Analyze Demographics and Interests data
Understanding your audience composition in terms of gender, age, and interests lets you also understand the kinds of creative content you need to develop, the kinds of media buys you should make, and the kinds of audiences you need to develop for marketing and remarketing campaigns.
Open the Demographics and Interests reports
To open the Demographics and Interests reports:
- Sign in to Google Analytics.
- Navigate to your view.
- Open Reports.
- Select Audience > Demographics or Audience > Interests.
Understand gender, age, and interests composition
Use the Demographics Overview report to start with a high-level view of your audience (male vs. female), and then drill in for details.
In this example:
- There is a 2:1 ratio of male to female users.
- There is also a 2:1 ratio of 18-34 year olds to all other age groups combined.
If you drill in to Gender and then into male, you see that the age ratio is consistent across gender.
In this example, there is a 2:1 ratio of 18-34-year-old males to all other males.
Drill in to each of the age brackets to see data for the Other Category dimension. In this example, drilling in to each of the top two age brackets, shows “Arts & Entertainment” as the top interest for both age brackets, while the second and third most popular interests differ across the age brackets.
Target high-value users
Identifying the demographics of valuable and potentially valuable customers is useful for targeting campaigns and building audiences for remarketing. For an ecommerce site, you might want to identify user groups with the highest ecommerce conversion rate or revenue. For a content-focused site, you might want to identify user groups with the highest engagement (for example, as measured by session duration or pageviews/screenviews per session).
The Age, Gender, and Interests reports all include engagement and conversion metrics. You can start from any of these reports to build a picture of your high-value customers.
In this example, the Age report shows that 18-24 and 25-34-year-olds together make up the majority of users, but the 25-34 segment contributes the most revenue and has the highest conversion rate.
If you drill in to that age group to see how it breaks down by gender, you see less disparity in the volume of sessions (still 3:1 in favor of male), but a much larger disparity in revenue (58:1). The conversion rate is 2:1 male to female, but the revenue per transaction is 9:1 in favor of male users.
So, in this example, 25-34-year-old men represent the highest-value customers.
A next step might be to identify the highest converting interest categories. You might find, for example, that Technophiles, Music and TV Lovers, News Junkies, Gamers, and Shutterbugs collectively represent the users who bring in the most revenue. So, 25-34-year-old men with these interests are the users on whom you want to focus.
You can drill in to each of these categories to further validate your findings on age and gender. Drill in to News Junkies & Avid Readers since it has the highest revenue and conversion rate.
In this example, the 25-34 segment of News Junkies & Avid Readers accounts for the vast majority of revenue and has the highest conversion rate. To see gender breakdown, drill in to the age bracket.
In keeping with the earlier findings, men in this segment outspend women by 79:1.
With this information, you can target campaigns and create audiences for your most-valuable demographic groups.
Eliminate ad spend on low-value users
You can use the same kinds of analysis to find low-value audiences that you used to find your high-value audiences: rather than look for high revenue and conversion rates, you simply look for the opposite.
Once you’ve identified those low-value customers, you can then exclude them from seeing your ads.
Segment reports along business lines
The two previous examples illustrated how to use these reports to evaluate your users at a macro level. These next examples illustrate how to use Segments to understand your users at micro levels in the context of your business. These examples look at data from the perspective of ecommerce businesses that need to understand users in the context of which products they buy, and from the perspective of publishers who need to understand sessions in the context of which content users consume.
If you are running an ecommerce business, you can segment by a number of dimensions like Product, Product Category, Product Brand, or Product SKU to see the demographic composition of your purchasing audience.
Apply the Segment to the Demographics Overview report.
You can see the age and gender breakdown for the Sessions (the key metric) initiated by users who purchased a single product.
Open the Demographics Age report to see the associated Acquisition, Behavior, and Ecommerce Conversion data.
With this one Segment applied, you can navigate through the Demographics & Interests reports to identify the high- and low-value users for a specific product.
If you’re a publisher who is selling ad space on your site, then you want to let advertisers understand who the users are who consume those pages, and the extent to which they consume them. You can evaluate consumption in terms of metrics like Sessions, Bounce Rate, Pages per Session, and Average Session Duration.
For example, if you run a site that serves lifestyle content, and you devote a section of that site to lifestyle accessories like luggage and electronics, you can create a session-based Segment to isolate traffic to those pages:
You could as easily create a Segment that isolates traffic to a single page.
Apply the Segment to the Demographics Overview report.
You can see the age and gender breakdown of users who conducted sessions that included that group of pages.
Open the Demographics Age report to see the associated Acquisition, Behavior, and Goal Conversion data.
With this one Segment applied, you can navigate through the Demographics & Interests reports to identify the high- and low-value consumers of specific content.
Refine remarketing audiences
Age, Gender, Affinity Categories, In-Market Segments, and Other Categories are all available as dimensions you can use to build the Segments that serve as the basis of your Remarketing Audiences in Analytics.
Using the Analytics report examples above, you could build the following Segment as the basis for an Analytics Remarketing Audience for your high-value customers:
Age “25-34, 35-44”
Affinity Category matches regex “Technophiles|Music Lovers|TV Lovers|News Junkies & Avid Readers|Gamers|Shutterbugs”
Any definition of an audience that you uncover in your Analytics reports can be turned into a Remarketing Audience that you can use in Google Ads.