10 Best AI Tools for UX Research (Tested & Compared) 🔎

We turned to our team of seasoned UX experts to bring you the best AI-powered tools for UX research. Each expert shared their preferred tools based on real-world applications, using them in diverse projects to enhance client experiences. 

Every tool included here has been rigorously tested, providing insights and data that drive measurable improvements in user experience.

There are numerous AI tools that can help you with UX research. Here is a quick overview of them, including their standout features and pricing.

Looppanel is an AI-powered tool tailored for UX researchers. It enables you to do efficient data analysis and organization. This tool comes with features like 90%+ accurate transcripts in minutes, auto-tagging, and smart repository search; it is known to analyze data up to 10x faster. Moreover, it provides you with automated notes that are categorized by research questions, ensuring insights are organized and easy to find. Looppanel's standout feature—its AI-powered tagging system—saves teams from manual work, keeping research accessible and relevant.

How Looppanel helps in UX research

Looppanel speeds up the entire UX research process by automating transcription, tagging, and insight extraction. Researchers can focus on analyzing user behavior instead of sorting through hours of recordings. It turns interviews into organized data you can act on quickly.

Key benefits for UX researchers:

• Auto-transcribes interviews with high accuracy
• Tags insights by topic or question without manual effort
• Groups similar feedback into patterns
• Saves time on data processing and reporting
• Makes it easy to find and reuse past insights

Standout feature

Source

Its AI-powered tagging system saves you from manual work. This keeps research accessible and relevant. For instance, you are conducting user testing sessions for a website redesign. Users provide feedback on various aspects like the homepage layout, navigation bar, and search functionality. In this case, instead of manually going through hours of recordings, Looppanel can help you process the data within minutes. It auto-tags user comments with labels such as “homepage clutter,” “menu confusion,” and “search bar placement.”

Why we ❤️ it:

Looppanel's automation handles tedious tasks. This allows our professionals to focus on deriving insights.

Pricing: 

You can avail of its services starting from $27/month.

ChatGPT is an AI-powered tool that offers a versatile, fast approach to UX research support. Although it is not purpose-built for research, it shines in helping UX teams draft survey and interview prompts, brainstorm research questions, and role-play user personas. Moreover, ChatGPT's has the ability to process open-ended responses. 

This can help your UX researchers identify themes and synthesize insights. It also aids in generating user stories and ideating solutions based on collected data.

How ChatGPT helps in UX research

ChatGPT acts like an assistant that helps researchers make sense of qualitative data. It helps draft user questions, identify feedback patterns, and generate structured summaries or user personas from messy text inputs.

Key benefits for UX researchers:

• Summarizes user feedback into key takeaways
• Drafts interview questions and personas quickly
• Extracts recurring pain points from raw text
• Helps generate design ideas based on user needs
• Saves hours of manual reading and synthesis

Standout feature

Let's say you are tasked with improving the navigation of a website after conducting user testing. Now, all you have to do is input all user feedback into ChatGPT, including pain points like “menu options are hard to find” or “too many clicks to reach the checkout page.”

Using this input, ChatGPT analyzes the unstructured data and generates a draft sitemap with recommendations:

1. Consolidate primary menu items under clear categories such as “Shop,” “Learn,” and “Support.”
2. Introduce a search bar prominently in the header.
3. Add a shortcut to the checkout page under the cart icon for seamless access.

This ability to transform unstructured data into meaningful insights is invaluable for UX researchers. Moreover, it can identify recurring themes in user responses, helping you prioritize design improvements that resonate with your audience.

Why we ❤️ it:

We like ChatGPT because using it is like having a tireless collaborator for your UX projects. It reduces the time spent on manual data analysis, freeing you to focus on designing impactful solutions..

Pricing:

Youcan access GPT-3.5 for free. However, it also has an enhanced GPT-4 model. To access that, you would be required to pay $20 per month.

Maze is an AI-driven UX research tool that is designed especially for unmoderated testing. On Maze, you and your researchers can upload prototypes, define user tasks, and rely on AI to analyze interactions. The tool automatically generates reports, including heatmaps and sentiment analysis, giving a clear view of usability and user reactions. This automation saves time by providing actionable insights in minutes, which can be easily shared with your team.

How Maze helps in UX research

Maze helps UX researchers run usability tests without needing to be present. Just upload your prototype, define tasks, and let Maze gather interaction data and emotional feedback automatically through reports and heatmaps.

