Getting Started with UX Analytics with Data-Informed Design

  • Datameer, Inc.
  • July 12, 2022
Data-informed design

“Data is the new oil and analytics is the combustion engine.”

The Vice President of Gartner, Peter Sondergaard, made this now-famous statement in 2011.

This statement was true then and even much more so now, over a decade later. 

Marketing teams are leveraging data garnered from analytics everyday to create what has now been termed “data-informed design.”

UX Analytics

What is data-informed design and why is it important?

How is User experience analytics used in creating these “data-informed designs”? 

How can you get started?

In this article, we will explore the answers to these questions in detail.

Let’s begin by looking at the terms; “User experience(UX) analytics” and “data-informed design” in detail.

What is UX Analytics?

UX analytics can be simply defined as the gathering of quantitative or qualitative data for use in the design or iteration of a product or feature.

Ux analytics involves tracking user behavior, obtaining feedback on your user’s experiences, etc., i.e., Each comment, review, click, swipe, and scroll provides you with invaluable insights into your user’s experience.

That’s the aim of Ux Analytics; To measure user experience metrics and KPIs that can help for better decision making and better products.

Data-informed design, what’s that?

Just as the name suggests, data-informed design is the use of the data (Ux data), to inform your product design process.

 It’s about utilizing data to make informed decisions on your design approach.

The heart of data-informed design

The heart of data-informed design.

Using Ux analytics Data to create data-informed designs.

 ” Errors using (even) inadequate data are much less than those without data at all.” 

-Charles Babbage

This famous quote by Charles Babbage highlights the importance of relying on data in order to avoid making errors or ill-informed decisions.

Every business wants to create easily adaptable products that are user-centric and convenient. 

To create these types of products or features, it’s essential for businesses to understand their user’s needs and pain points before allocating resources for design.

Understanding your user’s needs and pain points can be achieved by user experience (UX) analytics. 

With a Ux data-informed design approach, you eliminate assumptions when creating your target personas, making it a whole lot easier to create truly user-centric and adaptable products.

UX Analytics to Data-Informed Designs – An Illustration

So how does this really happen?

A good example of this concept can be gleaned from our favorite professional buddy, Linkedin.

At the time of writing, LinkedIn just added a laughing emoji to their react buttons.

Sounds basic, right?

Think again.

If you have been using LinkedIn for a while, you might have noticed the transition from the uptight professional vibe to a more social one. 

LinkedIn gradually became a space for people to not only share corporate stuff but funny content, birthday posts, marriage posts, etc.

LinkedIn picked up on this trend ( UX ) and decided to modify its Ux interface.

They went ahead to add a funny emoji 😂( data-informed design ) to their react buttons tray.

data-informed design

This is a good example of how relying on your data (user experiences of your product)can help you make better data-informed designs.

In my opinion, I believe this feature is one that could potentially change the way people view LinkedIn. 

Not to deviate…

Let’s talk about how you can get on this too.

Ways To Collect UX Data 

In what ways can we collect this user experience data?

There are several ways.

One tried and tested method uses research approaches to collect and analyze data. A few examples are :

1. A/B testing: An A/B test is used to determine which version or variant of something will perform more effectively in the market.

For example, the company can put out 2 different designs of the same product and share them with randomly selected users.

Thereafter, evaluate the UX analytics, i.e., review which of the product or design had a wider acceptance rate, etc.

 2. Quantitative and qualitative research methods:

(a). Quantitative data can give valuable insights into what the users want. Whether it’s the number of clicks, downloads, time spent on a page, view rate, etc..…

Methods of acquiring quantitative data include carrying out surveys, collecting site traffic, and even A/B testing.

(b). Qualitative data on the other hand, helps marketing see how the users view your product or feature and why they view it that way. 

In a way, qualitative data tells the marketing team how and why certain marketing strategies and interventions failed, and others did not, shedding light on the reasoning, opinions, motivations, thoughts, and thus experiences of your users.

Various methods can be used here to garner this type of data, including focus group discussions, user interviews, usability testing, etc.

 Ways to create effective data-informed designs

iterate based on feedback

Don’t forget to iterate..based on feedback.

1. Use analytics to optimize ad creativity.

Use data from your Ux analysis to determine what’s working and what’s not.  

Next, decide what can be changed for an ad to produce better results. You’ll be surprised how little optimization of your ads can lead to better ROI.

2. Use data to determine the best way to reach your audience. 

To do this, look at data to gain insights into the demographics of your customers, what resonates with them the most, and how you can capture their attention. 

Use these insights gleaned from this analytics to develop a strategy that’s tailored to your target audience. 

3. Use analytics data to finetune your marketing strategy. 

Don’t be scared to replace archaic strategies with new initiatives.

Craft your marketing to connect with your customers on an emotional level.

Consider using qualitative data to understand how and why certain designs make for better Ux.

Iterate based on feedback. Remember that iterative design is the cornerstone of data-informed design, so don’t be afraid to rethink the original solution and update based on feedback as needed. 


Collecting data isn’t the difficult part; having a data-driven design routine that you’ll stick to definitely is.

Being able to model and analyze your quantitative data is key to making better decisions and improving the quality of your users’ experience.

To do this, you require a technical platform that provides you with a consolidated view of your customer.

With data warehouses like Snowflake and modeling tools like Datameer, you can clean, prepare and analyze your data effortlessly.

Request a free trial today  to experience Datameer in action and learn more about how it can transform your organization’s approach to data.

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