Is Analyzing Time on Site a Waste of Time?

Assume your average time on site is 3:15. Is that a good thing, bad thing or “why should I care” thing?

Most folks believe more time on site is better — it means customers are viewing more products, reading descriptions and reviews word-for-word and “engaging” with your content.

But time on site is a poor indicator that your site is doing well. Perhaps you do offer fantastic product information, videos, product guides, customer reviews etc. and visitors love the content you provide – it helps them decide what they want to buy offline, from someone else. Or, customers comparison shop and leave your site open in its browser along with 6 other tabs.

Maybe your site is so difficult to navigate and find product, a lower time on site would actually indicate better customer experience and smoother checkout.

Don’t forget that average time on site is just an average. It can be segmented out by visitor type, referring site/campaign or by keyword, for example.

You would expect time on site to be lower when a visitor lands on a specific product page (rather than your home page) from a shopping engine (having compared the product and price against competing offers) or by a specific keyword (like “Marvin the Martian basketball”). If a customer doesn’t need to search or browse to find a product they want, shouldn’t a short time on site be better?

Not necessarily — a short time on site could indicate the customer never bothered to complete the purchase, or bailed when she hit your checkout page with required registration. It could also mean customers are ignoring your cross-sell suggestions and don’t care about your free-shipping-over-$100 offer.

And don’t forget, time on site cannot account for the visitors who view only one page. Unless a visitor loads a second page on your site, your analytics program will not calculate the time on the first page. That’s why you find many pages have an average time of 0.00.

Though time on site is usually explained in any Web Analytics 101 material, I believe time on site is a broken metric that is not important for online retailers. Longer or shorter time on site does not indicate site effectiveness.

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12 Responses to “Is Analyzing Time on Site a Waste of Time?”

  1. I think time on a website is worth looking at. If it is very low I would think that should tell you, the website has major issues with it. Other than that I would not pay much attention to it. There are more important metrics to look at like sales numbers for one.

    I chart monthly sales plus now I can compare sales numbers year to year. So I can compare month against month, because each month has a different expection of sales.

    So if your sales are going up each year compared to each month, you are doing something right.

  2. This is precisely why social media is turning into voodoo marketing — this specific issue is at the core of discussion around viable, useful metrics.

    In the end “time on site” is a backwards metric in my view. It’s like the page view. It creates more questions and, thus far, in terms of standards development it’s been a FAILURE. Systems/software designers and users alike cannot come to agreement on what constitutes a “video view” let alone PROVE the ULTIMATE goal: creating meaningful customer behavior.

    Creating meaningful customer behavior is, in this new economy, should be (IMHO) defined as:

    An organized series of prompts that ultimately leads to a sales lead or transaction.

    If the time-on-site/”engagement” doesn’t actually CAPTURE customer intent (ie. is the customer’s need immediate? latent?) and then plug it into an ORGANIZED SYSTEM (call it CRM if you’d like) then the “engagement” or “time on site” is just more waste — “branded entertainment”.

    Then again, DrsFosterSmith http://budurl.com/ljpl likely disagrees with my hard core view of direct response marketing… and they’re direct marketers too! Very successful ones in the pet industry who feel that “time spent on site” translates to “increased trust” in a trust-based retail niche. Trust is “enough” for them and time spent on site is a measure of it.

  3. Interesting post, but surely time on site is just one ingredient in the web analytics pie.

    Generalizations like “Longer or shorter time on site does not indicate site effectiveness” really need to be qualified, imo.

    Surely the answer is to do better analysis, rather than just throw the metric out. That means segment, segment, segment.

    For instance, to find out if it *does* indicate effectiveness, surely you would just segment out your quality customers from the riff-raff and see if time on site is different.

    Time on site could be the same for successful users who browse lots of catalog or product pages, and unsuccessful users who browse a lot of support pages, but again, segment them out and find out what’s going on.

    If it turns out that unsuccessful users do have a lower (or higher) time on site, then that gives you a clue that something is hindering their experience – maybe they’re sending time looking for something they can’t find again, or hitting a road block (poor navigation, for eg) & leaving. Segment them out and see if you can uncover what it is :)

  4. I think looking at it on it’s own can be deceiving – as it’s an average, looking at this overall average does not really give you much insight.

    Segmenting this measure can prove useful though – checking things like average time online for PPC visitors (and into specific campaigns) can help to detect potential clickfraud and poor quality visitors. Likewise, running this value against various organic keyword referrals, or specific landing page visitors can help to identify if some of these are performing poorly with very little time online.

  5. @Adam and all

    You are on the money talking of segmenting – no one metric, average or absolute, can have relevance out of context nor be meaningful outside of meaningful context.

    To take context further, segmenting can also be done by metric (eg page views, conversion rate, etc) in addition to by dimension (campaign, keyword, landing page – by data values)

    Think of visits of 2 minutes with 2 pv’s vs. those with 5 pv’s.

    @Jeff
    Its not the metric that is a failure – very few metrics are (something like “hits” may be).
    Taking anything out of context is en route to failure.

    Brian Katz – Analytics – VKI

  6. Here is a fresh way to look at Time-on-Site by asking 2 questions:

    1) If you wanted to change time on site would you want to increase it or decrease it ?

    2) How would you do that (increase or decrease) ?

  7. Yes, it is a valuable metric, but not the only metric.

  8. I agree that the way that Time on Site and Bounces are recorded is somewhat flawed by design. It is the nature of the mechanisms that collect clickstream data that define these metrics.

    Almost two years ago (!), I started to think about a new framework to link Time on Site and Bounces, since they are so closely related. This framework also develops a new way of calculating Time Spent on Site, using the same technique that demographers use to measure Average Life Expectancy. I wrote an introductory article here, check it out:
    http://www.tomsanalytics.com/2007/09/a-new-approach-to-the-time-spent-on-site-metric/

  9. Hi I was researching on the subject of time on site, and I ended up here.

    I find my time on site to be extremely high. According to Alexa it is over 40 minutes. I see ESPN for example is 6 minutes.

    I have a good community that debates alot on my site and I am sure I got a good core that boost up these stats, but I just can’t see it being that high.

    http://www.alexa.com/siteinfo/http%3A%2F%2Fmmanouvelles.com#

    I do not really have a question other then do you think 40 minutes is imposible?

    Thank you

    • What do your analytics say? I wouldn’t go off of Alexa data. They collect their stats through their toolbar and it’s a certain type of visitor that would install their toolbar. For example, if your forum is about internet marketing, that might explain the higher time on site stats from Alexa users.

  10. [...] comme le souligne bien un article de Linda Bustos sur Get Elastic [lien an anglais], que le temps passé sur un site soit court, moyen ou long n’a aucun sens en [...]

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