With so much data available through Google Analytics, sometimes it's easy to fall into the trap of always looking at the same things – reviewing keyword referrals or landing pages, or simply looking at traffic trends.
However, a wealth of available data is often overlooked. Sometimes reviewing something different, or slicing the data in a new way, is all it takes to find a great new opportunity or diagnose a long-standing problem.
Here are three top features in Google Analytics for giving a fresh look to data you may have looked at too many times before.
Advanced segments are a godsend for any type of analytics review or diagnosis. By default, you can look at traffic for organic search (or paid depending on the client focus) vs. all traffic to understand the trends and traffic changes you're seeing for the work you're doing against the overall traffic to the client's site.
Segmenting only new traffic is also a good way to help understand if a site is providing the relevant information in the right places to take brand new visitors to a conversion.
I have also recently started using custom segments to identify and exclude visitors who log in (set up a new custom segment to exclude any visitor who lands on the thank you for logging in page of your site). This is a useful alternative to a custom segment to help understand the behavior of new and returning visitors who have never signed up to, or purchased from, a site.
Audience Behavior, Frequency, Recency & Engagement
Frequency and recency refer to how often, and at what time intervals, a visitor returns to the site. Engagement metrics look at how long users are spending on site and how many pages they look at.
While these reports are somewhat broad brush, they make great starting points for understanding what direction you should take in your analytics research.
For instance, looking at the frequency of visits to a hotel site might show that there is a high return rate within 3 days, and a second peak at 50-100 days. This suggests that a large number of visitors are taking a three day period to review their hotel options before making a booking, and that they will generally wait 2-3 months before looking to book again.
When we combine this data with an advanced segment of only converting visitors, the data becomes even more stark. This data can be used to influence retargeting and email campaigns to increase conversion and return visitor rate.
Looking more closely at engagement, we can choose to review visit duration and page depth. I generally expect to see a peak for 0-10s visit duration and then a second peak for much longer duration periods, but the side of these peaks can be very telling about the relevancy of the information being provided to visitors.
Understanding the number of pages that converting visitors look at (again using this feature in conjunction with advanced segments) you should see a minimum number of page views required due to the conversion or shopping cart process. However, if you see a small number of page views above this number resulting in high conversions, you might be prompted to look at sending more traffic to these pages, or to understand the topic of these pages and focusing additional efforts there.
Multi-Channel funnels were launched in August last year, and provide extremely interesting data on the paths that customers take before converting on your site. This is extremely useful information for understanding the true value of a referral source over and above the last touch conversions that it drives.
This is especially useful for low conversion referral channels, and can provide valuable insights into true value. You can see first touch conversion data through the reports in this section and also start to understand how many visits it takes for customer to reach conversion.
The downside to this report is that the data isn't very granular (you can see for instance that a customer clicked through paid search, organic search and eventually converted through a direct visit, but you can't see the keywords involved). Despite this, it's a huge step toward better understanding of customer behavior and the true value each channel provides.
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