Conversation
Highlights

Building a Data Fabric Category: How Promethium’s Educational Approach Drives 8x Growth

Martha Stewart might seem like an unlikely inspiration for a data infrastructure company, but for Promethium CEO Kaycee Lai, her story perfectly illustrates the power of authentic category creation. In a recent Category Visionaries episode, Kaycee shared how Stewart’s approach to building her empire mirrors successful category creation in enterprise tech.

“Martha Stewart actually started out as an investment bank[er], as a very successful Wall Street executive, and she saw an opportunity,” Kaycee explains. “She became that Persona that she was marketing and selling to…her customers see themselves in her.”

This insight shapes Promethium’s approach to establishing the data fabric category. Rather than following the traditional enterprise software playbook of feature comparisons and technical specifications, they’ve embraced education as their primary go-to-market strategy.

“Rather than just marketing making claims, we take an educational approach in terms of, hey, let’s teach you guys things that are not necessarily about Promethium, but related to analytics, related to data engineering, related to data analytics,” Kaycee shares.

This educational focus serves a dual purpose: it helps potential customers understand the emerging category while establishing Promethium’s expertise. The strategy has driven remarkable results, with the company “on track this year to do about eight x over what we did last year.”

The Evolution of Data Infrastructure

Kaycee points to a fundamental shift in how companies approach data infrastructure. The traditional “modern data stack” involved piecing together best-of-breed solutions for each component: “You might have a best of breed data catalog, a best of breed data integration tool to do the ETL, do the pipeline, some sort of data prep and data transformation tool.”

But this approach has significant drawbacks: “You could easily buy four products for, say, a million dollars and spend seven to 10 million on integration fees, which is kind of silly, right, if you think about it. But that is the reality of the modern data stack.”

This pain point created the opening for data fabric platforms. As Kaycee explains: “The data fabric is going to be a standalone category, I believe, very shortly, because it is different enough and that you can’t simply take an existing product, slap lipstick and marketing jargon on it, and turn into a data fabric.”

Transparency as a Competitive Advantage

In an industry known for carefully orchestrated demos and marketing claims, Promethium takes a radically different approach. “There’s a lot of products that they look great in a demo, they look great in a video, they look great in an ad, but the product actually doesn’t look like that,” Kaycee notes. “We really shine is were actually very genuine, very transparent about like, what you see is what you get.”

This transparency extends to their go-to-market strategy. Instead of making grand promises, they focus on demonstrating immediate value: “When people figure out how the data fabric can actually directly impact their business, it’s very easy to kind of really increase your adoption from there.”

The Future of Data Analytics

Looking ahead, Kaycee sees generative AI as a transformative force in enterprise data analytics: “Gen AI is changing a lot of industries, a lot of how we do things, but I think it still hasn’t really made its way into data analytics and the enterprise successfully yet.”

This presents both an opportunity and a challenge for category creators. The key, according to Kaycee, is maintaining focus while building for the future: “It’s actually focus in picking a specific problem for a specific Persona that you want to focus on, because that will give you enough, it’s wide enough of what you need to build, but then it’s relevant enough for you to have something that you can start generating revenue early on from.”

For founders creating new categories, Kaycee’s journey with Promethium offers valuable lessons: focus on education over marketing claims, demonstrate immediate value through transparency, and maintain a clear vision while staying flexible enough to embrace emerging technologies. As he puts it, success comes from “being just maniacal about getting as much feedback and data points and be open and honest with yourself.”