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The Bounce Problem: How to Track Bounce in Simple Landing Pages

Last updated on July 5, 2017

Introduction

This post applies to cases satisfying two conditions.

First, you have a simple landing page designed for immediate action (=no further clicks). This can be the case for many marketing campaigns for which we design a landing page without navigation and a very simple goal, such as learning about a product or watching a video.

Second, you have a high bounce rate, indicating a bad user experience. Bounce rate is calculated as follows:

visitors who leave without clicking further / all visitors

Why does high bounce indicate bad user experience?

It’s a proxy for it. A high bounce rate simply means a lot of people leave the website without clicking further. This usually indicates bad relevance: the user was expecting something else, didn’t find, and so leaves the site immediately.

For search engines a high bounce rate indicates bad landing page relevance vis-à-vis a given search query (keyword), as the user immediately returns to the SERP (search-engine result page). Search engines, such as Google, would like to offer the right solution for a given search query as fast as possible to please their users, and therefore a poor landing page experience may lead to lower ranking for a given website in Google.

The bounce problem

I’ll give a simple example. Say you have a landing page with only one call-to-action, such as viewing a video. You then have a marketing campaign resulting to ten visitors. After viewing the video, all ten users leave the site.

Now, Google Analytics would record this as 100% bounce rate; everyone left without clicking further. Moreover, the duration of the visits would be recorded as 0:00, since the duration is only stored after a user clicks further (which didn’t happen in this case).

So, what should we conclude as site owners when looking at our statistics? 100% bounce: that means either that a) our site sucks or b) the channel we acquired the visitors from sucks. But, in the previous case it’s an incorrect conclusion; all of the users watched the video and so the landing page (and marketing campaign associated with it) was in fact a great success!

How to solve the bounce problem

I will show four solutions to improve your measurement of user experience through bounce rate.

First, simply create an event that pings your analytics software (most typically Google Analytics) when a user makes a desired on-page action (e.g. video viewing). This removes users who completed a desired action but still left without clicking further from the bounce rate calculation.

Here are Google’s instructions for event tracking.

Second, ping GA based on visit duration, e.g. create an event of spending one minute on the page. This will in effect lower your reported bounce rate by degree of users who stay at least a minute on the landing page.

Third, create a form. Filling a form directs the user to another site which then triggers an event for analytics. In most cases, this is also compatible with our condition of a simple landing page with one CTA (well, if you have a video and a form that’s two actions for a user, but in most cases I’d say it’s not too much).

Finally, there is a really cool Analytics plugin by Rob Flaherty called Scrolldepth (thanks Tatu Patronen for the tip!). It pings Google Analytics as users scroll down the page, e.g. by 25%, 75% and 100% intervals. In addition to solving the bounce problem, it also gives you more data on user behavior.

Limitations

Note that adding event tracking to reduce bounce rate only reduces it in your analytics. Search-engines still see bounce as direct exits, and may include that in their evaluation of landing page experience. Moreover, individual solutions have limitations – creation of a form is not always natural given the business, or it may create additional incentive for the user; and Scrolldepth is most useful in lengthy landing pages, which is not always the case.

I’m into digital marketing, startups, platforms. Download my dissertation on startup dilemmas: http://goo.gl/QRc11f

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