Of all the questions you might have about your online presence, one of the most important ones to consider when it comes to conversion rate optimisation (CRO) is, what do high converting users look like and how do we get more of them?
In this article, we will discuss the answers to these questions, and more specifically, explore how marketers can leverage analytics to identify what high converting users look like in terms of on-site behaviours.
In order to ensure your website’s performance, user behaviour and conversion opportunities are relevant and focused, we encourage you to start with these questions – what questions do you have about your site, users, and conversion rate, and how will knowing the answers help shape your optimisation strategy going forward?
You can then start to create optimisation hypotheses and design experiments for your site by encouraging users to behave in ways which drive conversions.
Set up your tracking
Before we even begin looking into the customer journey, you must first make sure that you have suitable tracking set up in your analytics tool to capture on-site behaviour. You must then allow it time to gather data before you can start analysing how these behaviours relate to conversions.
This isn’t just about the basic “out-of-the-box” standardised reports. It’s also about maximising insights into important interactions using ‘event tracking’ (in the case of Google Analytics). However, it’s also important that you avoid drowning yourself in data by tracking absolutely everything, which may force you to tune out any of the irrelevant noise.
The three core stages of the on-site customer journey
Assuming your tracking is set up, the next step is to look at the three core stages in the on-site customer journey.
I want to first ask a question that may seem to have a fairly simple answer. Is your website’s search bar useful? Without even going into the detail of what users are typing into your search bar, you can start by observing the top line data that tracks the conversion rate of users who use the site search option versus those who don’t.
This data can tell you a couple of things. Firstly, if customers who use your search bar have a lower conversion rate than those who don’t, perhaps the search results provided are irrelevant or causing frustration. Therefore, can the results be optimised?
Secondly, if the conversion rate for searchers is higher than those who are not, how can you get more customers to engage with your search function? Can the prominence, visibility or messaging around the search bar function be optimised?
Just by analysing this one behaviour, we have already identified CRO opportunities to drive product/service discovery.
Next, let’s take a deeper look into on-site customer behaviours.
We often think that the content on a website is what drives users to visit the website. However, how can looking further into the data, specifically at the level of engagement with this content, provide further insight on conversion opportunities?
Using on-site video content as an example, if you have set up quality tracking of video engagement, you can look at two different pieces of data to explore ways you can optimise this content to support conversion.
The obvious place to start is examining how users who play the video compare to those who don’t play it. Are users who watched the video then leaving the site, having got all they wanted out of their visit? Or do users who watch the video go on to convert more? Depending on what you find in your analysis, you know whether to work on designing experiments which promote or demote the prominence of the video to optimise for converting behaviours.
Looking even deeper, if you tracked how much of the video each user has viewed, you can analyse the video viewing behaviour in greater levels of granularity. Do users who have watched just 10% of the video convert just as much as those who have watched 75% or more? If longer time spent watching the video is a behaviour associated with higher value visitors to your site, you have just identified an opportunity for optimisation – optimising for watch duration.
This advice isn’t specific to just videos. You can also apply the above to other areas of your website, including page scroll depth, clicks on an info tab, etc. and analyse it the same way.
So far, we have mainly explored ways to optimise a website by increasing ‘positive behaviours’. However, one of the key ways you can also optimise your site is by reducing negative behaviours, namely abandonment.
Whether the conversion point on your website is a lead generation form or a full e-commerce checkout page, the principle of data analysis is the same when talking about optimising this experience. We again want to start with a question, like where are users abandoning your website? Adding field by field tracking, whether implemented as events into your website analytics platform or via a third-party tool like Zuko (formally Formissimo), will allow you to see the level of granularity you need, in order to make meaningful CRO hypotheses.
For example, if users are abandoning your website or a specific page on your website when asked to enter their phone number, you can explore different messaging options to reassure users on why and how you will use this data.
Or, if you are finding that users are abandoning on your password creation fields, you can begin exploring ways the password field requirements and error handling can be optimised. Perhaps in a situation like this, a visible tooltip and inline validation may be helpful.
To learn more about specific ways you can optimise your site checkout, have a read through this blog we’ve put together here.
Telling cause from effect
One obvious caveat to all of this is that data alone cannot answer one very important question – am I observing the cause or the effect? Or more specifically relating to the areas explored in this article, are users who are already motivated to convert more likely to use site search, or is site search helping to motivate users? Is watching my video causing users to convert more often, or are high value users already more likely to engage with my site content?
That is why we always back up data-driven optimisation hypotheses with both qualitative and quantitative data. Fundamentally, this covers two distinct areas: user feedback (in all its forms) and split testing your hypothesis via on-site experimentation.
For support on data-driven CRO, user research and on-site experimentation, Croud can help – get in touch with our CRO team today!