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The Background
When a network goes down, the people who feel it first are rarely the ones who can fix it. It is the customer service rep whose calls keep dropping. The remote worker whose video freezes mid-presentation. The IT manager fielding complaints without clear answers about where the problem actually lives.
Since 1998, Pingman Tools has built tools to close that gap. Based in Boise, Idaho, the company is the creator of PingPlotter, a network monitoring and troubleshooting platform that helps IT teams, system administrators, and network engineers pinpoint latency, packet loss, and connectivity issues in real time. The software does not just show that something is wrong. It shows exactly where the problem sits, so teams can move from guesswork to resolution and keep their users connected.
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From Side Project to Industry Standard
What started as a one-person side project in the early days of high-speed internet has evolved into a trusted diagnostic tool used by organizations ranging from NASA and ESPN to small IT departments and home users. PingPlotter Cloud, launched in 2020, extended the product's reach to remote workforces, letting teams monitor distributed connections from a centralized dashboard. It is the kind of company that has always punched above its weight, with a tight team and a loyal user base built over more than two decades.
But Pingman Tools growth ambitions were outpacing the sales processes that supported them.
The Challenge
The IT Teams That Never Heard Back
Every day, network engineers and IT professionals started Pingman Tools trials because they had a problem they needed to solve. Maybe their contact center was plagued by intermittent call drops. Maybe a distributed team was losing hours to unexplained connectivity failures. They signed up because they needed answers, and PingPlotter had them.
But too often, those trial users never heard from anyone at Pingman Tools. They explored the product alone, hit a question they could not answer, and quietly moved on.
A Pipeline That Could Not Keep Up
Steven Vugrin, Director of Sales at Pingman Tools, knew trial users represented a meaningful opportunity. The challenge was math. Trial leads were high in volume but typically lower in deal value compared to enterprise accounts. With a lean sales team, Steven could not justify pulling reps away from larger deals to manually follow up on every trial signup.
"We averaged about seven opportunities a quarter from trials," Steven explains. "Trials are great, but the deal sizes are typically smaller. Having a sales rep work them one by one just didn't pencil out."
The outreach that did happen was inconsistent. Reps used the same sequences regardless of who was coming in, and some emails still required manual editing to feel even remotely personalized. Messaging varied from rep to rep. Timing was often off. And when a trial user canceled, there was no structured process to re-engage them.
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What Was Really at Stake
The cost was not just lost deals. It lost relationships with people who had actively raised their hand for help. Every IT professional who tried Pingman Tools and did not receive relevant, timely communication was someone whose network problems went unsolved longer than they needed to. The gap between Pingman Tool's product and the people who needed it was not a product gap. It was a connection gap.
Steven had started experimenting with AI outside of HubSpot, using ChatGPT to draft follow-up emails from call transcripts. The results hinted at what was possible: more consistent messaging, faster turnaround, better quality. But the workflow was fragmented. Data had to be pulled out of the CRM, run through an external tool, and manually pushed back. It worked, but it could not scale.
"We were taking transcripts, dropping them in, writing emails," Steven recalls. "But getting the data into ChatGPT and back, there were some things that just didn't connect."
The Solution
Meeting Users Where the Problem Is
The IT teams signing up for Pingman's trials were not browsing casually. They were in the middle of something urgent: a network outage affecting their users, a performance issue they could not explain to their boss, or a pattern of packet loss threatening their service quality. These were people who needed a fast, informed response that acknowledged their specific situation.
Steven saw HubSpot's Breeze Prospecting Agent as the tool that could deliver exactly that, pulling from the CRM data Pingman Tools was already collecting and turning it into outreach that actually matched what each trial user was experiencing.
Building the Agent, Earning the Trust
Steven began working with Prospecting Agent in November, starting with what he describes as a deliberate, layered approach. He built a series of agents, each designed around a specific use case, so trial users were funneled into outreach that matched their situation and product interest. The system pulled signals directly from the CRM: when someone started a trial, when they completed certain setup steps, and critically, when they canceled.
