How AI can be used to help UX Researchers
Without a doubt one of the biggest (tech) trends we have seen in 2023 has been the arrival of truly smart AI through the likes of ChatGPT. It has really highlighted the strengths and capabilities they can, and will offer. It has also surfaced existing products that haven’t gotten the usage they have warranted, despite being having coming to fruition a while ago now.
AI is also something that is clearly here to stay. While there are concerns around what this means for peoples jobs or how it could affect society; as with a other significant developments in human history, it will have a profound affect. Like the invention of the printing press or creation of the world wide web, it can be used for the better and to improve and enhance what we are capable of and revolutionise the way we work. One of the most important things to remember is that behind every AI product there is still the need for a human to build it or operate it. I, therefore, see it as a new tool like Zoom or Gmail that will allow us to work more effectively and more efficiently. It frees up time for us to be able to focus our attentions on something else, develop new best practises or innovations within the field. In the article below, I share my initial thoughts on how AI products can potentially be used to help UX Researchers enhance and build on their research.
I was recently working on a team that was focused on helping users build better health habits. Building new habits is a very complex field, with many experts sources dedicated to this topic from whom to get the information from. One such source was actually a book that I had started reading at the time called Atomic Habits. I found it a fascinating read with a lot of relevant information, but it was hard to recall everything from it that we could take away. In this example I used AI (ChatGPT) to summarise the key takeways from the book about how to build better habits. We, as a team, then had a bitesize collection of insights on how we could help users build better habits that we could either explore and research more, or take away and develop.
Imagine an even more personalised version of ChatGPT. One that stored all the research and insights that you and your UX Research team created, and that your stakeholders could ask questions directly to. Image an advanced repository. As AI and language learning tools develop something like this could easily be achieved. This will really help create a user and research first approach for businesses, as they will have a huge amount of relevant information to tap into at the click of a button. Whether its asking information about how users found the homepage experience, or how they start their user journey, AI could help realise this potential.
One of the main starting points when conducting discovery research is to collect all available information on the topic. Whether its internally from other research teams such as customer insights or the analytics team, or secondary research that is available on the web its a vital part of forming and building the bigger picture. AI could be used as a way to quickly gather relevant information on a specific topic such as ways people are currently dealing with jet lag, or how long it takes them before buying a television.
It can often be difficult to get users to engage with a survey to get the feedback that you need. There are various studies that suggest different approaches to increase engagement and completion rate, such as ensuring there is clear benefit to the user, or making them feel like they are part of an exclusive panel and so their voice is really important to hear from. Either way capturing their attention to increase the response rate starts with the intial hook or headline. There are now some really good AI tools that will help you improve the headline that you have created based an initial version. I actually created the header for this article using one by Coschedule. This is only one such user case for having AI tools that can help with copy creation but it can be used in other circumstances.
Engaging presentations are a key part of telling the story of the valuable research insights that we have gathered. As well as having the message clearly communicated, its important to have an engaging pack, and often that will mean having visuals that can support the message that really bring the stakeholders on board. It can be challenging trawling through the endless feed of imagery that you can find on the web, and that is where AI can come in so handy.
Instead of searching on a browser for what you want, ask the AI to create the image in your head.
The image that will land the message to your team that will not just resonate with them, but sitck in their memory. Midjourney has emerged as one of the leading players in this field and having tried it myself I have been very impressed by its potential. There are additional options too such as Illustroke which creates vector images based on the same input and Stockimg which generates stock photos.
This is probably one of the most exciting potential on my list. Video generating. While this isn’t something they are capable of yet (to my knowledge), I have come across companies that are looking at developing this. It also feels like the next natural step to the imagery generation mentioned previously. This really does take engaging content to the next step, moving us from being story tellers to film makers. Image being able to type in a story of what you have learnt or what the user goes through and have a video or short movie made that relays that information. There is a reason why Tiktok, Youtube and Instagram are so popular. Humans love videos, they love the story telling and they love the nature of it compared to reading or listening as it is far more engaging by drawing people into the story. This AI potential can be seen with Google Imagen Video here.
Conducting moderated sessions with participants remotely has now become the norm. Since the COVID pandemic UX Researchers have discovered the benefits of doing this, with the main one for being able to to access a new user group as you are no longer restricted by the accessibility of your test location. As a result of this though, there could be times when you struggle with background noise because of where you are. Whether its noisy builders or neighbours, a busy cafe or road traffic; these sort of disturbances can be a distraction to both you and your participant. Thankfully there are now AI solutions to help limit this including Krisp AI
Overall, while AI is innevitably here to stay, I do not fear its impact on UX Research. For those who understand UX and UX research, you will know that product teams are trying to tackle very specific problems that are unique to their product and user base. It is not something they can therefore ask AI the answers to if they truly want to tackle their users problems. UX researchers will need to be there to continue to build the data and insights and have the specific skills that mean its been collected correctly, with minimum biases to maximises the credible and trustworthiness of the insights. UX Researcher are also guardians of the user. As long as product owners have to balance the business needs with the users goals there will also be compromise on the users experience, which is why a UX Researcher along with their voice and knowledge will be so important to protect what will be released for people to use. They are owner of the insights and someone to help drive the changes.
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