HqO triples research efficiency and delivers a user-driven product to market faster with Maze
HqO triples research efficiency and delivers a user-driven product to market faster with Maze

HqO triples research efficiency and delivers a user-driven product to market faster with Maze

Learn how HqO removed design guesswork by introducing Maze to collect customer insights and optimize their UX Research process.

About HqO

HqO creates workplace experience technology that transforms how people connect with each other and the places they work.

Industry

Tech & Software

Opportunity

Optimize their internal UX research processes and leverage unmoderated research to meet increasing customer demands.

Key Maze features used

Prototype Testing

Panel

Share

3x

number of projects with user research

HqO is a B2B2C organization transforming how people connect with each other, and the places they work, through the HqO Property Experience Platform. HqO’s software makes it easy for companies to create modern property experiences through world-class services that allow workers to thrive.

After recent substantial growth, HqO needed to optimize their internal UX research processes to meet increasing customer demands, without compromising on quality. Lead Product Designer, Anna Leach, saw the opportunity to streamline her team’s productivity and expand their research function by moving to efficient, unmoderated research—with the help of Maze.

The limitations of moderated testing

Previously, Anna’s team spent weeks doing moderated testing, which in HqO’s case meant both online and face-to-face research. The team was spending significant time planning their research sessions and trying to recruit test participants. Combine this with the additional resources needed to orchestrate and run the sessions, and over time the challenges of using moderated testing for every project began to outweigh the positives—ultimately leading to less insights over time.

Moderated research certainly has its place, with UX research methods like focus groups and field studies unequivocally benefitting from moderation, but in today’s world of continuous product discovery and remote-first research, feeling tied to exclusively moderated testing can restrict the speed at which you gain insights—and how quickly your product progresses.

While moderated testing has some key uses, it's not as efficient for every project when you're trying to gather insights quickly and continuously.

Anna Leach, Lead Product Designer @ HqO

Anna Leach, Lead Product Designer @ HqO

HqO found that the time required for moderated testing versus the pace of insights needed meant concepts were not always tested properly. Anna notes: “We had to spend a lot of time in recruitment, facilitation, transcription, and analysis, which meant during that time, we weren’t actively collecting insights.”

Due to time constraints of the research process and the pressure of fast-paced product launches, HqO would have to go to market with designs the team knew may be assumption-heavy.

“When we had to cut or reduce user research, there was an increased possibility that a solution might not work perfectly for a customer, or that users may have challenges using the platform,” explained Anna.

Unfortunately, that risk sometimes turned into additional costs and time needed to re-work elements which—with more efficient user research—could have been caught earlier. So, what’s the solution?

Establishing a scalable research practice with Maze

Anna’s team started their research refresh by looking for a tool that could help them quickly validate and test new solutions, as they worked on them: “We wanted to make sure we were going about solving the problem the right way, but we also wanted to keep in mind speed to market.”

By considering a remote and unmoderated research option, HqO realized they could achieve the speed, efficiency, and accuracy they needed from user research, without sacrificing the quality of data collected.

They reviewed a number of different solutions but eventually decided to go with Maze. For Anna, the decision really came down to two main things: pricing and speed. Maze offered everything HqO needed at an affordable price, and the team could view test results quickly, getting heatmaps, feedback, and analytics to make informed decisions and iterate rapidly.

HqO now regularly uses Maze for their research needs, like testing assumptions at scale, validating concepts and testing content, and recruiting participants to test their Figma prototypes.

Improve research efficiency like HqO

Empower user research with Maze. Collect customer insights faster and fuel decisions that improve your product continuously.

The Maze Panel and Reach are a great way for us to get results quickly. We’re getting answers within 24-48 hours instead of weeks—it’s been a game changer for us.

Anna Leach, Lead Product Designer @ HqO

Anna Leach, Lead Product Designer @ HqO

Maze also enables HqO to have a more consistent research practice. Now, Anna’s team is conducting user research more regularly to validate new features and iterations; providing them with customer insights early in the product development process and empowering the team to release features with more confidence.

Thanks to Maze, we’ve been able to triple the number of projects where we utilize user research, which helps us fuel insight-driven decisions at scale, and deliver the solutions to our customers faster.

Anna Leach, Lead Product Designer @ HqO

Anna Leach, Lead Product Designer @ HqO

As a result of adopting Maze, Anna noticed a substantial increase in the team’s productivity and efficiency: “We've been growing rapidly and managing many projects across a small team, so we have to ruthlessly prioritize to get the best value out of our time. With Maze, we've gained time and efficiency by being able to incorporate user research more regularly.”

From using only laborious and time-consuming moderated testing, to being able to incorporate streamlined, data-rich unmoderated research, HqO have seen an incredible turnaround in their research function since implementing Maze. We can’t wait to see what they’re going to do next.

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