"Being able to funnel them into a specific use case agent that's going to speak to their language and pull data from the CRM was really valuable," Steven says. "It could know that you canceled and ask if there was a problem with setup."
Initially, Steven kept the human review process active, reading every email the agent generated before it went out. He wanted to understand how the tool thought, how it structured its messaging, and whether it could match the tone his team would actually use.
The Moment He Turned Off the Review
As Steven read through the outreach, something shifted. The emails were not just passable. They were contextual, timely, and consistent in a way that manual efforts had never been. The language reflected Pingman Tool's values. The timing matched where each prospect was in their trial journey.
"I've completely turned off the human review," Steven says of the trial outreach. "And that's the one where we're getting a 52% engagement rate. It's doing its thing."
That decision, turning off human review on the trial motion, was not about blind trust in AI. It was earned through weeks of reading, refining, and recognizing that the tool was performing at a level his team could not replicate at scale.
Breathing Life into Lost Leads
One of the most surprising outcomes was what happened with canceled trials. Previously, when a user ended their PingPlotter trial, that was the end of the conversation. No follow-up, no re-engagement, no second chance.
Prospecting Agent changed that. By detecting cancellation signals in the CRM and triggering personalized outreach, it opened doors that had been closed. Trial users who had walked away began responding, saying they were ready to talk after all.
"People that have canceled their trial are actually coming back and saying, yeah, I do want to chat with you about that," Steven says.
The Transformation
IT Teams Getting the Help They Need
The transformation that matters most is not what changed inside Pingman's sales org. It is what changed for the network engineers, sysadmins, and IT professionals on the other end of that outreach. Trial users who previously explored PingPlotter alone now received communication that spoke directly to their situation. Someone struggling with setup got proactive guidance. Someone who canceled got a thoughtful check-in, not a generic win-back email. The distance between having a network problem and finding the tool to solve it got shorter.
From Ignored Segment to Revenue Engine
The numbers tell a sharp story. Before Prospecting Agent, Pingman's trial leads produced roughly seven opportunities per quarter. Reps worked those leads manually, inconsistently, and often not at all.
After deploying Prospecting Agent across the trial motion, engagement on outreach reached 52%. Reps no longer touch trial leads at all. They simply take the meeting when one is booked.
"My reps don't do anything now besides take the meeting," Steven says.
A 150-Seat Deal the Team Never Prospected
The clearest proof came when Steven temporarily put himself on the trial motion after offboarding a rep. A response came in from Prospecting Agent's outreach. It turned into a 150-seat deal.
"I literally had a response and it turned out it's a 150-seat deal," Steven says. "I just booked it this morning."
No rep prospected that account. No one manually crafted the email. The AI agent identified the opportunity, personalized the outreach, and created the conversation that led to revenue.
A Sales Leader Who Thinks Differently Now
For Steven, the shift went beyond one tool, one metric, or even his own team. Watching Prospecting Agent succeed on a use case Pingman had deprioritized for years changed how he thinks about where AI fits in the sales process, and changed how the rest of the organization thinks about it too. Trial leads are no longer low-value distractions. They are a scalable pipeline source that just needed the right system behind it.
The confidence has spread. Steven plans to extend Prospecting Agent into customer success for upsell opportunities, into post-demo follow-ups, and into proof-of-concept workflows. He is building what he calls "the PingPlotter sales admin 2.0," layering HubSpot's AI tools across the entire sales journey, so reps can focus on selling instead of administering.
"There's a lot more I'm going to be doing with this," Steven says. "The fact that I can get data from our CRM and act on it without pulling it out, running it through something else, and pushing it back, that changes everything."
What started as an experiment with a neglected lead segment has become the foundation for how Pingman plans to grow. And at the center of it is a simple belief Steven keeps coming back to: if AI can handle the outreach, his team can spend all their time on what actually matters, helping the people on the other end solve their network problems.
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