3 key lessons for getting user experience insights in a new market

Our Senior User Researcher, Lisa Laeber, delivered an insightful talk on discovery research in complex environments at August’s UX Crunch event. Lisa's talk explored core strategies for gathering user experience insights in a new, rapidly evolving market like AI. 

Here's a deep dive into her talk and some key takeaways from other speakers at the event.

How to expand into the AI market: 3 critical lessons 

In 2022, we noticed a shift in how researchers were using our platform. New users were tapping into our participant pool to create data for training AI models. 

Spotting a gap in the market, we decided to develop our platform to meet their needs. This led to a discovery research process in which we explored uncharted territory to uncover new opportunities.

We had to deal with complexity at different research stages, most critically:

• Scoping
• Recruiting
• Communicating

Let’s dig into the challenges we faced at each of these stages and what we learned as we overcame them. 

1. Scoping: Understand your stakeholders’ journey 

During the scoping phase, it's crucial to lay out the land before embarking on your research. This involves breaking down the project and defining the research question, purpose, and responsibilities. One essential strategy is to understand your stakeholders' journey—where they are now and where they want to go. A powerful question to ask here is, "What's next for you?"

For instance, if a stakeholder says the research should inform whether to build a separate AI product, you can ask questions such as, "What would you need to see to make this decision?" Responses could range from identifying a business opportunity to evaluating the feasibility of the problem. 

It’s also important to ask the opposite question: "What would you need to see to not move forward?" If you take your stakeholders’ position too directively, you risk confirmation bias. Be guided by their angle - what kind of evidence they want to see - but not the desired outcomes.

By breaking down these indicators, you can clarify the evidence needed and focus your research questions accordingly.

Key takeaways 

• Position yourself as an ally and guide for your stakeholders.
• Understand their goals and clarify what they need to see to make informed decisions.
• Avoid confirmation bias by ensuring your scoping questions don’t lean towards a desired outcome. 

2. Recruitment: Gather expert insights with a flexible approach

When laying the foundation for understanding a new market, desk research would be the ideal first step. But how do you do this for a market like AI - where the market is so new, rapidly changing, and available information is limited? 

This is where expert interviews become your primary strategy for gathering user experience insights. 

Talking to your existing users in this market will provide some initial insights, but it might not be enough. Early adopters are often different from the mainstream market, making it challenging to generalize findings. 

So, you need to learn from non-customers in the field. But recruiting in this market can be challenging. When we attempted to recruit non-customers in the AI space, we encountered several difficulties:

• Snowball sampling - generally a great strategy where exisiting customers recommend or introduce you to relevant people in their network - didn't work. Users were secretive about their networks due to the competitive nature of the industry.
• Recruitment agencies quickly became too expensive as they started to face challenges in locating relevant experts for us.
• Personal connections, though fruitful, were limited, and outreach via LinkedIn and social media proved ineffective. The market was so well funded that monetary incentives failed to convince. 

So, how can you adapt when faced with these roadblocks? The key here is to be flexible - and redefine your gold standards. 

We shortened interview times, asking for just 15 minutes instead of 45. Offering donations over incentives helped to reduce noise during social media outreach (although it didn't significantly increase recruitment success). We also hired one of the experts we interviewed as a consultant to unblock our general discovery and product teams’ iterative development processes. While not ideal for representativeness, this approach let us move quickly and minimize recruitment loops.

Key takeaways:

• Flexibility is crucial when dealing with a niche and rapidly changing market.
• Redefine your gold standards and adapt your recruitment strategies to the environment you're in. 

3. Communication: Be the tour guide to your insights 

Research doesn't end once the analysis is done. Communicating findings is a crucial part of a researcher's job. 

Research communication means moving from being your stakeholders' scout to being their tour guide. You don’t want to hand over a travel guide to your stakeholders and wish them good luck! As a good tour guide, you want to meet your audience where they’re at and curate an experience for them.

The two key points to remember here are to avoid information overload and customize outputs together with your stakeholders, so you can close the loop on "What's next for them".

• To avoid information overload: combine new information with known concepts.
• To close the loop on what's next: overcommunicate.

We combined graphical representations of different AI use cases (new information) with the known concept of product market fit, highlighting areas of good fit, areas that needed tweaking, and areas that required substantial development efforts.

To overcommunicate, offer different formats to fit different stakeholder needs. For example, we: 

• Ran a SWOT analysis with key stakeholders to discuss our strengths, weaknesses, opportunities, and threats in the context of building a separate AI product.
• Created an ideal customer profile for the AI training market and broke down our AI persona into end user and decision maker.
• Ran an AI Learning Event for everyone in our Tech and Product teams, which showcased our learnings and invited ideation around pain points.

Key takeaways

• Actively guide stakeholders through insights and close the loop on ‘what’s next’.
• Avoid information overload by integrating new insights with familiar concepts.
• Overcommunicate to ensure your research findings resonate and drive action.

Our top highlights from other talks

The UX Crunch event featured a plethora of insights from leaders and experts who spoke at the event. Here are just a few of our top highlights.

Bergen Larsen, Design Leader at BP, presented a fascinating talk on managing large-scale data and the challenges associated with it. The sheer volume of data can be overwhelming, but with the right tools and methodologies, you can harness it to drive meaningful insights.

Vee Rogacheva, Head of Product Design at Go.Compare, shared UX methodologies for enhancing user journeys within the product. She emphasized the importance of data collection tools like Prolific in understanding user behavior and improving the overall user experience.

Robert Graham, Global Head of UX at AstraZeneca, discussed the UX projects they are working on across different audiences. He highlighted the unique challenges of working with niche participant groups and the importance of tailored UX strategies.

Need fast access to engaged participants for user experience insights? Prolific can help. Learn more about how our platform can help you gain useful user feedback.