Have you struggled to find research participants for your studies? Basel Fakhoury can empathize.
Before he co-founded User Interviews with Dennis Meng and Bob Saris, they created Mobile Suites, an app for travelers to order hotel services. To find research participants, they had to buy refundable flight tickets, clear airport security, and cancel the tickets. Once inside, they approached travelers to ask questions.
While Mobile Suites had a core value problem, they realized that most businesses were struggling to find participants for user research. They addressed the gap by founding User Interviews.
Basel spends a fair bit of time understanding the tools companies use to conduct research. He spoke to HeyMarvin’s co-founder and CEO, Prayag Narula, about how businesses can build their UX tech stack to streamline research workflows.
Read on to learn more, or watch the full conversation about the Modern Research Tech Stack.
The Three-layer Framework
Basel’s framework for building your research tech stack is simple but effective. He divides all tools and services into three layers.
- Testing tools: This layer is divided by methodology. Companies may use different products for surveys, moderated interviews, and diary studies. Check out the research tools map User Interviews releases annually for information on specific tools.
- Participant tools: The second layer focuses on research participants, where User Interviews are specialized. These products help users find the right participants. Some also help manage participants across studies and teams.
- Insights repository: The third layer focuses on categorizing data and generating insights companies can use to make decisions. This is where Marvin fits in, with a range of tool integrations and AI qualitative analysis capabilities.
How it Started and How it’s Going
The first UX tools aimed to offer solutions across all three layers in the mid-2000s. In recent years, however, we’ve experienced a shift toward “unbundled solutions” that deeply solve problems within an individual layer.
“I think all of us in different layers of the stack are focusing on being the best they can and putting all of their effort into one or two things,” Basel said. “Then we need to figure out, ‘How do we work nicely with each other so that our end users, the researchers, can get all the benefit of tools that are spending all of their time on one part of the stack?’”
The key here is to reduce friction while working across multiple tools. Businesses realize they need to integrate well so users have a seamless experience across products.
Users then stack these efficient tools together, and voila! That’s a UX research tech stack.
Benefits of Choosing an All-in-one UX Tool
There are benefits to choosing a bundled solution. One tool for all three layers makes it easier from a business and administrative perspective.
Companies enjoy smoother user and access management and usually lower costs. The decision to bundle must take into account the team size, research framework, and company size.
Basel explains this using the example of User Interview’s offerings. Their product Recruit can help companies of all sizes and UX maturity levels find participants for research.
On the other hand, Research Hub is popular among enterprises, as it has more researchers spread across teams. There is a greater need to streamline coordination, segment participants, and ensure that the same participants aren’t approached too often.
Benefits of Unbundling Your UX Tools
In some cases, combining multiple UX tools may be less frictional than choosing one “end-to-end” solution.
Companies building a niche, best-in-class tool are especially invested in integrating with other layers of the stack. As Prayag said, “That’s their bread and butter.”
They want to ensure that their tools complement each other and that users have efficient workflows to conduct research seamlessly at every step of their process.
When an organization offers an all-in-one tool, multiple product managers handle different parts of the stack. The coordination between teams must be brilliant for the stack to work smoothly.
They also need to be aligned entirely on their product goals. Determining their core focus can be more challenging for these companies.
Because it’s one tool, intuition says everything should flow much more smoothly.
But it actually might be like, “fitting a square peg into a circular hole when they’re moving between different layers,” Basel said.
AI’s Impact on the Modern Tech Stack
“I think the insights layer is the most ripe for AI,” Basel said.
AI makes it quicker and easier to categorize the data, organize it into insights, and even share it with the rest of the organization.
At Marvin, these features often get the most customer love, too.
In the testing tool layer, there’s been an explosion of AI-moderated tools. These products offer the breadth of a survey and the depth of an interview. However, we’ve yet to find out how many participants are comfortable talking to an AI moderator.
The participant layer, too, has seen synthetic users, which are AI-generated customers built on user personas. For User Interviews, this is currently not a focus area. Basel believes synthetic users don’t yet offer the same level of insight as human users.
Researchers should be careful about using both synthetic users and synthetic moderators in one tool stack. Avoiding AI models talking to each other to generate insights is important.
Basel pointed out that rather than focus on replacing a manual process with AI, companies would benefit from thinking, “What’s a new orthogonal way to think about things now that we have this technology?”
For example, when newspapers initially moved online, they used the new technology to merely publish articles on a webpage. With subsequent versions, they built features that let readers interact with their content, which amplified coverage.
User Interviews is using AI (in the form of LLMs) to improve how they match research participants to researchers. With this, they’re helping businesses better understand who to talk to. Companies can then customize personas not just to a product, but also to a study and even individual questions.
Democratization of UX Research
When companies started UX research in-house, they began with one researcher. Eventually, they grew teams as they realized the value of research.
In the last few years, research has become vastly more democratized, with designers and PMs also getting into it.
“No one’s putting the genie back in the bottle,” Basel confirmed.
However, companies have realized that because people conduct research in different ways, they need to add guardrails and checks. It’s also important to make everyone aware of the capabilities of their tool stack. That has led to more formal research operations, with centralized teams for tool buying and research guidelines.
Research operations look for tools that can meet the requirements of all project stakeholders. This encourages new tools to adapt and be flexible for a range of users.
Democratization doesn’t mean that companies are going back to having one tool for all layers of the stack. Surprisingly, this is driving more unbundling than bundling. The centralized team is better able to recognize the priorities of each researcher and equip them with the right tools.
Identifying a Tech Stack That Works for You
Questions like, “When to spend on a tool?” or “When to bundle or unbundle?,” become easier to answer as companies become more mature. With time, the nuances and research-specific requirements become evident.
“At the very early stages, there’s sometimes a benefit to being scrappy,” Basel said. “I still think the biggest research tool is probably Zoom, which is not a research tool.”
Prayag agreed that people underestimate off-the-shelf research. Interestingly, the tools integrated most often on Marvin too are Zoom and Google.
No matter which approach you choose, your research should feel efficient and seamless. Your tool stack should enable you to share your findings with the right people. Spending more time on analysis and seeing data from all angles has multiple benefits.
The obvious one is helping decision-makers take the right steps for the business.
The other is showing the ROI on research, which ensures that you can keep talking to your customers to gain valuable insights. Dr. Ari Zelmanow of Twilio has some great suggestions on rethinking research to focus on this.
The industry has evolved a lot in the last couple of years, which has led to many new tools and services. With these, building the right research tech stack is within your reach.
The conversation also explored a range of other topics, including how to ensure neurodiversity distribution in participants. Basel and Prayag also discussed how to make it easier to switch between tools. Watch the entire video about research tech stacks.