Key benefits for UX researchers:

• Runs remote usability tests at scale
• Captures user interactions through heatmaps and click maps
• Identifies friction points and confusion in flows
• Automates reporting with clear visuals
• Speeds up testing cycles without live sessions

Standout feature

Source

Auto-generated reports with visual insights like heatmaps and sentiment analysis. Let's assume you are conducting a usability test for a newly designed checkout flow in an e-commerce app. Here, Maze can help you create a test where users are asked to complete a purchase. As participants interact with the prototype, Maze will capture data like:

• Click maps to visualize where users are tapping or clicking most frequently.
• Heatmaps show areas of the screen that users engage with the most.
• Sentiment analysis extracted from feedback questions, highlighting how users feel about their experience (e.g., "frustrated," "confused," or "satisfied").

Once the test concludes, Maze generates a comprehensive report with heatmaps highlighting design confusion (e.g., repeated clicks on inactive icons) and click maps identifying friction points.

Why we ❤️ it:

Quick, comprehensive analysis that lets researchers focus on strategy instead of time-consuming manual review.

Pricing: 

You do 1 study on Maze each month for free. However, to do more, you would be required to subscribe to its paid plans that start from $99/month.

Miro Assist enhances the popular Miro board with AI-powered tools to simplify and speed up UX research. This AI is integrated directly into Miro. It uses machine learning to generate diagrams, summarize ideas, cluster sticky notes by theme, and create presentation-ready content from research data. 

Thus, Miro Assist is considered perfect for researchers who need to make sense of large amounts of qualitative data and filter it into actionable visuals.

How Miro Assist helps in UX research

Source

Miro Assist enhances research analysis on digital whiteboards. It automatically groups sticky notes, summarizes user feedback, and helps structure research insights visually for teams working together.

Key benefits for UX researchers:

• Organizes messy data into clusters by keyword or theme
• Summarizes brainstorming sessions into usable formats
• Saves time sorting feedback manually
• Helps align teams faster with structured visuals
• Works inside Miro with no extra setup

Standout feature

Its cluster analysis for sticky notes groups data by sentiment or keyword. This becomes handy in checking data in a streamlined manner.

Why we ❤️ it:

The thing we love the most about Miro Assist is that it transforms raw brainstorming sessions into structured, actionable outcomes. This helps us save time and make team alignment easier.

Pricing: 

Miro Assist is available with all Miro plans: Free, Starter ($8/member per month), Business ($16/member per month), and Enterprise (custom pricing).

Dovetail is an AI-enhanced platform designed to organize and analyze user research and feedback data. With Dovetail, your team can quickly identify UX patterns and track market sentiment. 

In fact, it also helps you organize themes from qualitative data, such as interview transcripts and customer feedback. Apart from this, Dovetail's AI capabilities make it easy to perform thematic clustering and auto-summarization, enabling faster, more insightful UX research.

How Dovetail helps in UX research

Dovetail simplifies how researchers handle interview transcripts, notes, and feedback. It uses AI to identify recurring themes, tag insights, and build shareable research reports for product teams.

Key benefits for UX researchers:

• Automatically clusters similar feedback
• Highlights emotional and functional pain points
• Summarizes long research sessions into themes
• Helps track trends across multiple user studies
• Keeps research accessible in one shared platform

Standout feature

It has thematic clustering groups related insights, generating titles for each theme to help teams identify key trends. 

For instance, after analyzing user feedback on a website’s usability, Dovetail might cluster insights under themes like "navigation issues" or "content clarity," helping researchers prioritize areas for improvement. This automatic organization saves time, enhances focus, and ensures that teams can act on the most significant findings without manual sorting.

Why we ❤️ it:

Dovetail's AI tools transform complex, text-heavy data into organized, actionable insights. This helps us enhance collaboration and make UX research more effective.

Pricing: 

Dovetail offers free trials. However, for continuous usage, you would have to subscribe to one of their paid plans. Their plans start at $30 per month (Starter), with advanced options at $375/month (Team) and $1,800/month (Business).

Notably is an AI-driven user research platform known for simplifying the analysis of qualitative data with powerful tools. Some of the tools it uses are video transcription, cluster analysis, and digital sticky notes. This tool helps you generate concise summaries, perform sentiment analysis, and auto-highlight essential insights. Such functions allow researchers to uncover patterns and emotions quickly without manual work.

How Notably helps in UX research

Notably cuts down research time by auto-generating summaries and spotting emotional trends in user feedback. It uses sticky notes and clustering to help teams organize and visualize key takeaways.

Key benefits for UX researchers:

• Auto-summarizes interviews and feedback
• Performs sentiment analysis across studies
• Visualizes themes using digital sticky notes
• Helps spot patterns and emotions quickly
• Saves time by eliminating manual data sorting

Standout feature

Notably’s sentiment analysis gives an instant overview of participant attitudes. This makes it easy to measure positive, negative, and neutral sentiments across studies. 

For example, if users express frustration with a feature, the tool will highlight these sentiments. This analysis is especially useful across multiple studies, enabling researchers to identify recurring patterns and trends in user feedback without manually combing through data. 

