Zenlytic’s Mid-Market Focus: Why They’re Avoiding the Enterprise AI Gold Rush

While many AI startups chase large enterprise deals, some companies are finding greater success by swimming against the current. In a recent episode of Category Visionaries, Zenlytic founder Ryan Janssen revealed why they’re deliberately targeting mid-market companies instead of pursuing enterprise customers.

Understanding the Market Opportunity

Through their early consulting work, Zenlytic gained unique insights into how companies of different sizes use data. “We were actually working with dozens of companies from startups to Fortune 500s basically. And we had a front row seat to how they used or failed to use their data,” Ryan explains.

This experience revealed a crucial insight: mid-market companies often have sophisticated data needs but lack the resources of larger enterprises to build internal solutions.

The Mid-Market Sweet Spot

Zenlytic identified a specific revenue range where their solution provides the most value. “We like the mid market sales cycles versus long enterprise sales cycles… the sweet spot for us is something like our customers mostly have revenues between sort of 15 and $500 million a year,” Ryan shares.

The Data Team Challenge

Their focus on mid-market companies is particularly relevant given how data teams typically operate. As Ryan explains, “If you’re a data person at a mid sized organization, you kind of have three jobs, right? So your first job is, like, building and maintaining the tools… The second is helping with these sorts of questions, and the third is sort of deeper analytics.”

The problem? “They obviously love to do number three. They actually love to do number one as well… The only thing they really hate is the second one, which is sort of like answering those data questions for the team or building the data tickets.”

Avoiding the Enterprise Trap

While many AI startups are drawn to enterprise deals for their large contract values, Zenlytic recognized the hidden costs of this approach. Long sales cycles can drain resources and slow growth, particularly for early-stage companies.

Instead, they focused on building a product that could be quickly demonstrated and adopted. “Our objective is really to get to a demo in pretty much sort of every sales call,” Ryan notes, highlighting their emphasis on rapid validation and deployment.

Growth Through Focus

This strategic focus on mid-market companies has driven significant growth. “We’re about six x on the year so far in terms of Arr,” Ryan shares. This growth comes not from landing a few large enterprise deals, but from successfully serving a broader base of mid-market customers.

The Evolution of Their Market Approach

Initially, Zenlytic focused exclusively on ecommerce companies, allowing them to develop deep domain expertise. As Ryan explains, “We actually turned off everything else. We said no, only commerce businesses was because we wanted to get close to the problems of a commerce business and understand their day to day.”

This focused approach helped them build credibility and understanding before expanding to other verticals. “Commerce will always be a big part of the companies we work with… we’ve seen a lot of interest from other verticals as well. So lots from consumer tech, increasing amounts from SaaS businesses now.”

Lessons for AI Founders

Zenlytic’s experience offers valuable insights for founders considering their market strategy:

1. Choose market segments where you can move quickly and show value
2. Focus on sectors where you can build deep domain expertise
3. Consider the hidden costs of enterprise sales cycles
4. Build for rapid demonstration and adoption
5. Expand strategically from areas of strength

The key lesson is that bigger isn’t always better when it comes to customer size. Success in the AI space might come not from landing the largest possible deals, but from finding the right-sized customers where you can deliver consistent value and drive sustainable growth.