Google Ads has become increasingly automated and driven by artificial intelligence in recent years. This automation has simplified campaign management for advertisers. However, one area where advertisers still need to make strategic decisions is in geotargeting. Geotargeting refers to the process of determining where ads are shown based on location. Advertisers must decide whether to let Google’s algorithms determine the location or to manually set specific geographic targets.
To optimize location targeting in Google Ads campaigns, there are several key considerations to keep in mind. First, advertisers should align their targeting with the availability of their products or services in different regions. If a product is not available in a certain location, it should be excluded from targeting. This helps prevent frustration for consumers and wasted funds for advertisers.
Another consideration is connecting geotargets to localized landing pages. While geotargeting is set at the campaign level, landing pages are set at the ad group or keyword level. Advertisers must make decisions about which locations require specific landing pages or site experiences.
Google offers two location settings: “Presence” and “Presence or interest.” Presence targeting means that the user is physically present in the location at the time of the search. Interest targeting means that the user is outside of the physical target but has shown interest in that area in the past. Advertisers should consider using more broad geotargeting as a best practice, but there are instances when presence targeting makes sense, such as in sensitive verticals with strict targeting limitations.
Performance differences across locations also need to be assessed. Advertisers should test whether geotargeted campaigns based on specific regions result in outsized performance variance. In some cases, aggregating data across multiple regions allows Google Ads to allocate budgets based on the most likely conversions. However, there isn’t a one-size-fits-all answer to this issue, as it depends on factors like the specific business, competitive environments, and budget levels.
Real-life examples have shown that geotargeting can go both ways. In one case, a lead generation business saw improved performance after consolidating campaigns and removing regional budget allocations. This resulted in a decrease in cost per acquisition (CPA) and an increase in leads. However, performance differences across businesses often require reallocating spend or removing it from certain regions.
The key to optimizing geotargeting in Google Ads is finding the right balance between automation and manual control. This balance depends on factors like the nature of the business, products or services, localized requirements, performance data, and testing. Using data to guide the optimization process is crucial. By analyzing and testing different approaches, advertisers can leverage geotargeting tools to enhance ROI and achieve their marketing goals.
In conclusion, geotargeting plays a crucial role in optimizing Google Ads campaigns. Advertisers must carefully consider factors like product availability, localized landing pages, performance differences across locations, and the balance between automation and manual control. By using data to guide their decisions and conducting thorough testing, advertisers can find the ideal mix of automation and granular location control to enhance campaign efficiency and effectiveness.
