Interaction Insights with CrazyEgg

Share these actual insights

A few months ago I started getting questions from my colleagues on how the could use web analytics tools to gain insights into what and where the visitors clicked on individual pages.

Now, most of us know that many web analytics pages come with a ‘overlay’ functionality with which you can quickly get a glimpse at where visitors click. I would quickly like to point out a better way to measure and analyze interaction.

Tracking Clicks, where others fail

In a previous article, I conducted a interview with Neil Patel, founder of KISSmetrics and CrazyEgg. CrazyEgg is a tool that I have been using for some time to measure and analyze interaction on a page, interaction in this case being ‘clicks’. Measuring ‘clicks’, according to CrazyEgg, should be just that, measuring clicks.

Unfortunately, there are two fundamental problems with these functionalities in many of the web analytics packages today. Let me point them out to you:

    1. Clicks are not always made on links – in other words, visitors can click on the page many times without actually clicking on a hyperlink. Web analytics packages today will only measure and display data on clicks on hyperlinks. What if a visitor is clicking on a page element that does not contain a link? How will you know that although the element motivates a clicking behavior, there is no interactivity (ie. hyperlink) included with the element? Also, if you don’t tag your links uniquely (ie. 2 links on 1 page both containing the same URL) then you won’t be able to distinguish which one of the two links was used the most.
    2. Segmenting on Time to Click – Google Analytics is one of my favorite web analytics tools so far to conduct segmentation on. It is actually fun (eventhough Avinash Kaushik with all his blogs and books has motivated us enough to make it seem like fun… and insightful). After a keynote and personal conversation with Facebook’s Senior Open Programs Manager David Recordon I was quickly convinced that one of my new favorite performance and interaction metric would become ‘Time to Interaction’ as in plain English ‘Time to Click’. Basically the metrics tells you two things, the effects of page loading performance and persuasive content on the visitor and how long it took them to ‘Click’.

My Money, My Mouth

Armed with CrazyEgg I tried to tackle some insight issues at Thomas Cook Netherlands.

Faceted search is always a tough nut to crack. When you are in a position to define which faceted search items can be included on a specific page, you want to be sure that the options you are offering are relevant to the visitors encountering them.

In the travel industry, where I currently work, there is a huge distinction between visitors who want to book for a holiday in the near future and those who want to book in the VERY near future… the latter is known as ‘Last Mintues’. Thomas Cook offers a wide variety of holidays, the four main being:

    1. Flight holidays (Vliegvakanties) – often summer package holidays
    2. Car holidays (Autovakanties) – Europe is small, taking the car on holiday is normal
    3. City trip holiday (Citytrips) – often short 3 to5 days holidays to major European cities
    4. Ski holidays (Wintersport) – time to hit the slopes

The fifth pseudo type of holiday is ‘Last Mintues’ which bascially encompasses all four major holiday types with the differentiator being the fact that the actual holiday will start anywhere within the next 30 days*.

* My opinion is that 30 days is not really Last Minute. Personally I adhere a maximum departure date within of 14 days or less

Each of these type of holidays has its own page containing its own version of our faceted search application. Each faceted search application can be adjusted to best fit the type of holiday being offered. My question… are we offering the right options on the right page?

Faceted Search, a quick break down

The faceted search is split up into different categories:

    • Product – type of holiday
    • Destination – drop down list(s) to drill down to a certain country, region and city
    • Date – choose between departure week, month or during a specific school holiday
    • Days (not labelled in image below) – choose the duration of your holiday in days
    • Departure – choose a departure airport (if applicable)
    • Search Type – call to action to display results based on input or select advanced search
    • Free Search – search by country, region, city or accommodation name

Show me the money data!

