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| Source: www.similarweb.com, April 13, 2017 |
Visits - All of the data in the table above is averaged based
upon visits. A visit is simply a session where a visitor is on your website and
the two terms are often used interchangeably, whether the visitor only goes to
one page or visits 100 pages. If someone goes to your website, visits five
pages, leaves, then comes back an hour later, that is considered two visits, or
sessions (even though it’s one visitor).
Average Visit Duration - The average visit duration is
exactly what it sounds like; an average of how long each visitor stays on a
particular website per visit, from the time they get to your site until the
time they leave your site. Leaving your site can be through a number of ways
including “leaving” by closing their browser, clicking the “back” button after
first arriving on your site, or clicking on a link that takes them to a
different site somewhere else on the internet.
Pages / Visit - Every page a website visitor visits is counted
as a “Page View”. The “Pages / Visit” column is an average of how many Page
Views the average visitor views, and since some people visit a site once while
others are repeat visitors, the Pages per Visit metric is based on the pages
per visit per session. If someone visits your website, visits five pages,
leaves, then comes back the next day and visits five more pages (even if
they’re the same pages), that would result in 10 Page Views but an average of 5
pages/visit.
Bounce Rate - The Bounce Rate is the percentage of visitors
who leave a website after viewing only one page. Let’s say, for example,
someone wants to buy a red sofa and they’re very particular that it must be
red. Let’s say that person goes online and searches for “red furniture”. If from the search
results they click on a link that takes them to a furniture company’s website
that only sells
blue furniture, they would likely click the “back” button on their
browser because they knew immediately they weren’t going to find a red sofa on
the blue furniture company’s website. That visitor is said to have “bounced”
because they only visited the page they landed on and didn’t go to any other
pages on that site. Higher Bounce Rates aren’t always a bad thing, as we’ll see
below.
Making Sense of the Numbers
You’ll notice in the table above
that several values are circled in red and numbered (1)
through (8). This is how each will be referenced
throughout this section for easier reference. It’s also important to keep in
mind that the sites listed above are extremely popular websites and the metrics
you see are not what you should expect from your own site. Google for example
has over 2 trillion searches per year. Facebook has over 1 billion active
monthly users. Don’t try to take the numbers from the table above out of
context because your website is NOT Google, Facebook, or any of the other sites
you see here. The purpose of this is simply to show where some differences in
metrics come from.
The Myths,
De-Mystified
Most people who don’t fully
understand statistics, how website statistics are measured, or consider human
behavior in a “big picture” context often make certain assumptions that aren’t always
true. For example, a longer Visit Duration isn’t always a good thing. Consider
some of the following when examining statistics for your own website:
Average Visit Duration is one metric that most people assume the
longer the duration, the better. While this is often true, there are many
scenarios where it’s not the case. Take a look at items (1), (3), and (5) and the websites each one corresponds with. Now
think about how people typically use each of those sites. Facebook is known as
a site which people tend to visit out of habit or when bored. They tend to
scroll through their timeline, click on a few friend’s pages, make some
comments, share an article or two, and leave. An average of around 16 minutes (1) probably seems within the normal range to most
people. Youtube is where people go to watch videos and listen to music, so
naturally the average visit duration is going to be substantial...over 24
minutes in this case (3). Compare that to
Wikipedia at just over 4 minutes per visit (5)
and Youtube has more than five times the duration of Wikipedia, so why is that?
Again, this goes back to behavior.
People visiting Wikipedia are
generally researching some topic they want to know something about. Let’s say
you want to know the population of China. A quick search yields a Wikipedia
page at the top of the results, and people know that’s a site they can go to in
order to find out what they’re looking for, so they click on it. The information
is easy to find on Wikipedia, the visitor gets everything they need quickly,
and leave if that’s all they wanted to know.
The thing to note here is that
Average Visit Duration can be low because most people simply don’t like your
website, or it can be low because your site is structured so well that visitors
are able to find the information they need very quickly (e.g. if they’re just
looking for your phone number or address). In the latter case, a lower Average
Visit Duration is better. Conversely, a high Average Visit Duration may
indicate that people really like your site content and spend time reading it,
or that they can’t find what they’re looking for. A visitor to one car dealer
website may have to click on every vehicle to see the mileage, whereas another
car dealer website may have a filter to display only vehicles with less than
50k miles. The second site in this example would yield a shorter Average Visit
Duration, but it’s actually a good thing for the visitor in this case.
Pages per Visit can be looked at in a similar fashion. Wikipedia
has an average of only around 3 pages per visit in our table above (6) while Facebook has an average of over five times
that amount at 15 pages per visit (2). Most
people assume that more pages per visit is better, and often it is, but it’s
not always the case. Let’s go back to how the average person uses Facebook
versus Wikipedia. Facebook is a site which people tend to browse through,
clicking on multiple pages per visit. Wikipedia, as mentioned in the example
earlier, is typically the end point for someone who is searching for very
specific information. Once they get the info they were looking for, they don’t
typically browse through additional topics unless they’re related to the
original topic. This would explain the gap in pages per visit between those two
sites. Again, these numbers need to be taken within the context of user
behavior on a macro level, like the difference you would expect in how many
pages someone viewed while browsing through an old family photo album versus
how many they viewed while browsing through the dictionary. They’re both
technically books, but used very differently.
Bounce Rate, like the other two metrics being discussed, is also a
number that can be better if it’s higher or better if it’s lower, therefore
site usage is important to keep in mind. In the example of Live.com the bounce
rate is extremely low at 13% (8). When you
consider that people going to Live.com are going there for the very specific
purpose of logging in to their Microsoft account, it makes sense that almost
everyone going there does go to at least one more page before leaving.
Similarly, many sites linking to
Youtube do so in such a way that the visitor knows ahead of time they’re going
to end up visiting Youtube by clicking on the link, and as you’ve probably
seen, Youtube has an entire column to the right of their videos which shows
related videos, encouraging and making it very easy for visitors to go to at
least one more page/video before leaving the site. This sort of site structure
helps to lower the bounce rate to just 19% for Youtube (4).
The bounce rate for Wikipedia is
incredibly high with almost half of the visitors leaving after viewing just one
page (7) and as with everything else, this is a
direct result of usage patterns. Let’s go back to how most people use Wikipedia
(searching for a specific topic and clicking on the Wikipedia result in the
search engine). Since they’re often searching for something so specific, they
land on the Wikipedia page for that topic, get the info they need, then leave
the site. If you’re looking for the population of China and find it on
Wikipedia as in our example, you’re pretty unlikely to get sidetracked and
visit other pages on the Wikipedia site. You’re almost 50% likely, as the
bounce rate suggests, to leave after finding the info you sought.
With the car dealer website
example, consider that many visitors will arrive on your site after seeing one
of your vehicles on a 3rd party classified site. Think of how many visitors
are likely to click on a vehicle, let’s say on Craigslist, get taken to your
site, either looking for or seeing something about that car they didn’t see
before (e.g. if you don’t have a price on Craigslist they may click to see if
you have one on your website). It’s typical behavior for that person to hit the
“back” button on their browser and get back to looking at the other vehicles on
that classified site, especially if they’re looking for something very specific
that your vehicle doesn’t have. Of course you want every single visitor to buy
a car but that’s not reality. This isn’t necessarily a bad thing when bounce
rates are “high” (whatever you want to consider high). It could simply mean
that visitors are finding the info they want quickly, without having to jump
through a bunch of digital hoops (links) to find it.
Summary
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