No More Pogo Sticking: Protect Users from Wasted Clicks

When people have problems finding content, both time and clicks are wasted hunting through extraneous pages on a site. The hub-and-spoke pattern of navigating from a routing page—a search-engine results page (SERP), section landing page, product-category page, or similar—to a page deeper in the site’s hierarchy, then immediately back to the routing page is referred to as pogo sticking.

Recently, I found myself pogo sticking through the Redbox website. Why, you ask, was I doing this? I had wanted to walk to my nearest Redbox location, to get a little exercise and avoid an extra trip in the car, and grab a movie to watch that evening. On the website, I searched for my specific Redbox kiosk location and was shown a list of movies to browse. Upon seeing a movie that interested me, I clicked to get more information only to find that it was not available to reserve at my chosen location. Disappointing. I returned to the list of movies to try another option and again it was not available. It became clear that this browse page contained numerous movies that were not available at my chosen location. This did not match what I had specifically asked for! The excess work and frustration nearly dissuaded me from renting a movie altogether—had it not been for others in my company wanting to watch a new movie, I would have just streamed something on Netflix.

When a company’s website makes customers think lovingly of the biggest competitor, something is wrong.

The Problem with Pogo Sticking

Pogo-stick behavior is often discussed in regards to people bouncing off a site and returning to an external search engine. While this pattern may be generated by a poorly designed landing page, high bounce rates could also be due to visitors who are not truly interested in the product or service offered, and thus are not valid prospective customers.

Within a website, pogo-stick behavior is an indication that people are struggling to find relevant content. Navigating repeatedly through the same pages quickly becomes tiresome, and is highly discouraging. Users in this situation may give up entirely, or settle with the most satisficing answer encountered during the arduous journey through the site. Because of the excessive effort exerted, these users are not likely to extend their visit for a second purpose, nor do they ever return. This demonstrates the interaction elasticity of websites, where a higher interaction cost results in lower usage over time.

Users pogo stick from a page because the content found upon arrival was disappointing—somehow the destination did not match the expectation set by the page leading to it. This mismatch between a link and its corresponding page chips away at the credibility of the website, and at the brand as a whole. People resent sites that trick them into spending a click while getting nothing in return. In user’s eyes, these are not only wasted clicks, but also wasted time.

Identifying Pogo-Stick Behavior Using Web Analytics

Most often, pogo sticking is discovered by directly observing users during usability tests. However, web-analytics tools can also help identify this behavior and monitor improvements once changes have been implemented. The process of examining the sequence of pages that a user has visited during a single session on a website is known as path analysis.

The tool needed to find this data may be named differently in various web-analytics platforms, but it should be available in each of them. Analyzing specific navigational paths within a website can be a time-consuming task, so it is best to first identify those pages that are candidates for pogo sticking. Suspects may include your homepage, landing pages for main sections of content, your site’s internal search-results page, and product-browse pages. Prioritize which pages you tackle first, based on their visibility to your audience (overall unique traffic) and their potential for improvement. (Some personal judgment will be required for the latter, but you’re likely to gain the most from fixing those pages within your conversion funnel that have a high exit rate.)

The most simplistic way to identify a page where pogo-stick behavior may be occurring is to look at routing pages with a high ratio of page views to unique page views. This measure indicates that many users repeatedly navigate to those pages. However, this number alone does not necessarily mean that users pogo stick or otherwise fail to find information.

The exact same click behavior can be indicative of a positive user experience instead of pogo sticking if users repeatedly follow links from a routing page because they find all the destinations interesting. Consider, for example, a newspaper homepage with many news stories. If a user clicks, say, five of the headlines and reads all those articles, then this is good, not bad. On the other hand, if a user clicked those exact same five headlines and was disappointed with every single article (because of misleading teasers), then it would be bad. Simply counting clicks won’t differentiate between these two scenarios.

To get a better picture of how users interact with a routing page and with the pages it links to, the data must be narrowed to the session level and exclude paths where the user visited several pages before returning to the routing page or when the user spent substantial time engaging with the destination pages. In other words, you want to include only patterns of the type X-Y-X, where X is a routing page and Y is a page linked from X.  By creating a segment identifying that path sequence, you can measure the percentage of users exhibiting this pattern of navigation, and monitor it over time.

Investigate Using Qualitative Methods

Once pogo sticking has been identified, follow up with qualitative research—usability testing—to determine what may be spurring this behavior. Are people looking for a page or some content that they expected to find but doesn’t actually exist (or at least, isn’t available through that page)? Did a link on the page promise cute pictures of kittens but instead presented users with a wordy article scrutinizing society’s infatuation with prepubescent animals? Or, did that browse page not clearly display key differentiating information for people to easily find the product that fulfills their need—like what happened to me on the Redbox website? Quantitative data from analytics cannot explain why a behavior occurs, nor how to improve the experience, but only if and where that behavior may be happening.

Here are some of the common problems that can cause pogo-sticking behavior, along with suggested solutions and research activities that can be used to uncover the best way to implement those solutions.

After fixing a pogo-sticking problem, you will probably observe an immediate decline in your page views. But this is good! Users aren’t wasting as much time and effort navigating to pages they don’t need, and so the overall page count drops. This is an example where a more nuanced approach to interpreting website analytics data is required than simply wanting ever bigger numbers. Additionally, if you track analytics data for returning visitors you will likely find an increase in user loyalty, driven by improved usability now that people can easily find what they’re looking for. Higher loyalty will again drive increased page views over the long term. But short-term numbers will be down, and that’s positive because it means that you stopped annoying users with wasted clicks.

Learn more tips on using analytics data to identify usability issues during our full-day course on Analytics and User Experience.