Challenge

Running enterprise ABM at scale with a two-person marketing team and zero room for bottlenecks

Kevin Jong joined Genesis as Principal AI GTM Operator after helping build the ABM playbook at Snowflake — a company widely regarded as having written the book on account-based marketing. At Snowflake, Kevin had seen what a world-class ABM program looked like at scale: clean data pipelines, dedicated marketing ops teams, analytics engineers building dashboards, and a full supporting cast to turn intent signals into personalized campaigns.

Genesis was a different story. The company — founded by two former Snowflake leaders — was building an ambitious enterprise data acceleration platform and growing strategically into large accounts. Kevin and Esther Katz, Head of Marketing, were the entire marketing team. Their charter for the first six months was to create a closed-loop GTM system. What it didn't have was a scaled marketing department.

The ambition was enterprise-grade ABM. The reality was two people against every bottleneck that makes ABM impossible to scale.

1. A two-person team without design, dev, or ops to lean on.

Historically, building a personalized landing page meant submitting a design request, filing a dev ticket, and running QA, a relay across three or four teams. Genesis didn't have those teams. There was no design queue to submit to, no dev team to build pages, no marketing ops to wire up integrations. If Kevin couldn't build it himself, it didn't get built. And doing it manually took more than a week per page.

"If it's just me trying to do this myself from end to end, back in the day, pre-AI, I would say it's more than a week for sure."

2. Speed was the differentiator they couldn't afford to lose.

In sales-led enterprise deals, timing and momentum determine whether a deal advances or stalls. When a salesperson texted Kevin saying they'd just had a great dinner with a prospect and needed something to send immediately, there was no time to submit a design ticket. The old workflow meant the moment would pass before the asset was ready. The ability to deliver the right asset at the right moment was the only way to cut through.

3. Generic outreach couldn't earn trust with enterprise data leaders.

Kevin understood from years of enterprise marketing that technical buyers don't respond to generic brand messaging. The industry benchmark for cold meeting bookings hovered below 3%. With a lean team and a small target list, every touchpoint had to feel intentional, researched, and unmistakably human.

4. Sales needed a way to nurture prospects through complex enterprise buying cycles.

Once the initial discovery was booked, the team needed personalized follow-up materials (meeting recaps, case study roundups, business cases) that could circulate through an entire buying committee. Sending a Word doc or a bulleted email to a room of stakeholders wasn't going to carry the message. And with no dedicated content team, there was no one else to pick up the slack.

Solution

Kevin built the ABM system he'd seen at Snowflake, except he built it alone and agentic from the grounds up.

Kevin's insight wasn't just about choosing the right tool. It was about designing a system. He architected a closed-loop GTM engine where every piece of data (CRM fields, call transcripts, intent signals, campaign performance) fed back into the system and could be turned into action. Mutiny became the asset creation layer of that system: the place where all of Kevin's context, strategy, and research turned into polished, on-brand deliverables in minutes instead of weeks.

His approach was methodical. He fed Mutiny the context it needed (campaign briefs, call transcripts, CRM data, research) and prompted Mutiny to do the heavy lifting. He built a template library so that future assets started from proven frameworks rather than blank pages. The result was a system where Kevin could respond to any sales request, any campaign need, or any event in near real-time.

Using his closed-loop GTM system with Mutiny as the execution layer, Kevin deployed personalized assets across the full buyer journey:

1. Design a direct mail campaign that outperformed the industry by 3x.

Kevin orchestrated a creative direct mail campaign to kick off the new year: custom F1 RC cars with personalized F1 ID cards featuring each prospect's name, Genesis's mission statement, and a direct contact. He targeted 2-3 decision makers across a list of 20 target accounts. Feeding Mutiny a campaign brief, AI research for each account, and layering in product-specific information Kevin built personalized landing pages that spoke each prospects language.

The result: 20 1:1 landing pages created in a single day. Each link was sent to the assigned salesperson to include in their follow-up after the packages arrived.

2. Turn sales call transcripts into deal-advancing assets before the next meeting.

After a first meeting went well, Kevin pulled the transcript from Salesforce and fed it directly into Mutiny with context about the prospect's needs. Within minutes, he had a personalized recaps with relevant use cases and next steps, ready for the salesperson to share immediately. More than a follow-up asset, these pages became nurture tools that prospects could forward to other departments, building internal momentum for Genesis across the buying committee.

3. Arm sales with on-demand case study roundups based on specific use cases.

When a salesperson needed use cases for a specific industry mid-conversation, Kevin pulled relevant data from Salesforce and context from Genesis's own AI product, then fed that into Mutiny to build an interactive case study roundup page. The personalized case studies were in the hands of the prospects before the end of the day.

What made Kevin's system work wasn't any single tool. It was the way he connected everything: CRM data flowing into campaign briefs, call transcripts feeding personalized follow-ups, intent signals triggering new plays. Mutiny gave him the speed to execute against his own strategy without waiting on anyone else. Every asset matched Genesis's brand identity (fonts, colors, logos, visual style) so Kevin never had to choose between speed and quality.

"I'm able to spin up personalized assets and get it out the door in a few minutes. I can do stuff like this on the fly without a design team.” — Kevin Jong, Principal AI GTM Operator at Genesis

Outcome

Enterprise-grade ABM execution from a two-person team — with results that outperform the benchmarks

The direct mail campaign told the story in numbers. 10% of the cold accounts that received Kevin's direct mail ABM campaign converted into a meeting. Compare that against an industry benchmark of less than 3–5% for1st touch cold direct mail ABM campaigns.

But the campaign velocity is what made the results possible. Kevin is able to create 20+ personalized landing pages in a single day, each tailored to a specific account with relevant messaging, value propositions, and calls to action. Before Mutiny, building a single personalized page end-to-end would have taken more than a week with design dependencies, device testing, and QA. Now, campaigns are created, personalized, and distributed to sales in a day.

Beyond the direct mail campaign, Mutiny became the execution layer for Genesis's entire ABM motion. Post-meeting follow-up pages were live before the prospect's next internal meeting. Every asset that would have previously been skipped due to bottlenecks or dependencies now existed and helps differentiate Genesis in an enterprise sales motion.

Kevin built the kind of ABM program he'd seen at Snowflake, where a team of specialists turned intent signals into personalized campaigns at scale. The difference is that Kevin did it with a team of two and a set of AI tools that let him move at the speed of his own ideas.

Recommendation for Others

Kevin's advice to marketers building ABM programs is to start with first principles.

"Go back to the basics," he said. "Marketing as a practice doesn't change. The thing that changes is the way we execute." He recommends mapping out your buyer journey channel by channel, identifying the core bottlenecks, and then asking where AI can force-multiply your output rather than simply automate a process that doesn't work yet.

For teams evaluating personalization tools, Kevin emphasized the importance of human-centered design. In an era where inboxes are flooded with AI-generated spam, the ability to create assets that look and feel authentic to your company is what earns trust with enterprise buyers.

"You can have a closed-loop system that's running in circles and going nowhere. Or you can have something that's basically feeding the belly of the beast, force-multiplying the output of meaningful work." — Kevin Jong, Principal AI GTM Operator at Genesis