In this short example I will only go into the comparison between the Homepage and the Last Minute page. Here were some of my findings based on a CrazyEgg heatmap (and actual click location) report:

    • Product: visitors in Last Minutes were more interested in City Trips and Ski Holidays (still in season at time of measuring) than visitors on the Homepage where Car holidays got more interest. City Trips (which can be done be plane or car) have always been of high interest for Last Mintue travelers. Interest between Flight holidays and Ski holidays usually shifts between seasons, in this example the winter season was nearing its end.
    • Destination: Last Minute travelers are less interested in selecting a destination than Homepage visitors.
    • Date: no significant differences
    • Departure: Not clearly visible in the image below, we noticed that Last Minute travelers mostly wanted to depart from Amsterdam (Schiphol Airport). There were hardly none to any clicks on the link ‘Meer’ which can be used to display ‘More’ options.
    • Search Type: Advanced search (link under call to action button) is hardly of any interest to Last Minute visitors. The less the amount of options there are, the better.
    • Free Search: This option opened our eyes the most, eventhough it is obvious. Free Search was not used once in the test period, clearly pointing out that Last Minute travelers need to be inspired and come to the website with no specific destination in mind (at least those who seek Last Minute holidays via the dedicated page).
Analyzing faceted navigation use on two segments: Homepage vs. Lastminute

Analyzing faceted navigation use on two segments: Homepage vs. Lastminute

Turning insights into actions

Now what can we do with this data? Well, in short, we just found out that for our Last Minute travelers, we are simply offering too many options in the faceted search application. By using the interaction analysis outcome we can find out ways to streamline what we show to a specific type of visitor, in this case, the type that is uninspired and is just looking for the right offer as long as they can leave soon and depart from Amsterdam.

Below is an example of how we could refine* (as Louis Rosenfeld so nicely put it in his Redesign to Refine presentation at UX London, see slide 150) the options in the faceted search. In theory, we could save around 54% in prime Real Estate on the Last Minute page and offer visitors a quicker method to finding the right holiday deal without making enemies within the organization who see any form as change as an attack.

* By no means is this an end product, this is just an example for this blog post.
Basic redesign based on interaction analysis

Basic redesign based on interaction analysis

Steering the visitor

Not convinced yet? Below is a short example based on content on how, by properly designing and placing your content, you can steer your visitors’ attention.

On the homepage of one of the Thomas Cook websites we were display small block internal ads. In the example below, on the left, you can see that the ‘inspirational’ ads were place above the ‘offer’ ads. The difference between the two being that ‘offers’ focused on hard discounts and good deals, while the other focused more on inspiring the visitor with fancy destination information.

It is blatantly clear that visitors want deals, offers, discounts… anything that saves them money. To prove this, we switched around the ad blocks and noticed the clicks moving too. This confirmed for us what the user really wanted… savings!

Steering clicks by redesign based on interaction analysis

Steering clicks by redesign based on interaction analysis

Still in doubt? Well, then go test CrazyEgg yourself!

[button color=green url=http://www.crazyegg.com]Check out CrazyEgg now[/button]

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About Matthew Niederberger

Matthew works as Conversion Optimisation Manager at Ziggo BV. In his free time he enjoys family life as well as digging into online user research material whilst frequently generating some of his own, which he freely shares here on actualinsights.com.

Comments

  1. Teri says:

    Matthew, Would have loved to have read this – but there’s not enough contrast. Gray font may be trendy, but it’s not usable because it’s not legible, especially on a gray background. Sigh – bet there was some interesting content. If someone is advising on design, it also makes me question the reliability of the content when a basic design issue isn’t implemented. Consider the human factors, the usability principles … Info on them is widely available.
    Teri

  2. Hey Matthew, can you email me when you have a chance, just wanted to chat quickly about this posts (which is awesome btw).

    Thanks!

Trackbacks

  1. [...] other words, you are creating insights in the fields of Web Analytics, Web Performance, Web Interaction Analysis, Voice of the Customer, Community Engagement and Competitive Analysis. But why aren’t A/B or [...]

  2. […] have grown accustomed to heat maps over the years. From web analytics click overlays to CrazyEgg. Some companies out there have take it a step further and have gone so far as to not only track […]

  3. […] This example highlights a travel company who questioned whether they were offering the right form options on the right page. This heatmap indicated that there were many underutilized fields.Based on this heatmap, the image below is a possible test they could run on this form to measure whether it generated more conversions. […]

  4. […] This example highlights a travel company who questioned whether they were offering the right form options on the right page. This heatmap indicated that there were many underutilized fields.Based on this heatmap, the image below is a possible test they could run on this form to measure whether it generated more conversions. […]

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