How Hatch Gained Rich Qualitative Insights at the Speed of a Product Launch

Launching a New Hatch Product Requires Deep Understanding of a New Target Customer 

On August 4th, Hatch launched the Hatch Sleep Clock, the brand’s first bedside sleep tracker. Building a product that met the standards of the Hatch team was a challenge and understanding the person they were building it for was non-negotiable.The team needed to clearly understand their audience to develop positioning, messaging, and both app and product experience to have a successful launch. 

Amanda Amyx, Hatch's Senior Director of Design & Research, needed a research solution that would allow her team to both gain deep qualitative insights and move quickly. Strella came in at a pivotal moment: just as the team moved into the core development of the product. The team had previously completed a rigorous segmentation project that had told them which slice of American consumers to target. However, a segment on paper wasn't the same as knowing those people. 

"We knew on the surface, a very bird's-eye view, that they were right for us, but deeply knowing them was going to require a lot more research."

Amanda Amyx

The Challenge: Gain real customer insights across marketing and product at the pace of a new product launch 

The launch calendar for the Hatch Sleep Clock left little room for traditional research cycles, yet a steady stream of decisions still needed real customer evidence. To make matters more difficult, the questions didn't arrive neatly. 

"There was a period of months where almost every week we had some kind of new question," Amyx said, “‘what does quality sleep mean to this person? What does bedtime mean to them? when have they ever gone to great lengths to get a good night's sleep?’ Individually small, together they were the difference between guessing at a new consumer and actually understanding one.”

In the past, those one-off questions would pile up until they justified a more robust survey, by which point the decision it was tied to had usually already been made. When a question went unanswered, it wasn't because it had stopped mattering. The team would simply run out of time; they needed a way to answer questions while they were still live.

The Approach: Rapid Research to create a New Data Set Every Week 

Rather than a single research project or study, Hatch used Strella as a connected, near-continuous research layer across product development and launch. In about ten weeks, from mid-January to late March 2026, the team ran 11 studies and interviewed roughly 221 participants. The studies ranged from messaging testing, concept testing and general consumer discovery to usability of both product and companion app and feature prioritization.   

The pace was the point. Hatch ran those 11 studies in just over two months, often several in the same week. Two prototype A/B tests went live on the same day in February, and four studies launched in the 15 days between March 9 and 23. The conversational AI-moderated interviews happened whenever participants had a few free minutes, so a full study would field and return data in days rather than the weeks a traditional study required.

The rhythm mattered as much as the volume. "The fact that we were able to have a new data set every week to learn from...deepened our understanding and informed and inspired the messaging concepts we developed," Amyx said. Because AI-moderated interviews returned data quickly, she could put a single question in front of the right consumers and get back the actual language they used. "From a marketing perspective, it's so important that we get the real language consumers are using around these concepts," she said. "Having that conversational data back was so much more meaningful than a closed-ended survey."

The Result: Consumer Input Influencing Every Decision 

Hatch conducted research that had impacts across product and marketing, uncovering not just what customer sentiments were, but how real people would react to and use the product.
Marketing: Brand and Product Messaging

Here the work ran as a fast loop of learning and concepting. Early on, Strella answered the weekly discovery questions that gave the target consumer color and texture.

Once the target audience was clear, that same loop carried into message testing. One study put four distinct positioning territories in front of 40 wellness-minded U.S. adults and measured each on appeal, differentiation, believability, and interest. 

The real value was the reasoning captured underneath the ratings, gathered in people's own words rather than as multiple-choice tallies: which brands each message evoked, what felt genuinely different, and where the promise stopped being believable. In the past, a study like this would have been batched into a larger survey. Here it came back quickly enough to shape the copy.

Product: Usability & Concept Testing
Product research for Hatch with Strella was decision-driven. The Hatch team had multiple prototype variations and companion-app concepts. With Strella, they were able to quickly run A/B tests that provided directional feedback. This feedback aided the team in making the decision which direction to pursue.

The Impact: Rapid Research, Shared Across Teams  

"The type of data we get is natural, conversational language from consumers, exactly what they're saying, being able to get that at scale, and at such rapid speed, is really the value [Strella] brought to us."

Amanda Amyx

Real consumer language, at scale, fast enough to keep up with the launch.The speed to insights made the team sharper. Months of iterating on copy, messaging, and positioning, each round grounded in fresh consumer input, compounded. What changed wasn't only how fast answers came back, but the form they arrived in. Strella's automatic highlight reels meant a finding could travel as a two-minute themed video with a consumer's own words in it, dropped straight into a Slack thread, instead of waiting for a formal report. "People absorb and are inspired by information in different ways," Amyx said. "Video brings more humanity. It's really enabled that source of truth to be straight from the consumer, their voice."

Producing videos used to be too slow to justify on every question and every project. Now it was the default, and getting consumer voice in front of stakeholders that easily began to change what they expected of research.A question that once would have gone unanswered could now be turned around quickly, sometimes to their surprise. 

"Maybe they don't expect you to run research on it, but the fact that we could do it so quickly is almost a surprise," Amyx said. "Here's something to consider, with more texture."

Strella found a specific place in Hatch's toolkit: not a replacement for surveys or human-moderated work, but a supplement between them, delivering far more than a survey's tallies without the full cost and cycle time of traditional moderation. And it began to spread: some designers and PMs started to self-serve, designing and running their own studies with the research team's guidance. "It's crazy we're even at this point," Amyx said. "As this product launches, and whatever we develop next, I’ll definitely rely on [Strella]."

The Case Study in Numbers

The Hatch team continuously used Strella as questions came up. Here's how it breaks down by numbers:

• 11 studies fielded on Strella for the Hatch Sleep Clock and its companion app
• ~221 participant interviews run with existng customers and new target customers
• All Strella supported research on the Hatch Sleep Clock was completed over a 10 week period
• The highest volume of research was when 4 studies in a single 15-day stretch in March

Want to see how you can integrate AI-moderated research into your product development cycle? Book a demo with the Strella team below.