What is Data-driven Website Design?
A data-designed website is designed to convert more sales first and look pretty second.
The difference between good design and great design is very intuitive, which is the opposite of how precise your website and marketing data is. So the goal behind data-driven design is to create a website that looks good; but, more importantly, converts your traffic.
It might sound like common sense, but 90%+ of all websites are not designed like this. Instead, they were built to either look more modern, more user friendly, or more like their competitor’s sites, which are all great goals to have. The issue is, these website projects could have benefitted by utilizing existing user data to build a website that creates more sales.
Many people hear the word data and clam up. But actually, data can be quite easy to track and can even be visual. By understanding how your audience interacts with your website and identifying what pages resonate with them the most, you can design it to improve your user experience.
Data is used to prove your digital marketing efforts are on the right track, as well as help you uncover some areas where you could improve. As you likely remember from school, there are two types of data: qualitative and quantitative. Qualitative data is descriptive in nature, whereas quantitative data is rooted in numbers and metrics.
Rather than choosing one over the other, the greatest success will come from utilizing both since each can bring valuable insights to your website project.

Gathering Data
There are a few sound strategies for gathering user data for your creative design process:
A/B Testing, or Split Testing
By A/B testing your website, you can compare two or more renditions of a web page by dividing your target audience into groups (A and B) and showing each group a different version. In comparing these versions and responses against one another, you can see which version generates more responses and sales.
Google Analytics
Google Analytics is a great way to evaluate quantitative data, including your website’s clickthrough rate and bounce rate. It pulls from three primary sources: The HTTP request of the user, user browser and system information, and first-party cookies.
Google Analytics works through a block of JavaScript code that gets embedded on your webpages. From there, the tool retrieves data and sends that information to the server, on which you can view and download the data analytics.
It’s the most popular analytic tool, and it helps users simplify and analyze an array of information from site visitors.
Interviews
The best way to know what people are looking for is by asking them, which is why user interviews are an excellent way to gather qualitative data from your website traffic. Before you interview your site users about their experience, you should expect that the process will take time. Interviews are a proven method to determine if your users are getting the right message at the right time.
Marketing campaign data
Digital marketing campaign data is another underutilized data set.
Marketing data can provide insights into placing CTA (call-to-action) buttons, for example. Suppose someone visits a blog post, and now they are interested in getting a quote. One could test to gain more leads by inserting a CTA button at the top, in the middle, or at the bottom of the converting post. Actively making tweaks on one’s website can result in converting more traffic.
For example, a solar company might have a blog post about the best manufacturers of solar panels. The post’s organic traffic will interact with the page differently from paid traffic from Google or Facebook. The organic traffic might be researching and clicking a CTA located at the bottom of the page. Paid traffic might click a CTA found at the top of the page.
A well-built digital marketing campaign will have data that can help you make the right decision for your page.
Surveys
Surveys are a great way to collect both quantitative and qualitative data for your website project. When planning, define a clear objective first and don’t make it too broad. Make sure you dedicate each marketing survey to a specific subject or two so your results won’t be too general.
It can help your strategic plan to work backward to make sure your questions will produce answers that you are seeking. It is okay to test your survey with friends or colleagues before releasing it to your target audience.
Lastly, make sure your surveys don’t include a bias. Try and utilize neutral language wherever possible–that way, users will answer honestly.
The next step is to review the data. You can examine and discuss new ways to make your site better and more engaging based on the results. Then, you’ll have a better grasp of your user’s needs.
Heat Maps
Qualitative data is often the most critical data set to consider for a new website project. Yet it’s often the hardest to quantify since it involves how your website makes someone feel through the use of color, images, negative space, and design. These elements convey emotion, value, trust, and a variety of other nonverbal indicators.
Using a website heat map is valuable because it can visually show how your users interact with your website. Heat maps use a cool-to-warm color gradient applied on top of your website that shows which parts of a particular webpage are getting the most clicks, dwell time, and traffic.
When looking at a webpage, the heat map can show you which parts your users spent the most time on. If you scroll down and notice the bottom of your webpage has no heat indicators, that means most users view that portion of your page.
If users are mildly skimming past crucial information in the introductory section, you may consider redistributing your information to make it equally enticing. If users don’t spend much time on your homepage, reconfigure the content to increase the dwell time.
Heat maps are crucial for any website project to streamline your data-collection efforts and help test new ideas.
Why Does it Matter?
Your data is black and white, as are your company’s goals. Yet to gain more customers and market share, you rely on the design, layout, and content of your website (which is intuitive) to efficiently convey your value…which is easier said than done!
Even the most amazing designers can’t predict what will create the most amount of potential customers.
If your site is easy to navigate and engage with, then your potential customers will most likely return (or better yet, convert). All this in mind, you should remember that data shouldn’t have to compromise your brand’s vision. If anything, your data should enhance it.

Components of a Data-Driven Design
Hypothesis
The decision to redesign a website typically spurs from a hypothesis, or something testable. One easy example: the colors a site uses can create a sense of urgency in your traffic, so will your potential customers increase by 15% by updating the “buy now” CTA button?”
Once you pin down your hypothesis, it’s time to make a plan to test it out.
Testing
To accurately conduct your test, you need to make sure your sample size is sufficient. If the group is too small, the data may be inaccurate or questionable. Your focus group is a sample of individuals. The larger the group, the closer your sample data will reflect reality, but make sure you still choose a manageable amount of people.
Utilize A/B testing to test a CTA button’s color, for example. Give group A the red button and group B an orange button, then compare the results of user behavior.
When testing a new design approach, be sure to eliminate confounding variables. In other words, only change the color of the “buy now” button, or whatever new feature you wish to test, instead of redesigning the entire webpage. With a complete redesign, you would have many contributing factors to your sales, and it is hard to pinpoint which change worked.
Experimentation
One great thing about the data-driven creative approach is that you can conduct as many user tests as you’d like. The important part is to handle them in separate, controlled experiments. Instead of overhauling an entire website, it’s more effective to focus on smaller collections of data that will lead to better design choices in the long term.
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