Humanly’s Playbook: How to Turn 55 Customer Interviews into Product-Market Fit

Every founder knows they should talk to customers. But executing customer research in a way that actually drives product-market fit? That’s a different story entirely.

In a recent episode of Category Visionaries, Humanly founder Prem Kumar revealed how his team turned 55 strategic customer interviews into actionable insights that shaped their HR tech platform. The key? A systematic approach that went far beyond casual conversations.

The Research Framework

Rather than conducting random conversations, Prem created a detailed tracking system: “I have a spreadsheet that kind of broke them out by industry, by type of demographic, by pain points,” he explains. This methodical documentation allowed the team to identify patterns across different market segments.

The approach yielded unexpected insights about candidate experience. “Even the candidates that didn’t get the job rated it very strongly, which was a surprise,” Prem notes. “Through talking to candidates and talking to recruiters, [we found] that really setting expectations with candidates, telling them what the next step is… treating them with respect and kind of following through, even with a simple, not like auto generated follow up email, can go a really long way.”

Getting Beyond Confirmation Bias

One crucial lesson from Humanly’s research process was the importance of approaching interviews without preconceptions. “Having a structure to it. So instead of just saying, hey, I’m going to talk to 50 people, what are the outputs you’re looking to get out of it? What are you trying to ascertain? What thesis do you have going in?” Prem shares.

He emphasizes the importance of leaving ego at the door: “Getting rid of ego is important. It was very easy to push them down certain way. So basic user research but even though people know they need to do that, unfortunately I don’t see that always happening.”

Converting Research into Revenue

Perhaps most impressively, Humanly turned their research participants into their first customers. “Some of them actually turned into customers later,” Prem explains. “I can come back three months later and say, ‘hey, that thing you said you really wanted, we’ve actually built now.'”

This approach helped shape both their product development and go-to-market strategy. Instead of trying to solve every hiring challenge, they focused specifically on high-volume recruiting. “We’re very much focused on these high volume, entry level roles where there’s pain points around having to do seven phone screens a day and write seven sets of follow up emails,” Prem notes.

Scaling the Insights

The insights from these initial interviews continue to shape Humanly’s growth strategy. Their focus on candidate experience, revealed through early research, has led to impressive metrics: “We’ve passed a million candidates that we’ve engaged with and the average rating they have of the experience is about 4.8 out of five.”

More importantly, these early conversations helped define their category positioning. “When people think conversational AI, they’re thinking chatbot,” Prem explains. “But to me, conversational AI for recruiting is about any conversations you’re having with job candidates, not just the automated ones… how do you make that more efficient and more equitable?”

This focused approach to customer research did more than just validate their initial hypothesis – it helped Humanly build a product that solved real problems in ways their customers actually wanted. For founders looking to achieve product-market fit, the lesson is clear: it’s not just about having conversations, it’s about having the right conversations and systematically acting on what you learn.