In the present digital era, many business organisation desires to design websites and applications that are user-friendly and pleasant to access. But what do you know that users like or dislike? 

What can you do to discover their reasons behind the abandonment of a page or the rejection of an app?

This is where UX research becomes crucial.

UX research helps companies and designers with the knowledge of the interaction between users and a product. It focuses on problem identification, understanding the behaviour of users, and making the experience better.

Yet, conventional UX research methodology may be time and money as well as resource-consuming. Interviews, surveys, and usability tests are too slow and may not be sufficient for quick-paced digital projects.

This is the reason why Artificial Intelligence (AI) is turning out to be a game-changer in UX research. AI helps the researcher to gather, analyse, and interpret data more quickly and precisely. 

We will learn to use AI to aid in UX research and how, step by step, you can use AI-powered UX research tools.

What is UX research?

UX research refers to the research of how people utilise a product and discovering methods of improving it for them.

For example:

• Are the users finding the app easy to navigate?
• Do they get confused with some of the buttons?
• Some people do not complete their sign-up. Why not?

The UX research attempts to answer such questions in the following ways:

• Surveys and interviews: questioning people about their experience.
• Usability testing: observing the usage of the product.
• Analytics: the examination of the data of websites or apps to learn what people do.
• Heatmaps: the most appropriate areas where the users are clicking, scrolling, or moving their mouse.
• The UX research aims at creating a product that is easy, free, and gratifying to the user.

What AI is and how it helps in UX Research.

Artificial Intelligence (AI) refers to programming computers in such a way that they can think, learn, and make decisions just like humans. It is possible to learn and predict using AI tools, analyse a large amount of information, and identify patterns.

In UX research, AI helps by:

• Fast user behaviour analysis.
• Detecting concealed trends or patterns in data.
• Anticipating what the users may need or desire.
• Generalising the results of big surveys.
• Developing user personas automatically.

To summarise the points, AI will decrease human labour and will accelerate the process of user comprehension.

Why Use AI in UX Research?

The use of AI in UX research has several worthy purposes:

• Saves Time:

The AI tools are able to handle thousands of feedback messages or user sessions within a few minutes.

• Saves Money:

Manual data collection or analysis requires fewer people.

• Removes Bias:

AI is not focusing on personal views but facts and information.

• Finds Patterns:

It can monitor user behaviour patterns that humans can hardly observe.

• Improves Accuracy:

AI can gather data across various sources (such as surveys, analytics and user sessions) to have a full picture.

How to use AI for research tools?

Let’s know some of the real-life examples illustrating how AI assists UX researchers.

1. Learning about User Emotions.

AI technologies are capable of analysing the face, voice, or behaviour of a person to learn about their emotions when they are consuming a product.

How it works: These devices detect whether the users are bored, lost or happy with facial recognition or eye tracking.

The role it plays: Researchers can detect which features of a site or app cause people to feel uneasy or frustrated.

Example:

In the case of an app designed to test shopping, the AI tool identifies that users appear to be frustrated when they are on the payment page. It indicates that there is something that is confusing or slow on that page.

2. Automating the Review of User Feedback.

If you do it manually, then it is very hectic and time-consuming to read thousands of comments on the surveys or social media. However, with AI, all this information can be summarised in seconds.

How it works: The robot scans all the feedback provided by users and clusters together similar feedback.

The benefit it will provide: Researchers will be able to view the most frequent complaints and compliments quickly.

Example:

A summary of the AI on 2,000 survey responses showed:

• 40% said “the app loads slowly.
• 25% said “the design looks modern.
• 20% said “login is confusing.”

The team is now aware of the areas that they need to work on.

3. Automatically generating User Personas.

In UX research, a persona is a made-up figure that represents a typical user. In most cases, researchers develop personas based on survey or interview data. They can now be generated automatically with the help of AI tools.

How it works: AI uses the user data collected by analytics and social media in a real manner to generate detailed profiles.

Its benefits: Designers obtain realistic and data-based personas that reveal actual behaviour patterns.

Example:

AI invents a personality named Priya, 28, who is fond of online shopping, spends the majority of her time on mobile, and is annoyed by slow-loading pages.

This assists the design team in creating an emphasis on enhancing mobile performance.

4. Heatmaps and Eye Tracking

Heatmaps or predictive eye tracking can be used to demonstrate the places where users look or click most on a webpage with the use of AI.

How it works: AI follows the movements of the mouse or predicts the direction the eyes of people are going on a page.

How it can assist you: It informs you on what areas of your webpage are popular and what areas are not being taken into consideration.

Example:

A heatmap can indicate that the users do not see your Buy Now button too often, as it is too low. Your sales are increasing by moving it up.

5.Voice of Customer(VoC) Analysis.

AI is capable of analysing and reading large amounts of customer reviews, support chats, or emails.

How it works: This type of tool applies Natural Language Processing (NLP) to locate emotions and topics in user feedback.

The way it helps: They can explain whether the general feedback is good or bad and point out the significant problems.

