When Gage Sonntag was first hired at Super.com, the company was in the middle of scaling. And as he began learning about the pricing model, he felt there was a larger opportunity to lean into. They could think about monetizing differently with more advanced analytics and more complex ways to drive much stronger top-line results. With small changes and optimizations, he saw meaningful impacts on the business.
Finding the pockets of opportunity where the data team was best suited to play was the key to driving results.
So, what is the sweet spot? Where and how are data teams best positioned inside an organization? Gage sits down with Francois Ajenstat on this week’s episode of the Next Gen Builders podcast to discuss the answers to those questions and building and running a data-driven organization.
Listen to the episode and subscribe on Apple Podcasts, Spotify, and YouTube.
Structuring the data team for a data-driven culture
At Super.com, Gage’s leadership is all about empowering his team to make an impact through data. His approach centers on "mission-aligned teams" (MATs), where data analysts work directly within various business functions. This setup allows them to collaborate closely with product managers, growth managers, and engineers, ensuring that data insights are woven into the decision-making process.
By embedding analytics into specific teams, Gage achieves a balance between centralization and decentralization. This structure lets data analysts develop a deep understanding of the specific challenges and opportunities in their areas while still benefiting from a level of centralized oversight. “We’re trying to get the best of both worlds,” Gage explains, emphasizing the need for flexibility alongside strong data practices.
Interestingly, he learned this balanced approach during his time in craft brewing, where success required a mix of following systematic processes and allowing room for experimentation. He’s brought these principles to his current position, where he encourages his team to explore new ideas and take calculated risks.
Implementing a self-service, data-democratized model
Gage has seen companies where an idea gets passed to a data person who does the analysis, and sends it back—and that model works for some. But at Super.com, Gage wants to remove the number of people it takes to convert insights into actions.
“Providing people the data to do the analysis themselves and come to their own conclusions and then action those conclusions has been tremendously powerful for us.”
To do that, he’s democratizing access to the data and tooling and providing skills and knowledge to help people fish for themselves. With fewer handoffs, the teams can move faster.
“We really just coach our team on asking for help and making the ecosystem as frictionless as possible,” he says. “We’re there as a ‘phone a friend’ when you need it… but otherwise, an empowered end user works the best for our scale and size.”
How data teams can empower a culture of experimentation and learning
So what does this model mean for experimentation? Gage and his team put together experimentation best practices but for the most part: “What we really didn’t want to do was be part of every single experiment you run,” Gage says. The data team’s role is about making it easy for anyone to take an idea from inception to push it live.
“Being hard to run an experiment is not an acceptable barrier to trying, testing something, and seeing whether it works,” he says.
Gage knows that leading a data-driven organization comes with its challenges, especially when things don’t go as planned. He recalls a project at Super.com where an experiment led to unexpected financial outcomes. Instead of seeing this as a failure, Gage viewed it as a valuable opportunity to learn. “Failures aren’t just setbacks; they’re learning moments,” he says. This mindset is a key part of Gage’s leadership approach—focusing on resilience and the ability to adapt quickly.
“Failures aren’t setbacks; they’re learning moments.”
At Super.com, this approach is central to the company’s culture. Gage emphasizes the importance of having the right safeguards in place so that when things don’t go as expected, the team can quickly recover, understand what happened, and apply those insights to future efforts. “The key is to have the right guardrails in place so that when things don’t go as planned, you can recover quickly and learn from the experience,” he notes.
Experimentation needs guardrails for controlling problems that arise in response to three areas: people, processes, and technology. For instance, a guardrail for people problems is investing in training and best practice development, or for processes, it’s implementing peer reviews and documentation.
This commitment to continuous learning is more than just a strategy—it’s a core value at Super.com. One way Gage fosters this culture is through a gamified sportsbook, where team members can bet on the outcomes of experiments. This approach makes the experimentation process more engaging and encourages the team to view each project as a chance to learn something new.
The result is a work environment where learning is just as important as success. This not only boosts morale but also promotes a culture of ongoing improvement.
Gage says it helps to remember that in terms of experimentation, even at leading companies like Microsoft and Airbnb, “Most shots at bat aren’t going to work. " He summarizes industry estimates that 10% of experiments ship with bugs, and 80% of experiments fail. You have to have a reasonable tolerance for risk when you’re trying to move fast, he acknowledges.
“A good mentor of mine frames success as a ratio of learning divided by effort,” Gage says. In other words, the lack of learning is how Gage frames failure.
Resilience in leadership
Gage believes that growth comes from being open to learning, even when the path isn’t clear. As he puts it, “You can’t always predict the path your career will take, but being open to learning is what drives growth.”
Gage applies these lessons through a leadership style focused on empowering his teams and fostering a culture of continuous improvement. He recognizes that success isn’t just about technical expertise—it’s also about creating an environment where people feel supported and encouraged to innovate. By giving his teams the autonomy to explore new ideas and the resources they need to succeed, Gage helps them thrive and make a meaningful impact.
This approach ensures that resilience is built into the team’s everyday work. Gage’s focus on both the human and technical aspects of leadership means his teams are not only equipped to handle current challenges but are also prepared to adapt and grow in the face of future ones. His leadership isn’t just about achieving short-term goals; it’s about building a strong foundation for ongoing success.
Tune in to Gage’s story
Listen to the latest episode of the Next Gen Builders podcast to dive deeper into Gage’s approach to building a data-driven culture at Super.com, and the valuable lessons he’s learned along the way.
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