Why we ❤️ it:

Notably eliminates the manual work associated with user research, freeing up time for our experts for deeper analysis and creative insights. Moreover, we also find the platform’s ability to generate images from data insights to be handy in reading research reports.

Pricing: 

You can use Notably for $40 per month (Pro plan). However, its team plan is available at $300 per month. There is also an option to get custom pricing, for which you would have to connect with their team.

QoQo is an AI-powered Figma plugin that uses OpenAI’s GPT technology to streamline user research activities directly within Figma. This universal tool supports creating user journey maps, affinity diagrams, and interview scripts. 

QoQo helps generate all this quickly to keep design teams focused on the user experience. Apart from this, QoQo enhances the UX workflow with ease and precision by assisting in building accurate user personas and organizing dense research data.

How QoQo (Figma Plugin) helps in UX research

QoQo is a Figma plugin that helps UX teams turn research into visuals. It builds affinity diagrams, personas, and user journeys right inside Figma, using AI to organize insights fast and clearly.

Key benefits for UX researchers:

• Creates affinity diagrams automatically
• Builds user personas from grouped insights
• Summarizes dense data into visual outputs
• Keeps research and design in one place
• Saves hours spent switching between tools

Standout feature

The ability of this tool to auto-generate affinity diagrams from complex data is a very distinguished feature. This saves hours of manual sorting. 

For instance, if a UX researcher has gathered diverse insights about an app's onboarding process, QoQo will automatically group feedback into themes. These themes can be "ease of use," "visual design," and "instructions clarity." Such automatic sorting saves hours of manual work, allowing researchers to quickly visualize trends and focus on actionable insights.

Why we ❤️ it:

Integrating QoQo with Figma makes it a seamless research asset. This has accelerated insight generation for us while supporting a cohesive design process.

Pricing: 

QoQo offers unlimited access for just $4 per month.

Sprig is an AI-powered micro-survey tool designed to gather in-app user feedback. It has AI features like sentiment detection, emotion analysis, and keyword extraction that automate the review process for open-ended survey responses. This allows you to focus on strategy over data parsing. Moreover, this tool excels at collecting real-time insights directly from users, enhancing your UX research and helping you pinpoint key issues.

How Sprig helps in UX research

Sprig lets teams collect in-app user feedback and uses AI to analyze tone, keywords, and sentiment. It helps identify what users feel and why—right when they interact with your product.

Key benefits for UX researchers:

• Captures live feedback with micro-surveys
• Analyzes tone and emotions in open responses
• Extracts key issues and sentiments quickly
• Enables faster decision-making with real-time data
• Reduces manual review time for feedback

Standout feature

Sprig’s standout feature is its AI-driven sentiment and emotion detection, which turns raw user feedback into actionable insights. UX researchers can upload text data from surveys, interviews, or product reviews, and Sprig’s AI analyzes the tone, sentiment, and emotional context behind the responses.

For example, if users express frustration with a checkout process, Sprig can identify negative emotions like “anger” or “disappointment” and categorize them accordingly. This allows researchers to pinpoint specific pain points, prioritize issues, and personalize solutions.

Why we ❤️ it:

We love Sprig because it makes real-time feedback collection effortless and provides insightful summaries. This is perfect for fast-paced design cycles.

Pricing: 

There is a free plan available for using Sprig. However, to get enhanced solutions, its paid plans start at $175/month.

Synthetic Users is a tool that uses AI to create virtual user-profiles and simulate interactions. This allows UX experts to test designs and gather feedback without recruiting real participants. Moreover, Synthetic Users generates realistic user personas and behaviors, providing scalable feedback that mimics what real users might do. This makes it ideal for teams looking to validate designs efficiently and conduct large-scale testing without the hassle of traditional recruitment.

How Synthetic Users helps in UX Research

Synthetic Users uses AI to simulate real user behavior, so teams can test designs without waiting for participants. It helps run scalable tests quickly and identify common friction points before going live.

Key benefits for UX researchers:

• Runs tests using AI-generated user behavior
• Reveals usability issues without real participants
• Helps validate early prototypes faster
• Reduces time and cost for user recruitment
• Ideal for testing at scale

Standout feature

Synthetic Users have AI-driven user behavior simulation. It offers insights into user interactions at scale.

For example, a researcher could simulate how user activities on a website with Synthetic Users, identifying friction points such as unclear buttons or slow-loading pages. With the help of this data, they can refine the website's design for better usability and conversion rates. 

Why we ❤️ it:

Synthetic Users tackles the recruitment challenge head-on. This makes rapid and scalable testing possible while still providing meaningful insights.

Pricing: 

You can avail of Synthetic Users starting from $99/month.

Perplexity.ai is an AI-powered search tool that streamlines the process of finding relevant information, studies, and data. It delivers detailed answers alongside source citations for each claim by acting like a fusion of Google and ChatGPT. This makes it easier to verify information and assess credibility. Thus, Perplexity.ai is considered an invaluable tool for UX researchers needing fast, reliable insights and context on specific topics.

