About Demographics and Interests
Demographics and interests data provides information about the age and gender of your users, along with the interests they express through their online travel and purchasing activities.In this article:
Configure Analytics to display Demographics and Interests data
Before you can see or work with Demographics and Interests data in Analytics, you need to:
- Enable Advertising Reporting Features for your property
- Enable the Demographics and Interests reports for the view
Where Analytics gets the data
Once you update Analytics to support Advertising Reporting Features, Analytics collects Demographics and Interests data from the following sources:
|Third-party DoubleClick cookie||Web-browser activity only||Cookie is present||Analytics collects any demographic and interests information available in the cookie|
|Android Advertising ID||App activity only||You update the Analytics tracking code in an Android app to collect the Advertising ID||Analytics generates an identifier based on the ID that includes demographic and interests information associated with users’ app activity|
|iOS Identifier for Advertisers (IDFA)||App activity only||You update the Analytics tracking code in an iOS app to collect the IDFA||Analytics generates an identifier based on the IDFA that includes demographic and interests information associated with users’ app activity|
Demographics and interests data may only be available for a subset of your users, and may not represent the overall composition of your traffic: Analytics cannot collect the demographics and interests information if the DoubleClick cookie or the Device Advertising ID is not present, of if no activity profile is included.
The graphs and the first row of the Sessions column in the Overview report display the percentage of your overall data that is represented (for example, Age - 41.39% of total sessions).
Neither analytics.js nor ga.js collects demographics and interests data.
|Age||18-24, 25-34, 35-44, 45-54, 55-64, 65+|
|Affinity Categories||Lifestyles similar to TV audiences, for example: Technophiles, Sports Fans, and Cooking Enthusiasts|
|In-Market Segments||Product-purchase interests|
|Other Categories||Provides the most specific view of your users. For example, Affinity Categories includes Foodies, while Other Categories includes Recipes/Cuisines/East Asian|
You can view any applicable Analytics metrics in the context of these dimensions (e.g., Sessions, Bounce Rate, Transactions, Revenue).
Some geographies have limited coverage of interests. Data may not be available for many values of Affinity Categories, In-Market Segments, and Other Categories. Also, you may find that less data is available for In-Market Segments than for Affinity Categories and Other Categories.
Seven standard reports are available:
- Demographics Overview: The distribution of Sessions (or other key metrics) on your property by age group and gender. Sessions is the default key metric. You can also use % New Sessions, Avg. Session Duration, Bounce Rate, or Pages per Session.
- Age: Acquisition, Behavior, and Conversions metrics broken down by age group. When you drill into an age group, you see the breakdown by gender, then by interest. Ages below 18 are not included in the data.
- Gender: Acquisition, Behavior, and Conversions metrics broken down by gender. When you drill into a gender, you see the breakdown by age group, then by interest.
- Interests Overview: The distribution of Sessions (or other key metrics) on your property by the top-10 interests in Affinity Categories, In-Market Segments, and Other Categories.
- Affinity Categories (reach): Acquisition, Behavior, and Conversions metrics broken down by Affinity Categories.
- In-Market Segments: Acquisition, Behavior, and Conversions metrics broken down by In-Market Segments.
- Other Categories: Acquisition, Behavior, and Conversions metrics broken down by Other Categories.
You can use the Demographics and Interests dimensions in Custom Reports. For example, you might want to use the Gender and/or Age dimensions to set the context for evaluating Ecommerce metrics like Buy-to-Detail Rate or Product Revenue per Purchase.
Before you can see data in custom reports, you must enable Advertising Features for your property and enable reporting in the view.
Affinity, In-Market, and Other Categories are based on a hierarchical taxonomy that is flattened in Analytics; for example, in Other Categories:
- Internet Software
- Internet Clients and Browsers
- Internet Software
becomes three separate categories in Analytics:
- Software/Internet Software
- Software/Internet Software/Internet Clients and Browsers
A single session can be classified in multiple categories, and as such, can be counted multiple times in the metrics. For example, a session classified in Software/Internet Software/Internet Clients and Browsers will also be classified in Software/Internet Software and Software.
Even though a session can be counted in multiple interest categories, it is counted only once in the total at the top of the column.
Thresholds are applied to prevent anyone viewing a report from inferring the demographics or interests of individual users. When a report contains Age, Gender, or Interest Category (as a primary or secondary dimension, or as part of an applied segment), a threshold may be applied and some data may be withheld from the report. For example, if there are fewer than N instances of Gender=male in a report, then data for the male value may be withheld.
If a threshold has been applied to a report, you will see a notice below the report title.
Targeting on the Google Display Network
Analytics uses the same age, gender, and interests categories that you use in AdWords to target ads on the Google Display Network. For advertisers, this parity between products lets you explore the data in Analytics, and then put your findings to work in AdWords. For example, you can see how behavior on your site or in your app varies among different segments of users (Do 25-34 year old Technophiles have higher conversion rates than 35-44 year old Technophiles?). The results of that exploration let you then refine your ad targeting on the Google Display Network. If, for example, 25-34 year old Technophiles convert at a higher rate than their 35-44 year old counterparts, you might focus more of your ad budget on the 25-34 year old group.