Web Analytics Interpretation 101

Many people know that they need an analytics tool to measure performance on their Web site or search marketing campaign. Getting data is one thing. So, too, is looking at the results. But interpreting it and understanding the deeper meaning is something else.

As analytics tools become more complex, it will take special training and learning to set up analytics correctly. And more time and effort will be needed to interpret the data.

When Google Analytics first showed up on the scene, it was relatively straightforward. Today, it’s evolved into a formidable Web analytics tool, requiring a little more training and skill to truly leverage all it has to offer compared to when it first launched. The same applies to other analytics tools as well. For purposes of this column, let’s dig into Google Analytics because many people use it.

Get Your Team Involved

First, set aside the time and get as many team members involved in reviewing analytics data. Team members with different roles will see things and ask questions that will help draw out the real meaning behind the numbers and provide better context. If you just take quick peeks at your analytics reports, you will only get surface information and might miss out on wonderful opportunities.

For example, one time during a regular analytics review meeting, our team and client discovered some irregularities in visitor behavior. As a result, we made a couple modifications on the Web site to see if we could correct the problem. A month later, sales increased 600 percent. How many opportunities like that have been missed because a business didn’t take the time to truly interpret the analytics reports with its team?

Look Beyond the Single Metric

Next, try to look past isolated numbers and look at them in context to other metrics.

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For instance, in the above example, there are 22,125 page views to a specific page on your site. That doesn’t tell you much by itself. But looking at it in context to other metrics gives you a better picture. Notice that your bounce rate is 38.24 percent. This means that about 40 percent of your visitors left this page without looking at any other pages.

Also, by comparing the number of page views against the site average, we learn that this page only accounts for 5.77 percent of all page views.

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If we compare the number of page views against a previous month, we learn that there was a 23.65 percent increase in page views. We also learn that our bounce rate was 22.72 percent lower last month. Something obviously happened to increase the bounce rate. What was it? How do you get back to a lower bounce rate?

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We get a better picture of what’s really going on when we analyze pieces of information in context to other data and to other time frames. With these insights, you and your team can make more intelligent changes to your site or search campaigns that will help you achieve better performance. Additionally, you may learn valuable lessons that will keep you from repeatedly making the same mistakes.

Looking at Trends

Another powerful feature of analytics programs is the ability to look at data over a period of time. You may look at data by week, by month, even by year. Visualizing and measuring trends provides better context to the data as well.

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In the above example, we note that there was a spike in activity at the beginning of August and the beginning of September. Also notice that there are mini spikes during the middle of each week. Why is that? Are there special events or circumstances leading to this? Can they be repeated? Asking lots of questions is always a good practice as you attempt to interpret reports.

Interpreting Conversions and Goals

A primary use of an analytics tool is to set up goals and then track performance. Being able to understand and report on ROI (define) factors is vital. To understand visitor behavior, you must interpret these reports. Then you’ll be able to make the necessary course corrections to improve performance.

In Google Analytics, you can set up conversion goals to track performance over time. If you’re interested in learning more about setting up goals in Google Analytics, this instructional post outlines the process step by step.

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In the example above, a date range of about three months has been selected. More than one goal has been set up to track performance from a primary goal and then a secondary goal.

Maybe you have a soft goal for a visitor to download some information on your site while your primary goal is for a visitor to make a purchase. It’s also good to place a value on achieving each goal so you can see how it relates to the bottom line. In essence, when you add up all of the behavioral steps your visitors make, you can better track ROI.

We can see that Goal 1 was slightly more successful than Goal 2. Our overall conversion rate for both goals is slightly more than 45 percent. Additionally, the monetary value for these two goals is about $17,000.

You can drill down into each goal to see more detailed performance metrics. Also, you can view this over different date ranges to better understand seasonality or event related trends.

Note: There are methods and insights that analytics tools offer and there are hundreds of reports that help us to look at data in different ways. While you may be satisfied with just looking at the main page or dashboard, great opportunities exist if you do more than just look at the basic information. Consider learning more about what your visitors are doing on your site and how you can improve on that relationship.

As always, if you have any success stories or other tips that have worked for you, please include them in the comments below for the benefit of all readers.

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