How Perplexity.ai helps in UX research

Perplexity.ai helps UX researchers gather reliable information fast. It summarizes web content, finds verified sources, and gives context you can trust—making it easier to back research findings with credible data.

Key benefits for UX researchers:

• Finds relevant studies and data instantly
• Summarizes topics with source links
• Helps validate assumptions with reliable content
• Speeds up the research phase
• Supports better-informed design choices

Standout feature

Perplexity.ai provides auto-generated answers with source citations. This makes it a tool that offers reliable information in every search result. 

Let’s say your UX team asks Perplexity.ai a couple of queries or statistics related to web design. This tool will then auto-generate an answer by searching for the relevant data across the web. Moreover, it also lists the references it used to formulate that particular answer, ensuring everything is credible and research-backed.

Why we ❤️ it:

Our team loves Perplexity.ai because it combines speed with reliability, letting us locate well-sourced information faster than traditional searches.

Pricing: 

It is free to use. However, Perplexity.ai also offers a Pro plan, which is available for $20/month.

AI tools have introduced new possibilities in UX research by automating data collection and processing user behavior insights. In fact, it now even predicts design needs based on trends and analytics. 

Moreover, they can handle vast datasets quickly. This helps identify patterns that inform decisions on user interface, content layout, and engagement strategies. Thus, AI-powered tools are considered excellent for tracking quantitative metrics and offering initial insights, making the UX research process more efficient.

However, AI still has limitations. It lacks the understanding of human emotions, behaviors, and motivations. These are critical factors in creating truly empathetic, user-centered designs. Moreover, AI cannot fully grasp context and cultural subtleties or anticipate unique human responses to design elements.

Not entirely—AI enhances UX, but the expertise of professional UX researchers and designers remains essential. These skilled professionals bring a depth of empathy and creativity, ensuring designs are both effective and meaningful for users. This is where Tenet can help, blending technology with human insight to deliver exceptional UX.

At Tenet, we believe exceptional UX design drives growth, user loyalty, and revenue. Our structured process guides clients from onboarding to delivery, clearly explaining each phase's purpose. 

We fill knowledge gaps by offering insights beyond UX, covering areas like email marketing and SEO, which has made us a trusted partner for brands like Gartner. 

Clients can visualize their products through mockups and prototypes, and we provide post-launch support to adapt designs as needed. 

With transparent pricing and full ownership of deliverables, we ensure clients know exactly what to expect throughout the process.

Still unsure? Take a peek at how we helped our client. To see our past work, check out our portfolio of UX research and design.

AI tools for UX research automate tasks such as transcription, sentiment analysis, data clustering, and insight extraction. These tools help UX teams analyze user feedback faster, identify patterns in behavior, and generate actionable design insights. Popular tools include Looppanel, ChatGPT, Maze, and Dovetail.

AI tools improve UX research by reducing manual effort in organizing and analyzing data. They auto-tag transcripts, summarize interviews, and cluster qualitative insights. This allows UX researchers to focus on strategic decisions and user-centered design improvements.

AI tools cannot replace UX researchers. While they assist in processing and organizing data, human experts are essential for interpreting emotions, understanding context, and designing meaningful experiences. AI complements UX professionals but does not substitute them.

There is no single best tool—each serves a different purpose. For transcription and tagging, use Looppanel. For ideation, ChatGPT is ideal. For automated testing, use Maze. For clustering and qualitative analysis, Dovetail and Notably are effective.

Yes, AI sentiment analysis tools like Notably, Sprig, and Dovetail offer reliable sentiment detection. They analyze tone, keywords, and emotional cues to help identify user satisfaction or frustration, supporting faster, data-driven design decisions.

Use AI in the UX research process by collecting user feedback, then applying AI tools to transcribe, tag, and summarize insights. User research tools like Looppanel and Notably analyze qualitative data, while ChatGPT identifies themes and Maze automates testing. This accelerates insight generation and reduces manual effort.

Yes, tools like QoQo and ChatGPT can help build user personas by analyzing qualitative feedback and grouping behavior patterns. They summarize common user goals, frustrations, and motivations into persona profiles for design reference.

Yes, several tools offer free plans. ChatGPT has a free version, Perplexity.ai offers free research capabilities, and Maze allows one study per month. Miro Assist is also available on Miro’s free plan.

AI tools lack empathy and cultural understanding. They cannot interpret nuanced human behavior or emotional context as effectively as trained UX researchers. They are best used to enhance—not replace—human analysis.

Use AI to speed up repetitive tasks, uncover patterns in user feedback, and scale testing. It improves efficiency, ensures faster insights, and enhances team collaboration through structured data processing and visualization.