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If your SMB segment is getting harder to retain and your inbound is softening, you’re probably already thinking about going upmarket. The question nobody’s answering for you is: what actually has to change in your go-to-market to make that work?

ZoomInfo was in that exact position. 

“We knew we had great enterprise clients,” James Roth, CRO of ZoomInfo, told us on the GTM Science podcast. “And we also knew that they were completely under-penetrated in terms of what they should be using us for. We had this great enterprise footprint that, frankly, the go-to-market machine was not optimized for.”

On top of that, retention and LTV:CAC for enterprise were both, in James’s words, “unequivocally better.”

With startups churning at a higher rate and LLM search eating into inbound SEO traffic, going upmarket went from an opportunity to a necessity.

But deciding to go upmarket is the easy part. The hard part is rebuilding the machine to support it.

In this newsletter, we’re breaking down the operational changes ZoomInfo made and the results they saw going from 50/50 SMB/upmarket to a roughly 70/30 upmarket shift.

Listen to the full podcast episode on Spotify here or Apple podcasts here. In this episode, we also talked about inbound capacity planning, territory design, the MQL debate, and the reporting framework James uses to diagnose pipeline problems.

What They Changed

ZoomInfo’s enterprise GTM motion had problems at every layer. Account loads were wrong, comp was pointed at the wrong behaviors, outbound infrastructure was making reps’ jobs harder, and even the best people were spending more time preparing to sell than actually selling.

Here’s what they focused on to overhaul enterprise GTM:

• Account loads and capacity
• Compensation and pipeline composition
• Talent restructuring
• Budget re-allocation with ICP discipline
• Rebuilding outbound

Let’s break these down.

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Account Loads and Capacity Planning

Enterprise account managers had 30 accounts in strategic enterprise. That’s way too many for the kind of deep, multi-stakeholder selling that enterprise deals require. The original goal was to get loads down to 1-2 per rep.

But the answer ended up being more nuanced. James and his team audited how their top performers actually spent their time. In a given month, a top AM might log 45 hours on customer calls, 80 hours building decks, and 40 hours on other prep. Even the best people were spending more time on non-selling work than on actual selling.

“We set out on a mission to say, here are the top account managers, here are the top AEs, this is how they spend their time,” James says. “We want to see hours in meetings go up.”

Instead of just cutting account loads, they focused on compressing all that non-selling time through AI and automation. The research, the deck-building, the prep. By shrinking that, reps could handle more accounts than the original 1-2 target without sacrificing quality. The capacity math changed because the system was doing the heavy lifting around them.

Compensation and Pipeline Composition

Before the shift, enterprise pipeline was primarily made up of small, incremental seat additions; A BDR manager at a Fortune 500 needs three more ZoomInfo licenses. An enterprise rep closes that and moves on. Transactional upselling doesn’t cut it for going upmarket.

James called out compensation as one of the things driving that behavior, pointing reps toward those quick, small wins instead of doing the deep discovery that real enterprise selling requires.

The whole composition of what was in the pipeline had to change. Enterprise reps were incentivized to do what enterprise reps should do: understand business challenges and build toward larger, strategic deals.

Talent Restructuring

They brought in people better suited for the enterprise motion, both internally and externally. Internally, that meant re-deploying and promoting people who had the right skills. Externally, it meant hiring specifically for the kind of selling enterprise requires: deep discovery, multi-stakeholder engagement, longer deal cycles.

James noted that during the high-growth period of 2021-2022, they had account managers running Fortune 500 companies who had been SDRs three years earlier. That can work when everything is going well. It doesn’t work when you need true enterprise selling capability.

Budget Re-Allocation with ICP Discipline

This one is worth pausing on. A lot of companies assume going upmarket means getting a bigger budget. ZoomInfo didn’t. They pulled resources out of the parts of SMB that weren’t driving revenue and moved them into enterprise.

James was careful about which SMB they moved away from. An SMB with 25-100 employees is a real business with staying power. It was the micro-SMB (0-10 employees) that was a problem.

“We essentially wanted to get off a little bit of the drug that was that micro-SMB,” James says. Those customers came in fast when money was free but often didn’t have a business a year later.

