A note on Demographic information in Google Analytics


The purpose of this post

This tool has started to give us a lot more data about our customers and their demographic information in groups as opposed to individuals. This post will state the amount of information you can glean from Google Analytics about the site users. It will also address the perennial question of what do you do with this information. What is actionable after all? How will your business change after you know this information?

Defining Demographic information

The Google Analytics Help page says that
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 buy you should make, and the kinds of audiences you need to develop for marketing and remarketing campaigns.

The cookies tell the tale

Google Analytics gets its information from DoubleClick Third party cookies; from Android advertising ID and iOS identifier for Advertisers. The data that is really available is as follows:
  • Age: These are the age break-downs: 18-24, 25-34, 35-44, 45-54, 55-64 & 65+
  • Gender: Male and Female.
  • Affinity Categories: Interests that the user has browsed about
  • In-Market Categories: Categories that the users want to buy from.


One is assuming that you have already enabled the ability to collect demographic data and merge it with Google Analytics. If you have not done so, please follow the steps outlined here.

What it looks like

Once you have a few weeks of data, then open up the demographic reports and you will see a screen like this




This is the Google Analytics sample dataset so it is fake data but even so, by itself these are vanity metrics.  If you click onto the interests overview, you will see the following graph.





This again is not really useful apart from telling you what content your site visitors like and what they are willing to buy.


Ways to make it actionable.

How can we make this information useful one may ask? There are two distinct ways in which this information is very useful.

First, cross-tabbing these metrics with others like Acquisition, behaviour and conversions can tell you a lot of who really interacts most with your content or what age group and gender buys from you the most. Please import this nice dashboard to see some of the things you can do.

Second, you can use these metrics to create segments for re-targeting audiences for advertising. This provides your marketing team with tools to attracts niche segments more pointedly and get you better converting and more engaged traffic.


Caveats about this data

Please understand that the cookies that collect this data do not really like up with Google Analytics cookies so accuracy of the data should never be your concern. It just won’t match up with anything else in the tool. However, you should always look at trends over time to draw any meaningful conclusions in the first place.

The data around categories is very broad and no business will really fit in exactly into one category so the segments are not going to be very neat. Over time, your targeting will make this more accurate.


Conclusion

This data can be used only if we cross tabulate it with other metrics and is most useful for advertising and targeting potential customers. It is not entirely accurate but that is not the point in the first place. The reports won’t really change over time but the remarketing segments will and you will find most value of the data from using them. I hope this article has been of some use. 

If you have any questions or comments, please let me know. I am always open to feedback and possible corrections.



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