We recently hosted a webinar with two revenue operations leaders who have been using Von with their teams for the past several months. Jesse Meller, Head of Global Enablement and Operations at Canary Technologies, and Natalie Love, VP of GTM Strategy and Operations at 15Five, both came with real stories about how they're putting Von to work. Not theoretical use cases. Actual tasks they've handed off to Von that are producing results for their teams right now.
Here are the highlights.
Jesse's Salesforce Audit: From 71 Workflows to 9
Jesse's team had a problem that will sound familiar to anyone who's inherited a Salesforce instance. Four years of fast growth, constant firefighting, and workflows built on top of workflows had left them with a system that was starting to break. AEs were getting timeout errors when updating opportunities because a single field change was triggering five or six automations at once. Reps were frustrated. The ops team knew something was wrong but didn't have time to stop and do a full audit.
So Jesse's two Salesforce analysts used Von to conduct one. In less than a day, Von came back with a comprehensive analysis of their entire Salesforce instance and a 19-week remediation plan. It identified 71 unique workflows running at any given time, a majority of which were referencing the same objects and fields. That overlap was causing the timeout errors the AEs were experiencing.
Von's recommendation: consolidate from 71 workflows down to 9. Jesse's team kicked off that project and expects to have a completely rebuilt, much cleaner CRM by the end of Q2.
The 19-week timeline assumed one person working on it. With three people on the project, they're moving faster. But the real time savings was in the analysis itself. Mapping 71 workflows, identifying the conflicts, and prescribing a consolidation plan is weeks of work for a human. Von did it in hours.
The Product Launch Sidekick
Canary Technologies ships a lot of products. When Jesse started, they offered six solutions. Today it's closer to 17. When they launched their AI voice solution for hotels in February, they knew the product would be well received, but they also knew the technical complexity would generate questions and objections they hadn't fully anticipated.
So Jesse set up what he now calls a "launch sidekick." For the first month after launch, Von ran a daily analysis on every single sales meeting about the new product. It tracked overall sentiment, key objections, specific questions that came up, how pricing conversations went, and the predicted outcome of each call.
Within days, they were able to refine their script and build better responses for questions they hadn't planned for. They could see which types of hotels and brands were most receptive, and where the messaging needed work.
That daily cadence has since moved to a weekly report that Von sends to Jesse's inbox every Monday. The exec team, solutions engineers, and product managers are all on the thread. It's now standard practice at Canary: every new product launch gets a Von-powered feedback loop from day one.
The Taylor Swift Analysis (Yes, Really)
This one is fun. Canary is a hotel technology company, and with the World Cup coming to the US this summer, someone on the sales team suggested building a campaign around it. Jesse wanted real data to back the pitch, so he asked himself: what recent event had a comparable impact on the hospitality industry?
The answer was the Eras Tour.
Jesse asked Von to find Canary customers who were using their guest-facing solutions in cities where the Eras Tour performed, then compare product usage and revenue during those weekends against the other 51 weekends of the year.
Von pulled a list of 314 hotels, broken down by city and product. The results: a 50% increase in guest interactions through Canary's messaging solution and a 35% increase in average upsell revenue per weekend when the Eras Tour was in town. That became the foundation for their World Cup campaign and talk track. A few sentences in, and Von had delivered the data that would have taken a cross-functional project to assemble manually.
Natalie's Customer Health and Renewal Intelligence
Over at 15Five, Natalie has Von connected to Salesforce, Gong, Zendesk, and Snowflake. She started with five licenses. When I talked to her, she was at 40 users across account management, customer experience, sales, marketing, product marketing, RevOps, and enablement.
Her first priority was retention. Natalie set up Von to cross-reference product usage data, support tickets, and call sentiment to surface at-risk renewals before they came due. Going into Q2, she ran a query asking Von to review all customers up for renewal, flag anyone below expected usage thresholds, listen to their recent calls, review their tickets, and generate a save plan for each account.
Her account manager had independently set up the same query. That's the part Natalie kept coming back to: the team is building this themselves, which means they trust the output. When a list comes from RevOps, reps want to know where the data came from. When they build the analysis themselves in Von, they don't question it, because they were the ones who refined the query and validated the results.
Closed-Loop Product Feedback
15Five ships features fast, and sometimes the gap between "we released this" and "the customer who asked for it actually knows it exists" is wider than anyone realizes. Natalie has Von searching Gong calls, emails, and Zendesk tickets to identify customers who previously complained about a specific issue, then cross-referencing that against recently shipped features that address it. The goal is to make sure those customers hear about the fix and get a proactive outreach, not a generic release note.
Territory Planning in Days Instead of Weeks
At the end of last year, 15Five was adding an SMB segment to their sales funnel. Natalie needed to figure out whether the pipeline could support it, how to segment the employee-count tiers, how many reps to put in each pod, and what pipeline coverage would look like against quota.
She described the constraints to Von: total number of AEs, how many she wanted in each segment, the quota targets. Von analyzed a full year of pipeline data and came back with segment recommendations, pipeline weights per rep, and coverage ratios against quota. Through a few rounds of back-and-forth, Natalie landed on different segmentation tiers than she'd originally planned, based on how the pipeline data actually broke down.
A project that would have taken her weeks was done in a couple of days. And because Von stores organizational memory, it now knows what "mid-market" and "SMB" mean in 15Five's context, even though the Salesforce fields haven't been updated yet. Any future query using those terms pulls the right segments automatically.
The Biggest Takeaway
Sahil asked both speakers what they'd tell a friend who was burned out on AI tools that don't deliver. Natalie's answer was sharp: every tool has AI features now, but the question is whether that AI was built with a deep understanding of how revenue teams actually work. She can run the same prompts in a general-purpose model, but it won't answer the way a revenue operations professional would. Von does, because it was built for this specific job.
Jesse put it differently. He said Von lets him operate at full capacity. He has context across systems he doesn't personally know inside and out, and Von bridges that without requiring him to become an expert in each tool. It's faster than he is at pulling reports, better at cross-referencing data across systems, and it delivers the output in whatever format he needs.
Both of them are treating Von the way the positioning describes it: as headcount. Not a tool to check occasionally. Capacity they rely on daily.
Want to see what Von can do with your data? Request a demo or watch the full webinar on demand.
