Location targeting is a way for advertisers to clearly specify the location they want their ads to show. It is a crucial aspect for any ad campaign.
Advertisers can choose different content for their ads based on geographic locations. Many advertisers, however, stumble in setting it up due to its non-intuitive UI, or they incorrectly estimate the reach of their campaign budget.
It’s important to honor the rules of engagement for different ad network location targeting. Applying the same strategies across all networks may not yield the best results.
In this article, we’ll dissect the major ad networks’ location targeting options and offer some general rules on how to approach location targeting. Our goal is to provide a framework to guide you rather than specific instructions to follow.
Basics of location targeting
When selecting a location to target, you can choose:
- To target the exact location
- A radius around it
- Nearby/related locations.
You can target specific elements like ZIP codes, cities, DMAs (Designated Market Areas), or countries. County or DMA targeting may have overlaps depending on how they are defined.
If you manage campaigns for multiple locations with designated budgets, consider using ZIP code exclusions while using county or DMA targets. Adding a location to a campaign provides a focus for the campaign. However, including too many locations in a single campaign can hinder budget efficiency.
It is generally recommended to target no more than five major locations and preferably avoid multiple time zones within a single campaign. If your campaign targets the entire United States, ensure your budget covers the entire country and that your creative aligns with various regions to avoid message translation issues.
Why is adding exclusions important?
Exclusions work in the same way as targeting; they allow you to exclude specific spots or radii. The most effective practice is to identify specific exclusions within a radius or set overlapping exclusions to protect a specific location.
Let’s say you’re managing several locations on a single ad account and need to ensure each location receives its individual budget. In this case, you’d want to avoid budget overlaps that might divert leads meant for one location to another. This is where exclusions prove invaluable.
What location metrics should you monitor?
When setting your locations, you’ll also have access to metrics per location. If a particular location is not getting sufficient exposure or if the cost per engagement is too high, it might be time to reassess whether that location deserves your budget.
Optmyzr’s geo-mapping and value based bidding rules can help assess and action these insights.
The main metrics to consider in location targeting are:
- Average CPC: competitiveness as well as cost of living
- CTR: are you speaking in the language of your prospects by location?
- Conversion Rate: is a location a prime location for your prospects?
Now, let’s dive into the specific rules of engagement for each major ad network. It’s worth noting that this post was written based on the current rules of each platform, and we will update it if any changes occur.
Google
Google Ads’ location targeting functions at the campaign level. Thus, you should treat each location as a campaign objective. When combining multiple locations in a single campaign, consider the search patterns, auction price, and customer profitability in those areas. One crucial point is that Google Ads operates based on the account’s time zone, not the user’s. Hence, consider this when structuring your ad schedules and optimizing campaigns.
Microsoft
Microsoft’s location targeting is similar to Google’s but with a few crucial differences. Location targeting can be set at an ad group level, which can simplify your campaign structure. Also, since ads serve in the user’s time zone, scheduling can be more precisely aligned with your target audience’s habits. These factors make Microsoft Ads potentially more effective for advertisers struggling with budget and servability issues on Google.
Read*:* 7 powerful optimization tips to get more conversions from your Microsoft Ads
Facebook
With Facebook, the most specific campaign settings, including location targeting, operate at the ad set level. However, Facebook’s robust audience network offers more flexibility and specificity when it comes to location-based targeting. Remember, though, that targeting too small a location may result in your ads not being served, due to privacy-first web considerations.
Amazon
Amazon differs slightly as it allows anyone, anywhere to purchase from your product line, making location targeting less important. However, if there are areas where you don’t want your ads to be served, exclusions are available.
LinkedIn
LinkedIn’s location targeting rules mirror those of Facebook, with the ad set being more important than the campaign. However, given the types of ads that LinkedIn runs, it’s crucial to carefully consider the type of campaign and creative you intend to use.
Final Takeaways
In conclusion, effective location targeting can be complex but it’s an essential component of successful ad campaigns. We hope this guide helps you navigate the unique location targeting settings across these major ad networks.
Continue reading: Learn how WebMechanix used value-based bidding to generate 30% higher quality leads for their client.
Google announced earlier this year that video and discovery campaigns using audience expansion will transition to a new automation called optimized targeting, starting in June 2021. This feature will automatically show ads to people who are likely to convert. So how’s this different from audience expansion, which has been around since 2019 and works for a broader set of campaigns?
What is Audience Expansion in Google Ads?
Audience expansion looks for similar audiences to show ads to more users. An advertiser who’s selected the audience of in-market SUV buyers may see their audience expand to in-market car buyers because there is a similarity between these audiences. Assuming advertisers are using smart bidding, their CPA or ROAS results should remain consistent because smart bidding will automatically lower bids for related, but less relevant audiences.
Think of audience expansion as a system that starts from an advertiser’s selected inputs and expands from there. That works fine if the advertiser has done a good job selecting audiences. But it won’t capture new sales from entirely different audiences advertisers may have overlooked because they seemed too dissimilar for audience expansion to even try.
