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In the era of AI, everyone has the ability to build products worth using. Making the right products at the right time becomes the key differentiator here: Nowadays, it’s about how fast user needs are identified and acted upon. This article gives an insight on how to tackle this challenge successfully and which benefits come with performing user research.
Understanding human behaviour
User research helps ensure products and services are designed around real user needs, behaviors, and emotions - keeping the human experience at the center. [1][4] AI can help researchers gain a more comprehensive understanding of users by [6]: Generating user personas and journey maps based on data Predicting user needs and behaviors through machine learning models Personalizing research methods and stimuli based on individual user characteristics This deeper user understanding can inform more targeted and effective product design decisions. With all the benefits that will be covered here, there is still one thing to mention: AI systems are powerful but lack true human understanding and empathy. That is why researchers are an important resource in every company - they mastered empathy and know how to understand users [2].
Data-driven decisions are a no brainer
Relying on assumptions or anecdotal evidence can lead to misguided decisions. User research provides empirical data that supports informed decision-making, ensuring that strategies and designs are based on real user needs and behaviors [6]. User Research is also great in evaluating KPIs and if products perform as desired. The most important thing to consider here: Success does not come from the collected data, but from the actions that are performed after analysing it. Evaluating numbers and deriving actions from it can lead to staying up to date with the competition or even better: to gain a competitive advantage.
Designers bridge knowledge gaps
The role of a ux designer / researcher is shifting towards guiding overall product strategy based on deep user understanding[4]. Researchers and designers thrive if they manage to gather knowledge and use AI to the full potential to fulfill not only the needs of the users - but also themselves as the users of AI tools. This can also be a great chance for UX professionals to raise their voices in important alignments regarding vision and strategy - not only for one product, but rather for complete organizations. Designers now finally may have the chance to sit “on the big table” and to bring their point of view into discussions more often. As there is still a huge gap to bridge in companies regarding the knowledge and the right handling of AI, User Research helps organizations understand how AI is changing user experiences [3]. With AI’s potential for deepfakes and blurring humand-machine boundaries, user research ensures products to remain authentic and true to real humand needs, avoiding misalignment or deception.
Saving resources with the right Research
User Research saves resources, as features can be tested for desirability and proven as a user’s need before the actual rollout. If testing reveals features are not desired or lack crucial characteristics, it is much easier and cheaper to improve and optimize and come back once again with another test instead of finding it out afterwards.[6] With the help of AI, user testing never has been faster or cheaper: There are a lot of tools with built-in AI out there, helping researchers with summarization, analysis, hypothesis generation, interview question generation and much more for a very affordable price. User research can either be qualitative (how users think and feel about a product and how they behave) or quantitative (objective insights with a lot of users). Choosing the exact research methods will depend on product phase, desired insights or availability of time and other resources. And even here AI can help you: Firstly in choosing the right method by analyzing the current situation and context of the product, and helping you generating interviews or quantitative surveys afterwards. Here are a few tips for choosing the right method:
Test features, not products: Do not try to test your whole product with one prototype (if you have one) and one test. The prototype gets immensely complex at a certain point and mistakes are unavoidable. Also, the test has no focus if you test the whole thing. It is much easier in execution but also preparation, if tests are small but continouus. Therefore there is also enough time remaining to work in the feedback from the users.
Find out the goal of the test: Depending on the goal you have with research, methods will change. A good indicator on whether to choose qualitative or quantitative methods is: Do you want to know how users use your app and behave or do you want a lot of opinions and objective insights you can measure?
Use AI: Do not hesitate to describe your scenario (but be compliant!) to an AI of your choice and let it find out the right method. If the result matches your assessment - very good. If not - also fine! Having a second thought about your assessment is not a bad thing. Maybe consider to use both methods then.
Do not close your eyes to change
AI frees up time and space for designers and teams to focus solely on the user rather than technology or tools itself. It is revolutionizing the UX field in many ways - be it testing, generating ideas, helping with analysis or supporting with cumbersome tasks. Change is a constant factor in life and especially in tech and the UX profession, that’s why we should embrace the opportunities coming from the rise of AI. Instead of demonizing it and being afraid of it, we should see AI as a design partner that supports us in everyday life.
References
[1] https://www.userlytics.com/blog/ai-for-ux-research/
[2] https://www.uxtigers.com/post/research-humans-ai
[3] https://adamfard.com/blog/ai-ux-research-trend
[4] https://maze.co/blog/ai-meets-ux-research/