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I spent five years responsible for web analytics for a major ad-monetised content site, so Im not immune to the unique challenges of measuring a content consumption website. Unlike an eCommerce site (where there is a conversion event) content sites have to struggle with how to measure nebulous concepts like engagement. It can be tempting to just fall back on measures like time on site, but these metrics have significant drawbacks. This post outlines those, as well as proposing alternatives to better measure your content site.

So whats wrong with relying on time metrics?

1. Most business users dont understand what they really mean

The majority of business users, and perhaps even newer analysts, may not understand the nuance of time calculations in the typical web analytics tool.

In short, time is calculated from subtracting stamps. For example:

Time on Page A = (Time Stamp of Page B) (Time Stamp of Page A)

So time on page is calculated by subtracting what time you saw the next page from what time you saw the page in question. Time on site works similarly:

Time on Site = (Time Stamp of call) (Time Stamp of call)

A call is often a page view, but could be any kind of call an event, transaction, etc.

Can you spot the issue here? What if a user doesnt see a Page B, or only sends one call to your web analytics tool? In short: those users do not count in time calculations.

So why does that skew your data?

Lets take a or website, with a 90% bounce rate. Time metrics are only based on 10% of traffic. Aka, time metrics are based on traffic that has already self-selected as more interested, by virtue of the fact that they didnt bounce!

2. They are too heavily influenced by implementation and technical factors unrelated to user behaviour

The way your web analytics solution is implemented can have a significant impact on time metrics.

Consider these two implementations and sets of behaviour:

  • I arrive on a website and click to expand a menu. This click is not tracked as . I then leave.

  • I arrive on a website and click to expand a menu. This click is tracked as an event. I then leave.

In the first example, I only sent one call to analytics. count as a bounce, and my time on the website does not count in Time on Site. In the second example, I have two calls to analytics, one for the page view and one for the event. I no longer count as a bounce, and my time on the website counts as Time on Site. My behaviour is the same, but the websites time metrics are different.

You have to truly understand your implementation, and the impact of changes made to before you can use time metrics.

However, its not even just your sites implementation that can affect time metrics. Tabbed browsing default behaviour for most browsers these days can skew since a user who keeps a tab open will keep ticking until the session times out in 30 mins.

Even the time of day your customers choose to browse can also impact time on site, as many web analytics tools end visits automatically at midnight. This isnt a problem for all demographics, but perhaps the TechCrunches and the Mashables of the world see a bigger impact due to night owls!

3. They are misleading

Its easy to erroneously determine good and bad based on time on site. However, I may spend a lot of time on a website because Im really interested in the content, but I can also spend a lot of time on a website because the navigation is terrible and I cant find what I need. There is nothing about a time metric that tells you if the time spent was successful, yet companies too often consider more time to indicate a successful visit. Consider a support site: a short time spent on site, where the user immediately got the help they needed and left, is an incredibly successful visit, but this wouldnt be reflected by relying on time measures.

So what should you use instead?

Rather than relying on passive measures to understand engagement with your website, consider how you can measure engagement via active measures: aka, measuring the users actions instead of time passing.

Some examples of active measures on a content site:

  • Content page views per visit. A lot of my concerns about regarding time measures also apply to page views per visit as a measure. (Did I consume lots of page views because Im interested, or because I couldnt find what I was looking for?) For a better page views per visit measure of engagement, track content page views, and calculate consumption of those per visit. This exclude navigational and more administrative pages and reflect actual content consumption. You can also track what percentage of your traffic actually sees a true content page, vs. just navigational pages.

  • Ad revenue per visit. While this is less a measure of engagement, businesses do like to get paid, so this is definitely an important measure for most content sites! It can often be difficult to measure via your analytics since you need to not only take account the page but what kind of ad the user saw, whether was sold or not and what the CPM was. However, its okay to use informed estimates. For Click-through rate to other articles. A lot of websites will include links to related articles or you also might be interested in. Track clicks to these links and click rate. This will tell you that users not only read an but were interested enough to click to read another.

- I saw 2 financial articles during my visit. We sell financial article pages at an average $10CPM and have an estimated 80% sell through rate. My visit is therefore worth 2/1000*$10*80% = 1.6 cents. This can be a much more helpful measure than page views per visit since not all page views are created equal. Having insight content consumed and its value can help drive decisions like what to promote or share.

  • of shares or share rate. If sharing is considered important to your business, clearly highlight this call to action, and measure whether users share content, and what they share. Sharing is a much stronger indicator of engagement than simply viewing. (You wont be able to track all shares, for example, copy-and-pasting URLs wont be tracked, but tracking shares will still give you valuable information about content sharing trends.)

  • Download rate. For example, downloading PDFs.

  • Poll participation rate or other engaging activities.

  • Video Play rate. Even better, track completion rate and drop-off points.

  • Sign up and/or Follow on social.

  • Account creation and sign in.

If youre already doing a lot of the above, consider taking it a step further and calculating visit scores. For example, you may decide that each view of a content article is 1 point, a share is 5 points, a video start is 2 points and a video complete is 3 points. This allows you to calculate a total visit and analyse your traffic by high vs low scoring visitors. What sources bring visitors to the site? What content topics do they view more? This is more helpful than 1:32min time on site!

By using these active measures of user behaviour, you will get better insight than through passive measures like time, which will enable better content optimisation and .

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