Kyle Norton, CRO at Owner.com, took win rates from 38% to 53% in a single quarter. On $100M in pipeline, that’s $15M in extra closed revenue without a single new lead.

He did it by ignoring a best practice most CROs swear by.

On the GTM Science Podcast, Kyle told us how he used AI call scoring to analyze over 150 of his team’s calls. They identified the 12 skills most correlated with winning deals, based on their own data from their own reps and buyers.

“We expected to hear that the thing most heavily correlated with win rates was discovery,” Kyle says. “Every good CRO is like, ‘Oh, it’s discovery. It’s all about discovery.’ And it was very much not discovery.”

10 of 12 critical skills were end-of-call and closing behaviors. How you present pricing. Whether you value stack. How you set up next steps. Whether you ask for the business.

In this newsletter, we’re breaking down the story; why this worked, what he did with the data, and what it means for you.

Listen to the full podcast episode on Spotify here or Apple podcasts here. In this episode, we also talked about his prioritization framework, his talent density strategy, and the early investment philosophy that supported Owner.com’s growth to $60M ARR.

Generic Best Practices Are Costing You Money

This is a key distinction I need to point out: it’s not that discovery doesn’t matter. It’s that discovery didn’t matter as much as everyone assumed for Owner.com’s specific sales motion.

Owner.com sells a transactional solution to restaurant owners. The product is compelling, the need is obvious, and they’re the dominant player in their category. In that context, the deal isn’t won or lost on how well you uncover pain. It’s won or lost on whether you can get the prospect over the line in the moment.

“When you’re selling a transactional solution, excitement is everything,” Kyle explains. “It’s a very emotion-driven purchase decision.”

If Kyle had just followed the industry playbook (more discovery training, better qualification frameworks) he would have been optimizing for the wrong thing. His team would’ve gotten better at a skill that had almost no impact while ignoring the skills that actually closed deals.

This is the trap. We read the research, adopt the frameworks, and implement the “best practices” without ever validating whether they apply to our business. And because we never isolate the variables, we never find out what we’re leaving on the table.

(This is why all of our GTM Ops Frameworks emphasize how to figure things out for your business.)

Another key distinction: Kyle didn’t find this insight because something was broken. His win rate was already a strong 38%. He found it because he went looking. (Honestly, if this is the only thing you take away from this newsletter, I’ll consider my job done!)

“On a monthly basis, we are deconstructing our entire funnel and segmenting and looking at every possible cut of data we can to figure out how we improve the business,” he says.

Most teams only dig into their data when something is obviously wrong. Kyle’s team digs into it as a discipline, even when things are going well. That’s how you find the $15M you didn’t know you were missing. What better validation for what we do at USC?

Acting on the Data Is Where Most Teams Fail

Getting the insight is step one. Step two is where it usually falls apart.

Data breakthroughs are fun! Getting people to change behavior is hard.

Kyle didn’t send a Slack message saying “focus more on end-of-call skills.” He didn’t do a one-hour training and move on. He built a complete rollout of three modules over ten weeks and made it the only thing his organization was working on.

“My philosophy on change management is to only change one thing at a time and do it with a lot of depth over breadth,” he says.

He and his enablement leader spent days building specific training frameworks.

The output was a complete closing playbook:

• Value stacking sequences
• Assumptive close scripts
• Closing discovery questions
• Structured next-step frameworks

All built around Owner.com’s specific buyers and pricing. Reps weren’t told to ‘close better.’ They were handed exactly how to do it, then practiced it until it stuck, eliminating any ambiguity about priorities.

“We were constantly talking about this thing. We were giving them their scores every day, and they really cared about it,” Kyle says. “It just had an organizational energy to it that kept it top of mind.”

He structured enablement around the forgetting curve: reinforcing the skill the same day, then the next day, then two days later, then a week later, with increasing intervals as competence improved.

“Eventually, you don’t need to do any repetition. It becomes an unconsciously competent skill,” he says.

Reps didn’t just read about the new frameworks. They built their own call plans using them. They practiced in small groups. They created tools they’d use on real calls. Kyle pulled this from Bloom’s Taxonomy: the principle that the most effective way to learn a skill is to create something with it, not just consume content about it.

Two years later, the scripting is nearly identical to what they built during that initial rollout.

“It’s just a part of the DNA of the company now and the way that we pitch,” Kyle says.

What This Means For Us

Kyle’s story isn’t about AI call scoring. And it’s not about change management. It’s about the gap between the playbook we’re running and the playbook our data says we should be running.

That gap exists in every revenue organization. The question is whether we have the infrastructure to find it, the honesty to acknowledge it, and the execution discipline to close it.

Most teams can get to the insight. The tools exist. The data is there. What’s rare is the ability to go from “the data says this” to “we changed how 100 reps operate and it stuck permanently.” That requires building the process, creating total organizational focus, maintaining coaching cadence, and holding that discipline for months (all without hurting your numbers in the short term).

That execution gap is where we spend most of our time at USC. If your team has the insight but needs operational help turning it into revenue, let’s start the conversation.

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