Google Analytics helps you to critically analyze the performance of your website and therefore improve on its performance. However, it is not uncommon to misinterpret these metrics. I am going to show you four of them that come up commonly with our clients.
Metrics that are Often misinterpreted
The following are 4 Google Analytics metrics that are often misinterpreted and therefore misused:
1. Site Speed
How fast your website loads when a user clicks on a link is vital in improving conversion rates. Users are more likely to abandon websites that take more than 3 seconds to load.
Think about it! If you open a host of sites to find information you tend to ignore the slow loading websites.
Site speed is measured by taking a sample of your users (about 1%) and a simple average for every other metric measured. This means that the results are prone to outliers. The fact that a small sample size is used also makes the results provided questionable.
In order to get even more accurate results for site speed, simply increase the sample size to 100%. This means that all site users will be included in obtaining the metric. If you have a large site with large volumes of traffic, you can limit the sample to 10,000 hits per day.
2. Exit Rate
This metric uses an intuitive calculation method. It represents the percentage of page views that were the last in any session based on all page views. A high exit rate is an indication that your website is in trouble.
However, exit rate can often be misinterpreted. Some pages may exhibit a high exit rate such as those with content that is highly focused on conversion. Sites that also rank well for long tail keywords may also exhibit high exit rates. In these cases, a high exit rate would be a good sign. You should therefore judge exit rate based on the user intent on the particular page.
3. Conversion rate by Channel
Conversion rate is one of the most important metrics for any online marketer. However, it can often be misleading, especially when you consider how it is obtained. Google Analytics uses the last non-direct click and does not consider when the user returns as “direct” traffic.
Therefore, every channel is likely to have some conversions that may have occurred when the user returned as direct traffic. You should therefore interpret this metric alongside attribution reports and multi-channel funnels for a clearer picture.
4. Average Time on Page
This metric is useful when determining how well the content on your page is engaging your audience. It is calculated by taking the time spent across all pages to the last page.
If the visitor leaves the site and returns, it is assumed that there was no further time spent on the site. The metric also only considers visitors who exit the website without interacting with it. You can improve this metric by including more engagement events on your page e.g. scrolling.
What’s the point?
You need to take these data points with a pinch of salt. You can’t always trust them in their entirety but if you understand where the errors come in it can help you make better judgement calls with your data.
If you have any other input about Google Analytic metrics that would be useful to share, please let us know.