What is Optimized Targeting in Google Ads?
Optimized targeting on the other hand starts not from an advertiser’s targeting settings, but from the results they report. When an advertiser gets conversions, Google analyzes attributes of the converting users. If they find a pattern, like what types of searches lots of converting users recently did, then the system will automatically start to show ads to other users with similar behaviors.
This is another example of the huge shift in how PPC is optimized. Rather than managing details like targeting, Google wants us to optimize how we teach their machines to do their job better, in this case by reporting conversions more accurately using systems like offline conversion tracking, value adjust or value rules, all 3 tools we recently covered on this blog.
Let me explain optimized targeting in a more visual way.
How old school PPC management works
In traditional PPC optimization, a lot of time is spent managing lots of dials and settings. This is all done for the ultimate goal of getting conversions whether that means more sales, more revenue, more profits, or new customers.
Old school PPC is about limiting who sees ads using multiple settings
So in a universe of all people, our settings limit which people we want to show ads to. We assume we are good at guessing the right settings to get our ads in front of all prospective customers.
Audience expansion uses your settings to show more ads
Audience expansion works by expanding on one of the many settings we’ve dialed in, specifically which audiences or remarketing lists we’ve selected in order to limit who can see our ads.
Thanks to audience expansion, ads are now shown to some additional people. But there’s no guarantee that they’re being shown to people who would likely convert because that depends a great deal on how well the account manager set up their campaign targeting in the first place.
Modern PPC management teaches the machine what we want
Optimized targeting is interesting in that it completely doesn’t care about advertiser decisions about how to manage the myriad settings in Google Ads. Instead it starts from how we reported conversions and looks at what commonalities exist between actual converters.
From there it finds pockets of similar users to show the ads to. The assumption is that even if these users are wildly different from a targeting perspective, the thing that really matters is their similar behaviors. The system only worries about finding clones or doppelgängers of converting users. That’s a totally different approach but actually makes a ton of sense.
Pretty cool, Google!
The only way to really get results: Monitor them
While I love the innovative machine learning implementation here, as always it’s up to advertisers to monitor that these new automations are functioning as intended. Put on your PPC pilot hat and use tools like Optmyzr PPC alerts to immediately know when an automation fails.
Put on your PPC teacher hat to make sure you’ve done the best possible job reporting true conversions (e.g. good leads vs just leads). And put on your PPC doctor hat to make sure this new tool from Google is the right fit for your goals. You can after all still opt out of this feature by changing your targeting settings.
Regular Pages
Location targeting is a way for advertisers to clearly specify the location they want their ads to show. It is a crucial aspect for any ad campaign.
Advertisers can choose different content for their ads based on geographic locations. Many advertisers, however, stumble in setting it up due to its non-intuitive UI, or they incorrectly estimate the reach of their campaign budget.
It’s important to honor the rules of engagement for different ad network location targeting. Applying the same strategies across all networks may not yield the best results.
In this article, we’ll dissect the major ad networks’ location targeting options and offer some general rules on how to approach location targeting. Our goal is to provide a framework to guide you rather than specific instructions to follow.
Basics of location targeting
When selecting a location to target, you can choose:
- To target the exact location
- A radius around it
- Nearby/related locations.
You can target specific elements like ZIP codes, cities, DMAs (Designated Market Areas), or countries. County or DMA targeting may have overlaps depending on how they are defined.
If you manage campaigns for multiple locations with designated budgets, consider using ZIP code exclusions while using county or DMA targets. Adding a location to a campaign provides a focus for the campaign. However, including too many locations in a single campaign can hinder budget efficiency.
It is generally recommended to target no more than five major locations and preferably avoid multiple time zones within a single campaign. If your campaign targets the entire United States, ensure your budget covers the entire country and that your creative aligns with various regions to avoid message translation issues.
Why is adding exclusions important?
Exclusions work in the same way as targeting; they allow you to exclude specific spots or radii. The most effective practice is to identify specific exclusions within a radius or set overlapping exclusions to protect a specific location.
Let’s say you’re managing several locations on a single ad account and need to ensure each location receives its individual budget. In this case, you’d want to avoid budget overlaps that might divert leads meant for one location to another. This is where exclusions prove invaluable.
What location metrics should you monitor?
When setting your locations, you’ll also have access to metrics per location. If a particular location is not getting sufficient exposure or if the cost per engagement is too high, it might be time to reassess whether that location deserves your budget.
Optmyzr’s geo-mapping and value based bidding rules can help assess and action these insights.
The main metrics to consider in location targeting are:
- Average CPC: competitiveness as well as cost of living
- CTR: are you speaking in the language of your prospects by location?
- Conversion Rate: is a location a prime location for your prospects?
Now, let’s dive into the specific rules of engagement for each major ad network. It’s worth noting that this post was written based on the current rules of each platform, and we will update it if any changes occur.
