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Benefits of the User Explorer Report in Google Analytics

Published July 15, 2016
The idea of a more personalized digital experience is not new. We’ve seen trends toward localized search results, custom tailored marketing, retargeting that reflects our recent shopping behaviors, and email marketing that uses our names and seems to know our last interaction with the sender.
It’s as though the Internet is bending and shifting to mold itself to our unique wants, needs, and behaviors. Therefore, the latest addition to Google Analytics is not only on trend, it seems almost inevitable. The new User Explorer Report enables us to analyze the behavior of individual users.
We know, Google frequently introduces new features into Analytics and it can be difficult to stay on top of all the changes. But when new measurement opportunities become available, it’s worthwhile to spend some time with new reports. Any new section presents opportunities to find new ways to better analyze your audience. Especially this one.
Google Analytics has always shown anonymous, aggregated data. While there was the ability to view metrics broken down by subsets of individuals (all people in a certain city, new vs. returning visitors, etc.), you couldn’t see metrics correlated to one specific person. The User Explorer Report changes that, a bit. Of course, the information still is anonymous, but now you can view a history of actions for a single person. For example, you can view how many times a person came to the site, how long they spent on the site, what pages they visited, what goals they completed, what purchases they made, and more. Let’s take a closer look at this report and how you can apply it to your online marketing efforts.

 

Google Analytics User Explorer Report Showing Revenue

 

Accessing the User Explorer Report

To access the report, go to Audience > User Explorer from the main Google Analytics reporting section.

 

Google Analytics User Explorer Report

 

In this report, you’ll see a list of Users who came to your site, with each assigned a Client ID number that correlates to a unique device via which a User engaged with your site. In addition, you’ll see some metrics that correlate with each User, including total Sessions, Avg. Session Duration (average time spent on site per period visiting the site), Bounce Rate, Revenue, Transactions, and Goal Conversion Rate. You’ll need ecommerce tracking in place to measure Revenue and Transaction, as well as either ecommerce or conversion tracking to measure the Goal Conversion Rate.

You can click the heading for any column to sort by that metric. Click on any Client ID to see more specific details about that User.

Looking at Individual User Reports

Once you enter an individual User Report, you’ll see a breakdown of that person’s on-site actions and the times when they occurred. For instance, here’s a report for someone who visited Megalytic.

 

Google Analytics Individual User Report

 

From this, we can see several pages this person viewed, leading up to a new account creation event, along with timestamps for each action. We can also see, in the left-hand section, the acquisition date (original date this person came to the site on the particular device tracked); the acquisition channel (original channel that led the person to the site, in this case Organic Search); and device category (Desktop here).

At the top of the righthand section, you can see the total number of Sessions in which this person came to the site, as well as total Session Duration, aggregating all of the time spent on the site across all Sessions. In addition, if ecommerce tracking is in place, you’ll see total revenue for that person.

Next, you’ll see a list of days the person visited the site, with actions listed from each day. A solid line differentiates the separate Sessions.

In the example report, we see that this individual initially found the site through a blog post about fake referrals via organic search. Perhaps the blog post inspired the user to want to learn more about the company that authored it. Perhaps they have been looking for a new reporting platform and felt compelled to take action. The exact motivation is harder to discern, but we can see that a couple of hours later, the same person later returned to investigate more about Megalytic This time their journey began on the homepage and progressed through pages about features, services, plans, and other content. Finally, this person signed up for a trial, tracked by the event NewAccount.

From this point, the report continues to show the user’s activity in trying out the Megalytic interface, visiting inner pages and seeing a sample report. We can check back in on their visit the day after signing up by looking at June 14 in this interface. You can click the arrow by any given day to collapse the list of actions for that day.

 

User Report - 2nd Day

 

Now, we can see that this person actually came back, logged into Megalytic, and began editing a report created on the previous day, going as far as adding two widgets. This shows a level of engagement indicating the user was inclined, at the very least, to test the product beyond the initial login.

You can filter actions shown in this report using the “Filter by” dropdown in the top bar. This allows you to filter by one or more of the following categories: Pageview, Goal, Ecommerce, and Event. Simply check your desired box(es) and click Apply. Finally, you can use the “Sort by” dropdown to sort actions by time, with Descending showing the most recent actions first and Ascending showing the earliest actions first.

