UX Data-Driven Designs

At the time of a website creation, many designers make the mistake of just caring about aesthetics. They have a formed opinion of what is nice to have and what is not and they just apply it systematically. 

 

Later on, after months of wondering why they aren't creating enough engagement, they discover that the users don’t interact with the elements of the website as they would expect.

 

That is why data-driven designed websites are a must nowadays. They let us understand from early days what the problematic areas of our website are, so that we can solve them before it is too late. Today, we will talk about data-driven designs and how to get the most of it.

What is Data-driven? 

To be data driven means basically that we make our decision based on data. We are not trusting our guts anymore, but create a set of hypotheses that later we can test and compare through data. 

Being data-driven allows you to forget all the egos at the decision-making process and counter attack the HiPPO effect (highest paid person’s opinion). HiPPO effects describe how we tend to follow the advice of a person because of the title they have rather than the idea.

Of course, being data-driven is a perfect set of mind to reach to the best solution in every single case, and that’s why most successful companies are embracing it on its culture.

Data-driven design

Pros and cons of data-driven culture

By adopting a data-driven culture, we no longer base our execution on bold guesses, but we let the user have the final word. Based on it, we can discover the parts of our business that are not working as expected or that are becoming a bottleneck for growth.

 

This way, we can find the root of our problems and can solve them way faster and more efficiently than any other way.

 

Of course, such a great set of mind has to be used with some caveats. The cons of a data-driven approach could be summed up in the difference between being data-driven and data-informed. 

 

While data-driven means that data has the final say about anything, data-informed means that there is a human at the end of the process that collects all the data and the metrics available, and with that information makes the decision.

 

This is an important difference, since in order to be a data-driven company we need to have many considerations while using the data:

 

  • Sometimes, the metrics chosen for the experiment do not represent exactly the problem that we want to solve. So by optimizing them we might not optimize our root problem.

 

  • We might be handling different metrics at the same time. The perfect metric for a problem is really hard to find, we can track multiple issues at once, and with every single metric in mind, make our decisions.

 

  • The data we collected might not be significant enough. Imagine that we create 2 web designs and apply A/B testing to them but we do not get enough traffic to be statistically significant. We need to understand that those metrics should be taken away from the equation and decision-making process.

Data-driven design

In terms of website design, UX data-driven design means to make the decision based on the data of your users while they interact with your site. This is achieved by measuring how they behave with the elements of your website. There are a whole set of tools for this, such as usability testing, user personas, eye-tracking...

Data-driven design: how to

As for any other data-driven approach, a data-driven design has to start by finding the right metric to follow. Good news is that for a website, this is more simple to achieve than for other data projects. 

 

There are 2 metrics that are usually good North Star metrics:

 

  • Amount of traffic at your site.

  • Conversions (click ratio of the CTA)

 

The first let you maximize the total amount of traffic at your site, while the second how many conversions can be achieved from that traffic.

Vanity metrics vs actionable metrics

I would like to stress out the importance of normalizing the metric vs following the total amount of conversions to measure success. By normalizing a metric, that means, for example, divide the amount of traffic my week or dividing the number of clicks at you CTA by amount of visitors, we obtained actionable metrics.

 

Measuring your success in volume numbers can lead to misinterpretation of those metrics. If the number of clicks at your CTA is low, it can be because you don’t have a lot of traffic, or because your website design is not engaging enough, but you will not be able to tell the difference.

 

On the other hand, a proper data-driven design measures success with actionable metrics, that allows you to compare the progress you make from one month to another and illustrates which part of the funnel is becoming the bottle neck.

 

CTAs

Of course the CTA we have will make a difference too. If the journey is hard or long for our user, and yet they complete the whole journey, that lead will have more quality than another obtained from a simpler CTA. You don’t want your CTA to be extremely hard, or nobody will get to the next phase of your funnel.

User behaviour 

In order to get the most of our data-driven website, we will need to measure different aspects of it, that can be the total amount of traffic, user engagement, user behaviour… 

 

The amount of traffic and the user engagement (conversion rates) can be classified as outcome metrics. These metrics treat the web design as a black box and only compare the results of changing parts of it. However, in order to understand the process to get that outcome, we need to look at the user behaviour.

 

To deeply understand the user behavior at our site, we need to go a bit further from conversion rates and CTAs clicks. In order to measure user behavior, heatmaps are the best tool. Check out our last blog about different kinds of heatmaps if you still don’t know all the different ones. 

data-driven design - website heatmap

By looking at heatmaps, we can understand the behaviour of the user in our website as a whole, and not just try to figure out how to improve our conversions by random AB testing.

 

Heatmaps are usually considered as qualitative metrics. However, we can obtain quantitative metrics from heatmaps if we are able to calculate the amount of attention our users place in a specific area of our website.

 

At Kemvy, we focus on predictive heat maps that allow you to understand how the user will behave at your site instantly.

Final check list

Alright! Now that we have the understanding about data-driven designs, it’s your turn to put it into practice. A quick checklist to do at your site:

 

  • Are you measuring exactly what you want to optimize?

  • Are those metrics actionable ones and isolated from other factors?

  • Is the effort required for the user at your CTA the correct one?

  • Do you understand what is going on inside your website, so that you know how to improve your metrics?

 

If you already have all of them, congratulations, you are on the right path. Otherwise, you have work to do, good luck!