Once “not provided” data started replacing real keywords in Google Analytics, cynics believed all was lost when it came to information available in Google Analytics. However, when Demographic reports were launched in 2013, a whole new world of data became available to help us understand our audience. Let’s take a look at what is available to us now.
Demographics: Age and Gender
From the Overview section, you have a glance of your visitors by age and gender. You can change the small drop-down menu above the overview charts to look at new sessions, average time spent, bounce rate, and pages/session. These basic metrics are not new to people who have used analytics for a while. However, the ability to look at these metrics by age and gender will help determine if your preferred audience is coming to the site and interacting with it as you had hoped.
Think about just the age metric for a minute. Is your brand more relevant for millennials or seniors? I have one retail client that caters primarily to the 45-54 year old crowd. I looked at that specific age group in their account and added a secondary dimension of traffic source. Although they received more of these visitors through organic search, the ones they received through their email list were more likely to make a purchase. This makes sense since their email is going to people who request it and are already fans. If the reverse was true, meaning people who were 45-54 bought more when they came in organically, it might indicate a problem with the content in their e-news which is valuable data to have. Basically, this information can be used for troubleshooting if a strategy does not seem to be going well.
I can also see that one of their social media channels is not bringing in a significant number of visitors in this age group. However, when they do visit the site from this particular channel, they are highly likely to make a purchase. In fact, this channel had a 9% conversion rate over one month! Knowing this information helps the retailer see that efforts on their social media is producing a good return for their targeted age group when the link is clicked.
The same thing can be done with gender. Since this client provides high end home and fashion that appeal primarily to women, it is no surprise that females represent 75% of their traffic and 90% of their revenue. However, that other 10% is coming from males so that demographic should not be completely ignored.
Beyond learning about the age and gender of our visitors, we can also find out what interests them. This is a huge opportunity for advertisers and content writers. The Interests section also offers the Overview commonly seen in areas of analytics. It can be broken down by Affinity Categories, In-Market Segments, and Other Categories. The top Affinity Category for this retailer is Shopper/Shopaholics. Since this is a high end fashion site, that certainly is not a surprise! However, the second one is Movie Lovers. Perhaps in promoting their fashion items, they could comment on fashion trends seen in recent movies. That may sound like a stretch, but if their visitors like shopping and movies, there is no harm in trying some creative content in that area.
In-Market tells us other areas where the visitor is looking to make a purchase. As expected in this situation, the top segment is Apparel & Accessories. Maybe advertising on specialty sites that are not competitors would increase sales. Or providing samples for popular bloggers who write about accessories would be another way to drive buyers to the site.
Other Categories is simply other areas of interest that they are browsing. The top one for this fashion site is Arts & Entertainment/Celebrities & Entertainment News. Again, this offers more ideas for content writers.
As with most things in life, demographics and interests data is not perfect. When you start drilling into your data, you may see a yellow bar that states “Some data in this report may have been removed when a threshold was applied”. This means that Google is not going to drill in any farther because to do so could start to identify individuals.
Also, the data is not be perfectly accurate. Visit https://www.google.com/ads/preferences to see what Google thinks you are about. Some of the results are a bit surprising. Google has me at about 10 years younger than I am based on my browsing habits. (Hey, I’ll take it). And one of my assumed interests is animals which does not make much sense since I do not own any pets. So although it’s not 100% perfect, it still gives marketers something to go on and can get the creative juices flowing. With anything in analytics, the data there is just a bunch of numbers. The point is finding ways to use those numbers to make strategic marketing decisions.