AI is transforming our world. It's helping us navigate better and faster, gives us personalized recommendations on streaming platforms like Netflix, and even diagnoses diseases.
Today AI has become a part of our daily lives and has proved to be a revolutionary tool across most industries. With businesses seeking to improve productivity and efficiency, the adoption of AI is rising in the business domain as well. Did you know that 35% of companies reported using AI in their business, and an additional 42% reported exploring the use of AI? And this number is only going to increase in the coming years.
There are practically no limits to how you can use AI solutions as they are developed and implemented in organizations. But in this article, I want to explore AI's role in user research. It may not be as glorious as helping cure cancer, but it can help companies better understand user needs, remove bias from user research, and provide data-driven insights into user behavior.
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Though there are a lot of benefits to using AI in UX research, we need to get to the essence of the value AI can provide while being clear on what it cannot do. Here is what AI can and can't do in user research.
Where AI Can Help in User Research
AI is still in its early no matter what you hear, AI will not replace UX researchers or designers but will aid them.
Though it can do several things from cleaning and organizing data to analyzing it in a nuanced manner, it won't be able to conduct in-depth interviews or focus groups with people because that needs that "human touch."
Here are the areas where AI can legitimately help UX teams.
1. Remove Bias
User feedback is fundamental to building successful products. However, your product will only be as good as the feedback you get. So, you need to make sure your respondents are giving you unbiased information. Otherwise, you might steer your product down a cliff. And that's where AI, or AI-powered research tools can lend you a hand, as they don't rely on stated responses.
What I mean by stated responses is that as you make the user go through a task and as they do so, you ask questions, and users mostly answer these on a scale of 0 to 10, which creates a lot of bias.
The AI-powered tools come with features like session recordings and eye-gazed based heatmaps. So, by implementing these AI-driven user research tools, you can easily supplement user research and negate biases.
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2. Transcribe User Recordings
Conducting user interviews takes time, but analyzing all the sessions to derive insights from them is even more time-consuming. For faster retrieval of key user insights from these interviews, transcribing tools can help and have become much easier and more accurate with AI.
With a platform like Affect UX, you can transcribe live interviews in real time as well as imported recordings. Also, you can go from user recordings to tagged, searchable snippets in a matter of minutes. So, you can easily find and share the ‘moments of truth’ where the user shared honest feedback throughout these conversations. And a collection of these highlights can serve as validation to make data-backed decisions.
3. Surfacing Insights
In this age of data abundance, most businesses struggle with making sense of data and turning it into insights. AI can help with that as it makes digging through a pile of data points easy.
AI-powered software can automatically analyze data from any source and deliver valuable insights. With data analysis, AI can help UX teams take a large amount of research data and find trends and patterns in user behavior that may have gone unnoticed.
AI-powered user research platforms like Affect UX can make it easy for you to gather and organize feedback from various sources in one place and uncover actionable insights.
What’s more? Affect UX is powered by Voice AI that gives you deep insights into the user’s voice tonality and confidence level to accurately understand the intent of the feedback.
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4. AI-Powered Translations
We don’t all speak the same language, and most of you know how tough it is to conduct user research effectively when you don’t speak the same language as the user - it can be frustrating.
Luckily translation has become easier with AI; allowing product teams to test their products or services with users who speak different languages and still gain insights into how their target audience interacts with their offerings.
In short, translation services allow researchers to conduct user research globally, helping them gain valuable insights into the behavior and needs of users from different countries and cultures.
What AI Can't Do
While AI can save UX researchers a lot of time, automating tasks and allowing them to focus on the underlying insights and data, AI should be viewed as support for user research, not a replacement for real-UX research.
1. Creating Questions and Asking Follow-up Questions
The main goal of conducting user research is to get deep insights into users, and that can only happen when you ask the right questions and follow up the responses with more questions. But AI can't craft questions or follow-up questions. Only UX researchers can probe deeper into user responses and use their judgment and experience to ask the right questions and uncover insights that may not be apparent from initial user feedback.
2. Creativity and Innovation
While AI can provide data-driven insights, it may not be able to generate creative and innovative ideas for improving the user experience. This is something that only UX researchers can do. Only they are the ones who can come up with new and innovative solutions to UX problems.
Artificial Intelligence Isn't Going Anywhere—It’s Here to Stay
AI is no longer the future—it's very much the present. Soon, leveraging AI in research will no longer be a nice to have but a must have. And yes, while AI will not replace UX researchers, UX researchers using AI will replace those not leveraging AI.
So, start leveraging AI in user research by signing up for our AI-powered integrated user research platform Affect UX today, and begin delivering a flawless user experience fast.
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