Using Google Analytics Data for Facebook Ad Targeting

Published February 11, 2016
As marketers, we love Facebook. And for good reason! Through Facebook advertising, we’re able to target users by a wide range of demographic factors, including age, gender, income, net worth, interests, and much more ( so much more!). You can even identify targeting criteria from your own data about current and potential customers and use those same filters in your Facebook marketing, as well.
Even with all of this Facebook data at our fingertips, it’s not enough to set your campaign once and then forget about it. Your ad targeting strategy should be constantly evolving; growing to incorporate the information you’re collecting about those seeking your brand.
You know the power of Facebook’s targeting criteria, but did you know that Google Analytics can help you learn about the people who are actually visiting your site, reading your content, and converting? In turn, you can use this data to adjust your targeting on social media to better reach the people who meet your desired criteria.
Let’s take a closer look at how to set up Google Analytics to get the right data about your visitors. Next, we’ll dive into how to look at the data that correlates with Facebook targeting options.


Use Google Analytics for Facebook Ads


Google Analytics Demographic Targeting

To see demographic information in Google Analytics, you’ll need to turn on one simple setting. Under the Admin section, go to Property Settings for your desired analytics property. Next, go to Data Collection under Tracking Info. Then, toggle the switch under Advertising Reporting Features on.


Google Analytics Turn on Advertiser Reporting


Now, you’ll be set up to collect demographic information about any users that come to your site, based on how Google has categorized those individuals from their activity across the web. Note that you won’t see any retroactive data, but you’ll see it build in the future. To comply with government guidelines, make sure you update your privacy policy, letting users know how you’re tracking them.

To view demographic data under Reporting, go to the Demographics section under Audience. The Demographics > Overview report will show you a top-level breakdown of age and gender categories by Session.


Google Analytics Demographics Report


At a cursory look, the 55-64 age bracket makes up the largest category of people visiting the site, while gender skews slightly in favor of female. From this initial data, you could choose to specifically target 55-64, and possibly 45-54 (the next largest category) more heavily than other ages in Facebook advertising.

However, we’re just looking at total Sessions by age and gender here. We can do better than that! Let’s break down the data much more specifically to look at engagement and conversion data by category to better inform our future ad targeting.

Evaluating Conversion Data by Demographic

We’ll look at the Age report (Audience > Demographics > Age) to break down metrics on a deeper level. Here, we’ll opt to add a Secondary Dimension to allow us to look at categories by both age and gender. To do so, click the Secondary Dimension and choose Gender (note you can type in the search bar to find your desired dimension more quickly).


Google Analytics Adding a Secondary Dimension


Once you’ve added this Dimension to your report, you’ll see your table update to include subcategories of Gender within the Age brackets. Now, we can compare a number of metrics for each category.


Google Analytics Age Gender Report


Here, we’ll sort by Goal Conversion Rate, looking at the likelihood of each category to submit a lead form on the site. As a result, we see males 55-64 are the most likely to convert. Close behind are females 35-44. We also note that females 35-44 and females 25-34 tie for the highest number of total Goal Completions, with females 25-34 having the highest Goal Value (an approximate value attached to each lead generated on the site).

Based on this data, each of these categories broken out above would be valuable to target in future Facebook advertising campaigns, segmenting by both age and gender to monitor performance for each.

Consider Engagement Data

If you’re promoting blog content and encouraging readership on your site, you’ll want to look at engagement data such as Avg. Session Duration and Pages/Session by category. This will allow you to analyze how likely people are to spend time on your site and look at multiple pages of content. Here is another site’s data, looking at the same report but sorted by Avg. Session Duration.


Google Analytics Engagement Measures


Here, we can see that females 25-34 and 18-24 barely edge out other categories with the longest time on site, as well as the most pages looked at in a Session. We can then focus on promoting content to individuals fitting these criteria.

Google Analytics Interests

Turning on demographic data tracking also enables logging of user interests, categories showing topics that users frequent across the web. These include general interests such as entertainment preferences, as well as in-market categories indicating that users are shopping for items such as new homes.


Google Analytics Interests Overview


This data can help to inform possible interest targets in Facebook advertising that may not necessarily relate to the obvious factors you may think of. For instance, you may find that people who are researching both cooking and travel may be interested in articles about ethnic food, guiding your targeting to promote articles on that topic.

Geographic Targeting

Geography is often one of the most important criteria for reaching users likely to fit your target audience. Businesses serving a local audience may find that people from one zip code may be much more likely to purchase services, as opposed to the next town over.

Using the Geography reports in Google Analytics can help to guide how you geotarget Facebook ads. As an example, we’ll look at the Geo > Location report. We’ll drill down to City level within Florida (to do this, we simply click Florida on the map). Next, we’ll sort by Goal Completions to show the cities that have driven the most leads over the past year.


Google Analytics Geographic Reporting


In this report, we can see that Cape Coral has by far driven the most lead submissions, followed by Fort Myers and Naples. Interestingly, we can also note that these aren’t necessary the towns with the highest Avg. Session Duration or Pages/Session, with other cities ranking higher for those metrics but having lower conversions. From this data, we can choose to focus on targeting Facebook content to users in the cities most likely to convert.


Google Analytics allows you to supplement the data you get from Facebook Advertising, learning about the people who engage with your website to target similar individuals elsewhere. You can find a number of factors that correlate with targeting criteria available in the Facebook ads platform, including age, gender, interests, and geography.

Be sure to review your Google Analytics data, both in planning to launch Facebook ads and in the process of refining them. Make sure you’re targeting the demographics who are most likely to spend time reading your content and, ultimately, to convert into leads and paying customers.


When the client first came to you, you talked up the value of Google Analytics. You emphasized the importance of seeing where your traffic was coming from. You went on and on about how Google Analytics can show traffic sources to pinpoint whether people came from search, social media or a specific site referral, and how valuable this data was. You sold them on it, so much so that your client looked forward to receiving that first report, the magical day when they would finally understand where visitors were coming from.
But then the report came, and it looked like this:



It showed that 10% of your client’s traffic came from “(direct)/(none)”. What does this label mean? How do you explain Direct traffic to your client? Better yet, how do you explain “none”?
Let’s take a closer look at understanding Direct traffic in Google Analytics and how we can address it with clients.
Digital marketers spend a lot of time focused on PPC and SEO campaigns in order to drive desirable traffic to a website. The phrases we’re ranking for and bidding on get meticulous attention, so much so that we often forget about some of the other ways that visitors find us.

We put a tremendous amount of the effort we put into reviewing organic search data and PPC campaign performance in analytics. But how closely do we monitor referral reports?

If that’s not a channel you review regularly, you may be missing out on seeing traffic that is coming directly from links you’ve obtained around the web, local business listings, news mentions, and more. Many times, links are only considered as a means to an end, a metric that Google uses in determining how to rank sites in the SERPs (search engine results pages). But the fact is, many of a site’s links may be directly contributing to its traffic.

In this article, we’ll review how to look at referral reports in Google Analytics, and some of the many ways to use that data to better inform your web marketing decisions.


Remember how your mom told you not to stand too close to the television because it might hurt your eyes?

The same rules can apply to data. If you’re too close, you may miss the patterns and trends that are crucial to understanding your website’s performance. You can’t judge a site’s performance looking at data in the bubble of a single day, you must consider any day’s traffic compared to the days before and after.

Google Analytics makes it fairly easy to analyze trends over long periods of time. But it also allows you to stand right in front of that TV, to look at more granular levels of time, right down to the hour.
There’s a better way to get that close to the data, without burning your retinas. We’ll cover how to analyze traffic effectively in today’s post.