Accurate user data is the bread and butter of any successful website operation — the indispensable key to making sure that your website is pulling in clicks, generating conversions and giving visitors and customers what they want.
If you don’t know what your users are doing, you can’t find out what they need, and you certainly can’t adjust accordingly to be able to give it to them.
Luckily, there are a tremendous number of website data analytics tools that can provide reams of data on your users and on everything they’re doing while surfing your website. Unluckily, the sheer mass of all of this data can be disorienting, and the consequent inability to distinguish what is important from what isn’t can often make the information at your fingertips into as much of a curse as it is a blessing.
While artificial intelligence and machine learning already help immensely when it comes to the rote task of sifting through reams of data, actual marketing strategy still requires a human touch. We’ll discuss the two broadest types of website user data below — quantitative and qualitative — and show you what each reveals about your users and what its limitations. You’ll learn how to combine the two types to accentuate one another’s strengths and compensate for the other’s weaknesses, providing you the fullest picture possible.
You should leave with a clearer way forward to craft an ever-better website that leaves customers and users happy.
Qualitative vs. Quantitative Metrics
Everything that you learn about how users interact with your website arrives the form of either quantitative or qualitative data.
Quantitative data is expressed in raw numbers. It provides you with concrete aggregate statistics about what’s happening on your website. It tells you:
- How many people visit your website per month
- How many visit each particular page
- What the average amount of time that they spend on each page is
- How many go on to buy products from you (conversion rate)
- How many leave your website after looking at just one page (bounce rate)
If you have some question about user interaction with your website that can be answered with numbers, turn to quantitative data.
Qualitative data, by contrast, attempts to convey something about each user’s subjective experience on your website. These data can take the form of:
- Surveys given to users asking them to comment on their experiences with your website or give their thoughts about specific pages.
- Heat maps that show which parts of which pages users tend to most focus their attention and their cursors.
- Information about user behavior on each page, like rage clicking, aimless wandering.
In general, quantitative data is broad, but shallow. It offers broad statistical information about user trends and can alert you to general problems with your website. If your page bounces suddenly increase, or if your conversion rate falls off, you know that you have a problem. However, you won’t necessarily know why you have the problem that you have from consulting quantitative data alone.
A Trend! But Why?
Quantitative data alerts you to trends, but doesn’t shed much light on the reasons behind them. If you know, for example, that the bounce rate for a certain web page is high, then you know that you have to do something to change that page and help it retain user interest.
Relying on quantitative data alone, however, is frustrating in this instance because you don’t know what that something is. You’re left in the dark about what to do to improve the page.
Parsing the Trend
That’s where qualitative data comes in. Qualitative data provide deep insights, but have a narrow focus. Suppose that you notice, though watching a user interact with your site through a service like FullStory or UserTesting, that he finds himself confused by your menu options, and begins rage clicking all over the place or wandering confusedly and trying to figure out how to navigate to where he needs to go.
Unfortunate as this may be, it’s not conclusive on its own. That particular user may have had trouble, but other users may not — in which case, altering the page to suit that particular user may actually hurt your bottom line.
Although qualitative data can give a deeper understanding of each user’s experience, because they are so personal and individual to each user, qualitative data cannot give you the big picture.
Quantitative and qualitative data each have their respective strengths and weaknesses regarding what they can tell you about your users. Neither can give you a well-rounded picture on its own. Fortunately, there is a natural complementary between these two types of data that lets you combine them to get that elusive full story about your users.
Combining Qualitative and Quantitative Metrics
The key to properly combining the insights given by qualitative and quantitative data is to see how they each fit together. The general procedure to follow is something like this:
- First, use quantitative data to glean as much general information about user interaction with your website as possible. As every webmaster knows, Google Analytics is an extraordinary free treasure trove of quantitative information about your website. Exploit this resource freely. Use the broad, top-down view of your website that quantitative data provides to detect possible areas of improvement. Note that Chinese users (and some other restrictive countries) may have to access their website analytics data through a VPN in order for it to function properly.
- Second, check the quantitative data for signs of trouble: falling conversion rates, a plateau in the size of your email list, or whatever else happens to be of special concern to you.
- Third, examine the relevant qualitative data. See how individual users interacted with the parts of features of your website that your quantitative metrics indicated were slackening. Once you can determine what your users took issue with in that area, make the necessary changes.
- Finally, never stop repeating the previous steps. The goal of website perfection might be unattainable but that shouldn’t stop you from trying.
A Specific Example
Suppose that your raw conversion rate remains stubbornly low. You already advertise on the relevant web pages, but when you examine the heat maps of those pages closely, you find that users are relatively uninterested in those parts of the page where you offer a call to action and exhort them to buy.
You could examine the qualitative data to see what the source of this problem might be. Maybe your call to action isn’t catchy enough or displayed with enough prominence. Perhaps you web page layout doesn’t fully catch the eye.
There could be some other crucial web design mistake at work.
In any case, quantitative data shows you a problem exists and qualitative data helps you figure out why and and make the required adjustments.
We mentioned GA – an overall solid free tool, but there number of other excellent web analytics services (ahem, such ours) which provide a wealth of both quantitative and qualitative analytics tools — including heat maps, uptime monitoring, logs of everyone who visits your website, and more — in one place. Not to mention it’s easier to navigate than the somewhat antiquated Google Analytics.
These metrics are crucial to staying on top of any internet-based business. According to a recent study of the best web hosting services by HostingCanada.org, 27 out of the top 31 most popular hosting providers by market share have uptimes less than 99.9%. This may not seem like a lot, but even a few minutes of downtime could be incredibly costly to the bottom line, either as lost sales or tarnished reputation. This is one feature to compare among service providers while conducting an evaluation.
The Bottom Line
Quantitative and qualitative data each have their place in the online marketing world and no webmaster worth his salt can afford to ignore either. A single-minded focus on one or the other can leave you with blind spots that will keep your website from reaching its full potential. In short, mix and match for best results.