Example:

Out of 10,000 reviews, the AI identifies that most users are complaining of delivery time. The next priority of the company is to improve the speed of delivery.

6. Predicting User Behaviour

AI may forecast the future actions of the user, such as whether they will make a purchase or not.

How it works: AI monitors the actions of a user and matches them to his or her past behavioural patterns.

Its usefulness: You get an opportunity to act early before the users leave.

Example:

According to AI, when there are three unsuccessful attempts to log in, many users abandon the process. After the second attempt, the team introduces an option of Forgot Password, and the number of drop-offs reduces.

How to use AI in UX research: Step by Step

The following is a rudimentary AI UX research guide.

Step 1: Define Your Goal

Begin by choosing what to learn.

Example: What is the reason why the users are not going through with the checkout process?

Step 2: Collect Data

Collect data using AI tools that can gather data automatically, such as:

• Analytics (Google Analytics, Mixpanel)
• Heatmaps (Hotjar)
• Feedback (Typeform, Thematic)
• Recordings of the sessions (PlaybookUX).

The tools collect all information required on user behaviour.

Step 3: Analyse Data Using AI

Enter the data collected into the analysis AI.

For example:

• Summarise the answers of surveys with MonkeyLearn.
• Use Hotjar to study heatmaps.
• Get ChatGPT to summarise unstructured feedback.

Example:

According to AI, users fail to purchase because they are not able to visualise the total price before payment. That is a clear problem to fix.

Step 4: Develop Personas and Journey Maps.

Use AI persona generators with the help of Delve AI to generate automatic user personas and customer journey maps.

Example:

Anita, 32, is an irregular visitor visiting the site via mobile at night, and leaves at the payment page, saying it is very slow.

Your team is now aware of where improvements are required.

Step 5: Generate Design Ideas

Once you have the insights, you can create AI design tools to convert them into mockups or prototypes.

There are the Uizard, Figma AI, and Galileo AI tools.

Example:

You instruct the AI to make the checkout process quicker and with fewer form fields.

The artificial intelligence proposes a new design with a minimalist design.

Step 6: Test and Improve

Conduct the new AI-based usability testing to determine whether your new design has improved.

Example:

On redesign, Maze AI states that the users are able to check out 40 per cent faster.

This will be the confirmation that your changes did not work in vain.

Advantages of AI in terms of UX Research.

1. Speed:

Within seconds, big data is analysed by AI. As an illustration, it is capable of reading and summarising 1,000 survey replies within seconds.

2. Accuracy:

It eliminates human error and discovers patterns that can be overlooked by people.

3. Cost-Effective:

It does not require a big team to do advanced research.

4. Scalability:

Millions of users can be managed by AI simultaneously, which is ideal with large companies.

5. Continuous Learning:

Most AI tools operate 24/7 and notify when the behaviours of users change.

Challenges of AI usage in UX research.

Even though UX research works really well with AI. However, you can’t ignore the challenges:

1. Data Privacy:

AI tools work with user data. Organisations should comply with the data protection regulations, such as GDPR, and secure the data of users.

2. Deficiency of Emotional Comprehension:

AI can scan information, but not necessarily understand human feelings or cultural significances.

3. High Cost of Tools:

Small start-ups might not afford some of the sophisticated AI tools.

4. Need for Human Insight:

AI does not provide results without requiring human researchers to interpret and make creative decisions.

FAQs

What is AI in UX research?

AI may be significant as the UX research becomes quicker, less expensive, and more data-driven.

The feedback of traditional methods takes weeks to be analysed, whereas AI can summarise the feedback of thousands of user sessions or comments in several minutes.

It is also able to detect latent patterns that humans may ignore.

Is it possible to completely substitute human UX researchers with AI?

No, AI will never be able to replace human UX researchers.

AI is capable of processing data and delivering insight; however, it is not able to perceive human emotions, context, or creativity in the same manner as people do.

What is the application of AI to usability testing?

• AI can automatically analyse videos of user sessions, or test recordings and identify areas where users are inactive, confused, or make mistakes.
• It is even able to provide usability values and indicate areas of problems without manual review.
• This saves time from going through video recordings manually.

What are the UX research AI heatmaps?

• AI heat maps indicate the most visited components of a web page.
• They are made using tracking of user clicks, scrolls, or eye movements.
• Even before actual testing is done, AI applications such as Attention Insight may be able to simulate eye movement so that designers can optimise layouts at an early stage.

Conclusion

AI has transformed the UX research into a quicker, smarter, and more precise one. It helps in exploring the user behaviour, gathering feedback, as well as discovering concealed patterns within only several minutes. 

Hotjar, Maze, and UXtweak tools save time and provide valuable information to make more design choices.

However, AI is not able to replace human knowledge. Empathy and creativity are still needed in good UX. The most efficient outcomes are achieved when AI processes data, and human beings are concerned with emotions and design concepts. 

However, collectively, they simplify user experiences, make them enjoyable, and indeed user-friendly.