bounce-analytics

Understanding Bounce Rate

One of the most misunderstood metrics for web analytics is “bounce rate.”

Google defines bounce rate as “the percentage of single-page sessions (i.e. sessions in which the person left your site from the entrance page without interacting with the page)” (source).

In layman’s term, bounce rate is the rate visitors visit 1 page and do not view any other pages — one-and-done.

Like with other metrics, we can’t draw any conclusions based just on the bounce rate %, but rather, we use it along with other data to help us assess a situation. Here are many ways that bounce rate can be interpreted and many other things to be aware of when analyzing bounce rate.

  1. “Bounces” are normal

Bounce rates, in general, are a measure of engagement. Sometimes you engage, sometimes you don’t. Bounces are normal — you cannot get 0% bounce rate.

The following is from a small, e-commerce website.

bounce1
Figure A

A 49.88% bounce rate means that pretty much half of all visitors do not go beyond the first page visited. Why is that? We can’t know without polling the visitors themselves. The common explantation is they weren’t interested.

For example, in a clothing store at a mall, there will be window shoppers and people who walk in with no intention of buying. This could be considered similar to a “bounce” for them, and again, it’s normal and part of doing business —  not all visitors are interested in your content.

2. Related content will lower bounce rate

These are the numbers from a blog that does not focus on any one particular topic:

bounce2
Figure B

The ~90% bounce rate is quite high, but it is because the blog entries are almost entirely unrelated. This means that if someone were to land upon a blog entry after searching for something on Google, they might leave right after, simply because there is nothing else on the site they care to read about.

How might this happen? Here’s an example:

Going back to the mall example, let’s say instead of a clothing store, we look at a knick-knack store, like Spencer’s Gifts. The store, if you don’t know, is full of random items, ranging from gag gifts to t-shirts of death metal bands. Although they are able to stay in business, they do not have as much success as a store with a theme like Forever 21, which sells clothes targeting young women, thus increasing the chance of multiple purchases and return visits.

3. Paid traffic should have a low bounce rate

When you have a website, there will inevitably be a lot of “accidental” traffic — people are looking for one thing, end up on your site, and leave when they realize it’s not what they are looking for.

When traffic is paid for, however, the intention is to market to a target audience. When this happens, the content should appeal to the visitor from this channel, thus bounce rate should be lower.

Figure D
Figure D

In Figure D, we see the various sources of traffic and their corresponding bounce rates. While the bounce rate for the site is about 80%, averaged, it is actually much lower from the advertising source: 29.27%. Moreover, the traffic from the advertising source spent 7 minutes and 4 seconds on the site, when the average session for all traffic was 1 minute and 30 seconds. When it comes to targeting an audience, both these metrics correspond to a job well done.

4. There is a lot of fake traffic out there

In addition to accidental traffic, the biggest factor that skews our bounce rate data is fake traffic.

Fake traffic is not performed by an actual person, but rather, by a bot. This bot might be friendly, like the ones that Google use to browse and index websites. Or it can be spammy, like Figure E:

Figure E
Figure E

If you were to enter any of those 5 URLs in Figure E (but don’t do it!), you would end up on some bizarre website. These are just another spammy technique going around the web world. How can we tell without even visiting the websites? Because 4/5 have a 100% bounce rate.

While 0% bounce is unlikely for a large sample size, equally unlikely is a 100% bounce rate.

So if you are a webmaster to a large site, you should filter out these results in order to preserve the integrity of your data.

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