Google
Google Ads’ location targeting functions at the campaign level. Thus, you should treat each location as a campaign objective. When combining multiple locations in a single campaign, consider the search patterns, auction price, and customer profitability in those areas. One crucial point is that Google Ads operates based on the account’s time zone, not the user’s. Hence, consider this when structuring your ad schedules and optimizing campaigns.
Microsoft
Microsoft’s location targeting is similar to Google’s but with a few crucial differences. Location targeting can be set at an ad group level, which can simplify your campaign structure. Also, since ads serve in the user’s time zone, scheduling can be more precisely aligned with your target audience’s habits. These factors make Microsoft Ads potentially more effective for advertisers struggling with budget and servability issues on Google.
Read*:* 7 powerful optimization tips to get more conversions from your Microsoft Ads
Facebook
With Facebook, the most specific campaign settings, including location targeting, operate at the ad set level. However, Facebook’s robust audience network offers more flexibility and specificity when it comes to location-based targeting. Remember, though, that targeting too small a location may result in your ads not being served, due to privacy-first web considerations.
Amazon
Amazon differs slightly as it allows anyone, anywhere to purchase from your product line, making location targeting less important. However, if there are areas where you don’t want your ads to be served, exclusions are available.
LinkedIn
LinkedIn’s location targeting rules mirror those of Facebook, with the ad set being more important than the campaign. However, given the types of ads that LinkedIn runs, it’s crucial to carefully consider the type of campaign and creative you intend to use.
Final Takeaways
In conclusion, effective location targeting can be complex but it’s an essential component of successful ad campaigns. We hope this guide helps you navigate the unique location targeting settings across these major ad networks.
Continue reading: Learn how WebMechanix used value-based bidding to generate 30% higher quality leads for their client.
Google announced earlier this year that video and discovery campaigns using audience expansion will transition to a new automation called optimized targeting, starting in June 2021. This feature will automatically show ads to people who are likely to convert. So how’s this different from audience expansion, which has been around since 2019 and works for a broader set of campaigns?
What is Audience Expansion in Google Ads?
Audience expansion looks for similar audiences to show ads to more users. An advertiser who’s selected the audience of in-market SUV buyers may see their audience expand to in-market car buyers because there is a similarity between these audiences. Assuming advertisers are using smart bidding, their CPA or ROAS results should remain consistent because smart bidding will automatically lower bids for related, but less relevant audiences.
Think of audience expansion as a system that starts from an advertiser’s selected inputs and expands from there. That works fine if the advertiser has done a good job selecting audiences. But it won’t capture new sales from entirely different audiences advertisers may have overlooked because they seemed too dissimilar for audience expansion to even try.
What is Optimized Targeting in Google Ads?
Optimized targeting on the other hand starts not from an advertiser’s targeting settings, but from the results they report. When an advertiser gets conversions, Google analyzes attributes of the converting users. If they find a pattern, like what types of searches lots of converting users recently did, then the system will automatically start to show ads to other users with similar behaviors.
This is another example of the huge shift in how PPC is optimized. Rather than managing details like targeting, Google wants us to optimize how we teach their machines to do their job better, in this case by reporting conversions more accurately using systems like offline conversion tracking, value adjust or value rules, all 3 tools we recently covered on this blog.
Let me explain optimized targeting in a more visual way.
How old school PPC management works
In traditional PPC optimization, a lot of time is spent managing lots of dials and settings. This is all done for the ultimate goal of getting conversions whether that means more sales, more revenue, more profits, or new customers.
Old school PPC is about limiting who sees ads using multiple settings
So in a universe of all people, our settings limit which people we want to show ads to. We assume we are good at guessing the right settings to get our ads in front of all prospective customers.
Audience expansion uses your settings to show more ads
Audience expansion works by expanding on one of the many settings we’ve dialed in, specifically which audiences or remarketing lists we’ve selected in order to limit who can see our ads.
Thanks to audience expansion, ads are now shown to some additional people. But there’s no guarantee that they’re being shown to people who would likely convert because that depends a great deal on how well the account manager set up their campaign targeting in the first place.
Modern PPC management teaches the machine what we want
Optimized targeting is interesting in that it completely doesn’t care about advertiser decisions about how to manage the myriad settings in Google Ads. Instead it starts from how we reported conversions and looks at what commonalities exist between actual converters.
From there it finds pockets of similar users to show the ads to. The assumption is that even if these users are wildly different from a targeting perspective, the thing that really matters is their similar behaviors. The system only worries about finding clones or doppelgängers of converting users. That’s a totally different approach but actually makes a ton of sense.
Pretty cool, Google!
The only way to really get results: Monitor them
While I love the innovative machine learning implementation here, as always it’s up to advertisers to monitor that these new automations are functioning as intended. Put on your PPC pilot hat and use tools like Optmyzr PPC alerts to immediately know when an automation fails.
Put on your PPC teacher hat to make sure you’ve done the best possible job reporting true conversions (e.g. good leads vs just leads). And put on your PPC doctor hat to make sure this new tool from Google is the right fit for your goals. You can after all still opt out of this feature by changing your targeting settings.
