

It encourages teams to break down silos and identify solutions quickly. 

It helps teams test more than one business objective at the same time. 

They let marketers identify additional searches that customers might be using to locate a business.

They make it harder for customers to leave negative reviews about a business. 

They allow marketers to limit the terms that competitors are able to bid on at auction, 

They prohibit otherwise qualifying queries from triggering ads for an irrelevant search 

Add more phrase and exact match keywords to improve reach. 

Eliminate negative keywords that could block relevant traffic. 

Ignore suggestions to add relevant new keywords. 

Add Customer Match lists with data that is more than 90 days old 

With fixed annual budgets that don’t adjust according to demand

With quarterly budgets that don’t need prior approval to be increased

With budgets that aren’t set for a time period or initiative 

With budgets that adjust to the price of stock 

Maximize clicks

Target ROAS

Maximize conversions 

Target Impression Share 

Create a new CPA or ROAS goal for Performance Max campaigns to achieve.

Keep Performance Max budget limited to 10% of other campaigns’ budgets. 

Optimize Performance Max to a comparable CPA or ROAS target to other campaigns. 

Run the Performance Max experiment for one to two weeks before evaluating results. 

By testing multiple variables at a time, an A/B test gives advertisers information they can use to adjust their campaigns quickly based on insights. 

By revealing whether their trial campaign drove user action that wouldn’t have taken place otherwise, an A/B test gives insights into user behavior. 

By running a single campaign at a time, an A/B test allows for a true ramp-down period between each testing period so that results can be decluttered. 

By running concurrently with an original campaign, a trial campaign controls for external factors, like seasonality, that might otherwise bias results. 

Is there a way our data collection policies can be modified to encourage customers to share as much as possible? 

What are the data storage capabilities for each marketing team member’s organizational device? 

How can we start to use this data as quickly as we can, even at the expense of alignment with other teams? 

Are we aligned with local regulations on data collection and user privacy to ensure we are properly using first-party data?