FAQs: Bullseye Geotargeting
What is bullseye geotargeting?
Bullseye targeting, also known as Layered Location Targeting, is a way to layer geographical targeting areas within Google Ads in order to get more detailed information about where users are when they see an ad and to better control bids based on that information. With layered targeting, you are essentially targeting the same location multiple times, which can seem a little redundant. Why do I want to target the same area across 3 layers? The answer is quite simple in theory: control. By layering your targeting areas, you are better able to control how much you bid for smaller geographic areas based on performance and business need. Bullseye targeting can be used at the same time as other geotargets, such as city or zip code targeting.
The recommended best practice for bullseye targeting is to layer increasingly larger radii around an address, such as a store location. For example, if a store in the Somerville area near Boston wants to implement bullseye targeting, they may add the following targeting layers to the campaign:
- 1 mile around the location
- 3 miles around the location
- 5 miles around the location
- 7 miles around the location
After the campaign has sufficient time to gather data (60-90 days typically), Google will then provide KPIs for how the campaigns are performing within each of those radii segments in the bullseye. This allows the advertiser to set bid adjustments for different radii to help Google prioritize areas where users are more likely to take action on your ads and direct fewer resources toward radii that drive fewer results.
When should you use bullseye targeting?
There’s no harm in using bullseye targeting at any point in a campaign. The radii can be layered on top of other targeting, such as zip codes.
Wondering where you should show your ads? You know the area around your store best. When you sign on for advertising services, please let us know if there are certain zip codes that we should target or exclude. A 2017 Access Development survey of consumer shopping habits revealed:
- 93.2% of consumers typically travel 20 minutes or less to make their everyday purchases.
- 87% of consumers typically travel 15 minutes or less to make their everyday purchases.
- 92% of urban consumers typically travel 15 minutes or less to make their everyday purchases.
- 70.3% of rural consumers typically travel 20 minutes or more to make their everyday purchases.
When choosing the geo-target for digital ads, franchisees should consider their area and how far consumers are willing to drive. For most locations, we recommend starting with a 5-10 mile radius and adding additional targeting layers, such as:
- Additional neighborhoods, communities or zip codes
- Major population centers where consumers may commute for work or pleasure, if reasonable
What impact will bullseye targeting have on my campaign?
Adding bullseye geotargeting to your campaign is not likely to have a major impact on performance, but it doesn’t hurt. Google says “location targeting is based on a variety of signals, including users’ settings, devices, and behavior on the platform, and is Google’s best effort to serve ads to users who meet your location settings. Because these signals vary, 100% accuracy is not guaranteed in every situation.” Bullseye targeting allows an advertiser to gain extra visibility into where ads are being shown. In 2023, machine learning has largely replaced the need for bullseye targeting. Google’s algorithms already optimize ad campaigns to show ads to users who are most likely to take action, whether they’re 5 miles away or next door to the location. However, adding bid adjustments may help signal to Google which areas take priority for the ads, allowing the budget to be spent more efficiently.
Another thing to consider is the search volume in your targeted areas compared to your budget. If there is a radius or zip code where there are more people searching for your keywords than others, you will spend more budget in this area. Depending on the monthly search volume and budget, some areas may rarely get served an ad while others take up the majority of the budget. This is normal. We recommend evaluating your customer base to determine whether certain areas drive guests with higher lifetime values than others, and making sure there is enough budget to blanket that area, in addition to areas where you get most of your customers from.
Variation in geographic reporting numbers
The geographic data in your Google Ads statistics table may vary somewhat from other data in your account or sources such as third-party tracking or web logs. Here are a few possible reasons why the data may vary:
- Campaign or billing summary: Performance data may vary slightly from data in your campaign summary or billing summary because Google’s data collection techniques can vary.
- IP addresses: IP addresses are routinely re-assigned, and Google Ads updates its IP data regularly to reflect these changes. Third-party tracking providers may update their IP data on a different schedule.
- Invalid clicks: Google Ads filters out invalid clicks, so the number of clicks per geographic area may differ from that shown by other data sources.
- Location of interest: Google Ads may pick up on locations that a potential customer has shown interest in, which other data sources may not be able to detect.
- Other sources of traffic: Third-party tracking providers may count all sources of traffic to your site, instead of just Google Ads traffic. For example, let’s say Google Ads generates 50 visits to your site, but your site has a total of 100 visits from all sources. Google Ads will only report on the 50 clicks from Google Ads traffic.
You may notice some data from “Unspecified” areas in your report. There are a number of reasons why an area where your ad showed might be unspecified:
- IP address or search query: Google can’t determine the location from the IP address, and the search query didn’t indicate interest in a recognized location.
- Multiple cities/regions in Google Maps: The search was performed on Google Maps within a large geographic area that included several cities or regions.