Hey guys, we’re back again with our weekly series: Google Analytic’s Fundamentals. This week’s article is a continuation of last week’s discussion about using Google Analytics to better understand your core audiences. This week we’ll focus more on specific dimensions while also discussing how to gain clearer insights about your visitors.
What can you get from this article?
- Understand the four most important dimensions about Google Analytics that will allow you to better understand your customers.
- Understand the differences between these four dimensions and how to account for these differences in your analysis.
- Understand how to convert the results of your analysis into real data-driven decisions that will positively affect your business.
We are focusing on four dimensions of Google Analytics
Overall, there are four dimensions in Google Analytics that are particularly relevant to helping you understand your core audience.
- Demographics: This includes the attributes of a user such as their age, gender, and interests.
- Location: The geographic location where the website is accessed. This can range from the city level to the continent level.
- Behavior: This shows whether the users are new or returning and how engaged they are with your website by showcasing their number of visits and their session length.
- Devices: The devices the sessions were conducted on (e.g. mobile, desktop, tablet).
Without further ado, let’s drill down into each of these dimensions and see how you can apply the knowledge they provide in order to help you understand your visitors and turn that understanding into actionable business insights.
The demographics category includes four dimensions, all of which are predicted by Google based on the user’s browsing behavior:
- Age Group: the user will be assigned to one of six age groups (18–24, 25–34, 35–44, 45–54, 55–64, 65+) based on their browsing behavior
- Gender: male or female
- Affinity Categories: predicted interests of the user
- In-Market Segments: predicted industry segment of the user (e.g. travel, education/post-secondary, etc.)
Google intentionally aligns the dimensions used here with the ones they use in Google Adwords. This means that if you are able to identify your target audience’s demographic it is very simple to then run a parallel Google Adwords campaign that targets the same audience.
It is interesting to note that the affinity categories and in-market segments might not make sense to you (I have seen “moviegoers” as the top visitor segment of a juice website). However, this is totally fine because at this point knowing which specific user group is driving traffic to your website is more important than knowing exactly why they are coming. Right now all that you need to know is that targeting this user group will likely drive more traffic to your website and increase your conversion rate.
The location category is fairly straightforward. It is made up of four geographic levels that tell you where the visitor of your site is located while they’re doing their surfing. This includes their city, country, subcontinent, and continent.
In addition to providing their geographic location, Google Analytics also offers their language as a dimension but this is only helpful if you are a multinational corporation or if you are trying to identify international spam.
For companies without an international presence, I recommend focusing on city-level data for the best results. Comparing metrics across different cities using the method below can give you many surprising insights.
Behavior is one of the most valuable dimensions of your site visitors that you can analyze. Google Analytics provides three modules that help you better understand user behavior on your site:
- New vs Returning: Compares the differences in behavior of new visitors and returning visitors.
- Frequency & Recency: Displays the distribution of how frequently visitors visit your website.
- Engagement: Displays the distribution of how long visitors spend on your site through number of page views and sessions.
Unfortunately, of these three modules, the only one that can be displayed in a standard dashboard is New vs Returning.
In order to produce a dashboard-like analysis for the remaining two variables, you need to create customized segments through the customized segmentation feature (learn more here, and read this blog post for more details about customized segments).
For example, you could create a segment of users who have visited your site more than three times. You can then compare this segment with other returning visitors to identify changes in user behavior as they visit your site more frequently.
However, with New vs Returning visitors segment alone we are still able to extract a lot of great insights.
When analyzing New vs Returning visitors, the first thing we need to do is modify the rules of analysis we explained above in order to account for the fact that new visitors behave differently than returning visitors.
Here are a few ways returning visitors behave differently as compared to new visitors
- They are usually less of them than new visitors.
- Their sessions usually have higher engagement (lower bounce rate, higher pages/session, higher avg. session duration).
- Their sessions usually have a much higher conversion rate than new visitor sessions.
When analyzing new vs returning visitors, you need to account for these tendencies and modify your analysis accordingly.
For example, if the conversion rate between new and returning visitors is similar, you have a problem. Using this insight, you could then hypothesize that the number of visits to your site has no effect on how users feel about the credibility of your products or services.
Optimizing your user experience across devices has become increasingly important.
Google recently rolled out a new algorithm that places more emphasis on mobile experience in determining the search engine ranking of a website (read more here).
This means that even if you have a good desktop website you will need to optimize your mobile platform in order for Google to rank your site well in search results.
Google can tell you the browser and operating system a user uses, their network provider, and what device they visited from.
However, I would recommend that novice analysts focus solely on the Mobile vs Desktop experience.
Just as with Returning vs New visitors, the behavior of mobile and desktop users is inherently different. Here are some guidelines to keep in mind:
- The total number of sessions on mobile is generally lower than the total number of sessions on desktop. However, depending on your business type (mobile game company vs grocery store), this difference could be more or less pronounced.
- Mobile sessions will generally have lower engagement (higher bounce rate, lower pages/session, lower avg. sessions duration).
- The conversion rate on mobile will be significantly lower than the conversion rate on desktop.
Applying Insights to Business Actions
Finally, we have come to the “so what” question. Now you know how to learn all about your customers and potential customers but how is this relevant to your business?
There are three primary ways you can use the results of your visitor analysis to inform business decisions: 1) strategy modification 2) targeted advertising, and 3) website optimization.
This point is particularly valuable for startups. During the early stages of your business, it is usually extremely difficult to understand the demographics of users who are interested in your products and services. With visitor analysis, you can uncover this mystery and use the information to tailor your product development and strategy towards that specific user group.
At the same time, startups are all about testing. One of the cheapest ways to test the traction and viability of your idea is to place a Google Adwords ad to see how many people visit your site.
In this case, visitor analysis can tell you exactly who visited your site. With the results of this analysis, you can reach out to users in that specific demographic group and build your product for them.
Advertising platforms such as Facebook Ads and Google Adwords now provide very detailed targeting options based on the age, gender, interests, and other attributes of your users.
Using the result of your visitor analysis, you can now design specialized marketing campaigns targeting your specific user groups and thus greatly increase your reach and message effectiveness. In other words, it allows you to reach more of the people who need your services and ensure that those messages are tailored to their needs.
Even better, both Google Analytics and Google Adwords use the same interests and affinity categories so you can simply plug the results of your visitor analysis directly into the Adwords tool, saving you a lot of time and work.
Although page-level and user-flow analyses are the best option for optimizing your website user experience, visitor analysis serves as a great starting point to guide your future analysis.
For example, if a certain user group has a significantly higher bounce rate than other users, it is worth taking note of this anomaly when conducting user flow analyses in order to better understand why that specific group is having a sub-par experience.
It is also worth noting that you can also break down your page-by-page and behavior flow analysis by user groups. Adding another dimension (user group) to your analysis will increase the complexity of your information but may return surprising and valuable insights about your website.
That’s it for our Google Analytics guide this week. We hope it will help you turn your Google Analytics data into actionable business insights. If you have any questions or feedback, please comment below or email me at firstname.lastname@example.org
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