 

User Report Filter by Pageview

 

Practical Uses for the User Explorer Report

So, we’ve covered how to review the data, but how you can you practically apply this report in your digital marketing analysis?

While you aren’t looking at larger scale trends as in other sections of Analytics, looking at an individual customer’s behavior helps you see on a more granular level how someone engages with your brand. There are numerous ways to utilize the data in this report, and certainly more to be explored, but here are a few ideas on where to start.

One is the ability to see where various pages fit in the funnel of the conversion process beyond looking at landing pages and final pages before conversion. For instance, in our previous example, we can see that someone came to a blog post before later returning to the main portion of the site. We can also note that this person looked at the Features page, browsed through a couple of other pages, and then circled back to Features before converting. From this data, we can see that while certain pages may not result in a final conversion, they may be an important step in the process leading to a signup.

This report also allows you to take a granular look at the content people who frequently return to your site are viewing. For instance, you may see that a percentage of your visitors come back 15 times in a month, but do you know what those people are looking at? Viewing high-session visits in the User Explorer report will show you what areas of the site are drawing people back, whether blog articles, product pages, or videos.

Another option is to look specifically at visitors with high session counts who did not convert. Obviously, these people are interested enough in your brand to keep coming back but aren’t choosing to sign up for your services or complete a purchase. What pages or sections of your site are they looking at where you can consider adding a call to action?

You can also analyze the behavior of individuals who have completed transactions resulting in high revenue. What pages do these people view during the process of navigating through the site? How often do they come back to the site before purchasing?

Overall, one of the greatest opportunities is to evaluate patterns and trends that appear among multiple users. When several individuals take similar actions that bear similar results, there are valuable lessons to be learned from these behaviors.

Conclusion

The User Explorer Report offers capabilities not previously available in Google Analytics, making it a truly meaningful addition to the existing views. You can analyze an individual’s direct path to conversion or evaluate a more nonlinear customer journey and the sequence of over the course of multiple visits.

Use this report to fine-tune your approach to attracting conversions and revenue. This data will take you a step beyond looking at large-scale trends to granular aspects of the user experience and how they pertain to positive outcomes. This is an exciting new level of analysis that allows us the ability to understand the often convoluted course to conversion. With this insight we all have the potential to change the way we connect with our customers.

ALSO IN THIS BLOG

When the client first came to you, you talked up the value of Google Analytics. You emphasized the importance of seeing where your traffic was coming from. You went on and on about how Google Analytics can show traffic sources to pinpoint whether people came from search, social media or a specific site referral, and how valuable this data was. You sold them on it, so much so that your client looked forward to receiving that first report, the magical day when they would finally understand where visitors were coming from.
But then the report came, and it looked like this:

 

 

It showed that 10% of your client’s traffic came from “(direct)/(none)”. What does this label mean? How do you explain Direct traffic to your client? Better yet, how do you explain “none”?
Let’s take a closer look at understanding Direct traffic in Google Analytics and how we can address it with clients.
Remember how your mom told you not to stand too close to the television because it might hurt your eyes?

The same rules can apply to data. If you’re too close, you may miss the patterns and trends that are crucial to understanding your website’s performance. You can’t judge a site’s performance looking at data in the bubble of a single day, you must consider any day’s traffic compared to the days before and after.

Google Analytics makes it fairly easy to analyze trends over long periods of time. But it also allows you to stand right in front of that TV, to look at more granular levels of time, right down to the hour.
There’s a better way to get that close to the data, without burning your retinas. We’ll cover how to analyze traffic effectively in today’s post.
Digital marketers spend a lot of time focused on PPC and SEO campaigns in order to drive desirable traffic to a website. The phrases we’re ranking for and bidding on get meticulous attention, so much so that we often forget about some of the other ways that visitors find us.

We put a tremendous amount of the effort we put into reviewing organic search data and PPC campaign performance in analytics. But how closely do we monitor referral reports?

If that’s not a channel you review regularly, you may be missing out on seeing traffic that is coming directly from links you’ve obtained around the web, local business listings, news mentions, and more. Many times, links are only considered as a means to an end, a metric that Google uses in determining how to rank sites in the SERPs (search engine results pages). But the fact is, many of a site’s links may be directly contributing to its traffic.

In this article, we’ll review how to look at referral reports in Google Analytics, and some of the many ways to use that data to better inform your web marketing decisions.