That’s what we call ICP discipline. Saying ‘no’ to easy, fast-closing deals to invest in longer, harder ones where the payoff is better but further out. If we’re a recurring revenue business, “ideal” customers mean recurring customers.

(This is one of those decisions that sounds obvious when someone else describes it, but is genuinely hard to execute when the quarterly number is staring you in the face.)

Rebuilding Outbound From the Ground Up

This was the biggest operational lift, and the one with the most measurable results. ZoomInfo called the project GTMO (Go-To-Market Orchestration), and it was designed to eliminate three questions from an SDR’s day:

• Who do I call?
• Why am I calling them?
• What do I say?

Before GTMO, SDRs were spending about five minutes of prep before every call just trying to figure out the basics. Is this already a customer? Is this an ultimate parent or a subsidiary? Is another AM going to get mad at me for calling into their account? They’d cross-reference CRM data, check Snowflake, hunt through tabs. Compare that to a well-tuned machine like Salesforce, where reps had 20 seconds between calls because everything was served up.

Signal validation came first. They went back forensically through every opportunity they’d generated and mapped what signals were actually present when those deals opened. Funding rounds, C-suite changes, earnings call mentions, companies going private. They wanted to know which signals correlated with real pipeline based on their own data, not which ones the team assumed mattered.

“Maybe the loudest sales guy in the room says new C-suite is the most important thing out there,” James says. “But then the data shows you that, frankly, new C-suite starts, they don’t open.”

How many of us are prioritizing outbound based on signals we’ve never validated against our own data? (This is something we push our clients to do constantly at USC.)

From that analysis, they built prioritized lists. Not 5,000 accounts to sort through. The top 25, ranked by signal strength, with a clear reason attached to each one.

Then they layered in AI-generated talk tracks. Not one-size-fits-all scripts. These are customized by vertical, sub-vertical, segment, and the specific signal that triggered the prioritization. They’re also built on data from the last ten closed deals, so the messaging reflects what actually worked in real conversations.

An SDR clicks into an account and sees: here are the 3 to 5 people in the buying committee. Here’s a cultivated script for each of them. Here’s the signal that tells you why now.

“At no point should an SDR ever walk into a day and say, what should I do?” James says. “They should have a cultivated list. It has to be prioritized. There has to be a point of view on each of those as to why this is prioritized at a higher level.”

Because the system did the thinking, they also changed who they needed to hire for SDR roles. They didn’t need experienced enterprise SDRs who’d already built the instincts to navigate complex accounts on their own. They could bring in higher-potential, entry-level talent and feed years of institutional knowledge into the system itself.

The Results

Here’s James on what happened after they rolled out the AI talk tracks and signal-based prioritization:

“We piloted a specific SDR group and we said, all right, we’re going to try these AI talk tracks, see how they work. 15% increase in conversion with everything else kept the same. So we’re like, okay, we’re on to something here. How do we continue to refine this?”

“And then we started going with the prioritization of the higher signal density accounts,” Jason continues. “Conversion rate went up another ten points.”

What This Means For Us

James’s story is about a problem a lot of B2B SaaS companies are facing right now: GTM  that worked in 2021 doesn’t work anymore, and shifting upmarket isn’t just a sales strategy decision. It’s an operational rebuild.

You can’t just tell enterprise reps to go sell bigger deals.

• You have to lower their account loads so they can do deep work
• You have to re-align comp so it points toward the right behaviors
• You have to build the outbound infrastructure that arms reps with the right accounts, the right signals, and the right messaging instead of expecting them to figure it all out on their own
• And you probably have to do all of this without a bigger budget.

The conversion rate lift is impressive. But it only happened because ZoomInfo did the operational work underneath it first. The signal validation, the capacity planning, the pipeline re-composition, the outbound buildout. Without that foundation, the AI talk tracks and signal scoring wouldn’t have had anything to sit on.

That operational buildout is where we spend most of our time at USC. If you’re thinking about shifting upmarket, or you’ve already started and the machine isn’t keeping up, let’s figure it out together.

GTM projects stalled out?
Not after 1 hour with us.

Book a free GTM Ops Execution Workshop.

Bring your top priority and walk away with a validated approach, a phase-by-phase roadmap, and an execution timeline. All internally actionable.

Learn More