#StartupsEverywhere: Kene Anoliefo, Co-Founder, HEARD
This profile is part of #StartupsEverywhere, an ongoing series highlighting startup leaders in ecosystems across the country. This interview has been edited for length, content, and clarity.
Enhancing customer research with AI
With a background in product marketing and research, Kene Anoliefo knew the struggles of increasing research insights to match the fast-paced development of products. We sat down with the HEARD co-founder to discuss her company, the role of AI in the startup ecosystem, and more.
Tell us about your background. What led you to HEARD?
The company is inspired by a lot of the problems that I faced in my prior career as a product leader for over a decade. I led product teams at big companies and early-stage startups.
I've been able to cut my teeth building products in lots of different places. One issue that I kept running into was friction where I needed insights to make the best decisions fast. It didn't matter where I was, even working with the best research teams in the world, there was always some tension as the pace of building kept getting faster and faster. We were expected to make high-stakes decisions and deliver value fast but were waiting up to six weeks to get some feedback.
From there, the idea for my current company was born. We were able to confront the problem facing a lot of customer-facing teams at a really exciting time in technological development. Now, we can train AI to have an open-ended conversational dialogue with customers but directed towards specific goals that researchers want to learn.
What is the work you all are doing at HEARD?
HEARD helps product research and marketing teams learn about their customers fast by using AI to conduct user research. When working on a product or marketing team, gathering customer feedback is essential. However, scheduling, moderating, and analyzing user interviews can take anywhere from four to six weeks. We speed up the time that it takes to run those studies to 48 hours or less, saving teams over 30 hours per research study.
We also help companies analyze all the data from customer conversations, turning it into insights the team can view in real time without any manual coding or tagging. Using this tool, teams can decide next steps based on user feedback quickly.
What size companies do you work with and why is user feedback so important to innovation?
We work with companies across all stages and life cycles. Some of our customers are early-stage startups who don't have a research team and using our product is the first time they're able to bring a reliable research capacity onto their team. We also work with large public companies who do have existing research teams, but there's way more demand than their teams can fulfill. Our product helps them to expand the capacity of research that they can do, by allowing a single-user researcher to do more and empowering non-research experts.
Every company needs to be in contact with their customer to understand and get feedback on things, especially because companies are constantly innovating and trying to figure out what's going to be their next bet. Whether it's an early-stage startup trying to build research capacity from scratch, or a larger public company wanting to do research more efficiently, we're able to come in and sort of offer that solution in both cases.
Tell us more about how your AI is built, and what role it plays in enhancing the research process?
We train multiple different AI models on how to complete different tasks within customer reach, from designing a study and writing a discussion guide to moderating the interview with your customers. Instead of needing a person to sit in a room talking with senior executive customers, AI fills that role and is trained on how to moderate a good, open-ended qualitative user interview for research.
In this space, you have to try anything and everything. The answer is usually a combination of multiple methods. So for some things, we will go build synthetic data sets. For others, we will work with trained user researchers and build specific data sets that we can use in training our models. The right approach depends on several factors, the specific task, how the data needs to be structured, and how effectively the AI can train using different data sources.
What has been your journey accessing capital? What do you want policymakers to know about capital access and its impact on startups and innovation?
I think our fundraising journey probably follows one similar to other venture-backed companies. We raised an initial seed round, with venture investors as well as angel investors. Both my co-founder and I are fortunate to have previously worked in the startup ecosystem and made connections. Though it’s always challenging even if you do have experience fundraising in the past or have worked in the industry.
I think access to capital is the fuel that makes the engine run in the early days of a company. I was privileged to have already been a part of these spaces and knew how to use them to my advantage. If I didn’t have that access before starting my company, it would have been really hard for me to break through.
There have been varying approaches to democratizing and giving more people access to capital. Ultimately, I think the more we can diversify the people who give money, the more it'll create opportunities for more people to participate and build businesses in different ways that might not fit the existing kind of venture-backed framework.
What are your goals for HEARD moving forward?
We believe we're the tool that is going to help people take ideas, get feedback from real people, and then put the feedback back into the system. The future that I see is one where a single person doesn't necessarily need to have spent decades with deep expertise in research, design or engineering to be able to make their ideas happen quickly and create products that have an impact.
My hope for the company is that we play an incredibly important part in that space. We are becoming an engine helping make sure that the ideas and things companies are creating are aligned with the needs of the people they are serving. I am excited to be a part of this space and ecosystem enabling a new type of creativity and innovation.
All of the information in this profile was accurate at the date and time of publication.
Engine works to ensure that policymakers look for insight from the startup ecosystem when they are considering programs and legislation that affect entrepreneurs. Together, our voice is louder and more effective. Many of our lawmakers do not have first-hand experience with the country's thriving startup ecosystem, so it’s our job to amplify that perspective. To nominate a person, company, or organization to be featured in our #StartupsEverywhere series, email advocacy@engine.is.
