A Web Analytics Primer - What Does It All Mean?

Web Analytics Primer

Cardinal Path article

I remember, when I first began my transition into web analytics, having been somewhat confused at all of the metrics on offer in our Web Analytics Suite. I needed to figure out and learn what visitor behaviors each of them existed to describe, how they fit into the big picture and why they were so important in describing the health of a website.

This article is for the beginners, anyone who is making the perilous journey into the treacherous realm of online marketing, and all of the developers and designers who are curious about measuring and improving their websites based on good old data. It aims to provide a brief definition of each of the major web analytics metrics, what they mean, why they matter, and which types of websites each are most relevant to.

Pageviews

The number of times any page on a website has been loaded in a visitor's web browser, and the analytics code has successfully recorded the fact that page was loaded.

The number of page views will be an important metric to consider - whether the goal of a website is lead generation, e-commerce, disseminating information, or advertising - as it is a general indicator of demand for a website and the content on it.

Note that high page views is not always a good sign - a high count of pageviews combined with a low time on page (see below) could be a warning that visitors are not finding what they're looking for on your website, and are searching extensively but fruitlessly for it.

Visits

The number of times any user has loaded at least one page on a website. In many analytics suites (including Google Analytics), this terminates a visit after 30 minutes of inactivity. If a visitor returns to a website after they have not accessed any of it's pages for more than 30 minutes, that will be counted as an additional visit.

The number of visits is important to keep in mind, as it can assist in determining how many chances a website has had to convert its visitors into prospects, buyers, readers, or successful referrals to other websites.

Why bother with this? The number of conversions versus conversion 'chances' is a crucial comparison to make when determining the success or failure of a website in achieving core business objectives.

Conversion Rate

The number of conversions of visitors to prospects, buyers, readers, or referrals divided by the number of visits to a given website.

This is very likely the most important of all metrics, even though it doesn't tell you very much on its own. What it does tell you is how many times your visitors did what you wanted them to - for your website.

Bounce Rate

The percentage of visitors who have accessed a website, loaded only one page, and then left. The lower this number is, the better - in most cases. A 'bounce' can be trigged by a visitor who leaves a website, visits another website, and does not return to the first website within 30 minutes. A 'bounce' can also be triggered by a visitor who visits a website, loads only one page, then closes their browser and doesn't reopen that browser and visit the website again within 30 mintes. Each page on a website will have a different bounce rate attached to it.

It is important to know the bounce rate because it can help to indicate which pages are the most 'repulsive' to your visitors, or which repel the most visitors off of your site when viewed alone. As many children of the 80s learned, 'knowing is half the battle'. It's this half of the battle that helps you fight the other half: fixing the issue.

The bounce rate tends to be more important on content-reliant and e-commerce websites than on others. For content-reliant websites, it means that the content is not being consumed, or that the piece of content viewed (or the page in which it is presented) is not doing a good job of tempting visitors to consume other pieces of content.

For e-commerce websites, a high bounce rate may be worse because it means that visitors haven't even viewed their shopping carts or tried to buy - they left as soon as they saw the website or the item they came for.

Time on Page (ToP)

The amount of time between a particular visitor loading a page from a website, and then loading a second page from that same website. This metric has a maximum value of 30 minutes (see Visits above). Each page on a website will have a different value for time on page attached to it.

On a content-reliant website, a high time on page may mean that a piece of content is sufficiently engaging as to spur the visitor to read the whole thing. An overly high time on page, however, could also signal that the content is unclear or confusing - especially if paired with a high exit rate (see below).

On an e-commerce website, an unusually high time on page for individual item pages, or any of the checkout pages, can indicate either a high degree of customer uncertainty in making a purchase decision, or that the process is too complicated and/or confusing as before. Of course, if coupled with a high exit rate, the second conclusion can be more likely.

View/Visit Ratio (VVR)

The number of pageviews divided by the number of visits to a particular website.

This metric, along with the average time on page, can help determine how much time the average visitor spends consuming content on a given website. The view/visit ratio can also help to work out how much content is being viewed on a website, which can be an important guide for content-reliant websites and blogs.

Entrance Rate and Landing Page

The term 'entrance rate' refers to the percentage of visitors for whom a particular page was the first one they visited during their website visit. The first page visited by a particular visitor on a given website visit is referred to as the 'landing page'. Each page on a website will have a different entrance rate associated with it.

The entrance rate for a content-based website may be higher on pages with actual content on them, as people are more apt to share links to individual content articles of interest rather than to the website itself. The same can also apply to e-commerce websites, where individual items are suggested by previous visitors to their friends or followers. The entrance rate is generally not as relevant for lead-generating websites.

Exit Rate and Exit Page

The exit rate is a cousin of both the bounce rate and the entrance rate: it is subtly different from the first, and the opposite of the second. The 'exit rate' refers to the percentage of visitors for whom a particular page was the last one they visited during their website visit. The last page visited by a particular visitor on a given website is referred to as the 'exit page'. Each page on a website will have a different exit rate associated with it.

A high exit rate for individual articles on a content-reliant website can indicate an article that does not succeed at leading into another article or generating advertisement revenue. A low exit rate, however, can suggest the opposite. The exit rate can be combined, as seen above,

The exit rate can be of some importance to e-commerce and lead-generation websites alike - high exit rates on the purchase confirmation or contact form confirmation pages, respectively, can indicate a great degree of success.

Closing Thoughts

Note that comparisons based on the above metrics should be made only between similar websites with similar purposes supporting similar business objectives operating in a similar vertical. These metrics are the most valuable when used together, and can reveal many insights if properly combined. It's also very important to ensure that your web analytics tool or system is working and set up properly before jumping to major conclusions.

If you're a web analytics beginner who has gotten some value out of this post, or if you're a web analytics guru who has a few suggestions for this post or for future posts for beginners, please let us know in the comments section below.

Thanks for reading!

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Scott Kennedy | November 2012

Great article... I am beginning my voyage in the deep sea of digital analytics and found this article very straight forward and easy to consume. I would be interested to see further posts that speak to "strategies on breaking into the web analytics arena".

Thanks!

scott moss | February 2013

Just starting out and this helped me out a bunch. Thanks.

Jim Brown | September 2013

I am a fresher in the field of web analytics. I am sure the tips provided in your post will help me a great deal

Anonymous | January 2014

Your list of reasons for why a visitor to a website may stay on one site/page view etc. for a "long" or "short" interval misses ordinary human behaviours...example, interrupted to converse with another person, gets up and leaves screen to pour coffee, brews fresh coffee or reads offline something else, or otherwise gets distracted while online connection is not terminated. Perhaps analytics software should include the general term "X" (for the unknown) in the initial definition of any cause, and then the analyser may choose to define X as being zero. Doing so would remind marketing teams that "software logs' data" do not necessarily reflect the primary causes of how a visitor spends time on a website. That is, not all choices made/behaviours measured reflect a choice made on the basis of information necessary/relevant to/a buyer's needs/wants. Perhaps you have already addressed this aspect of data collection in a discussion of the usefulness of including a short "How Useful Did You Find This Page?" survey (optional for users to reply), preferably not in the form of a popup ad, perhaps as a clickable element. Thanks for your information.

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