VP, Revenue Operations & GTM Strategy
For eleven years, I've been the person hired to fix broken revenue processes inside enterprise organizations. I design the strategies, the frameworks, and the systems. Then I usually build the tools that make them real. Along the way, I've doubled revenue per account, launched new prospecting channels, and built governance structures that keep sales and product aligned.
I move between strategy, systems, and people. This is where the work gets real.
I design the annual revenue strategies and the programs that execute them—client deepening plans, account segmentation frameworks, prospecting initiatives. I work with sales leadership to understand the problem, turn it into a real plan, and make sure the org knows how to run it.
I build the infrastructure that keeps your revenue processes running. That means data integration, BI platforms, governed data sources, and usually at least one AI-powered automation that saves your team dozens of hours a year. I work in Salesforce, Power BI, Tableau, and Python. I know what's possible.
Strategy that doesn't land with the sales team is just documentation. I own the full program rollout—change management, training, adoption metrics, and the feedback loops that make it better over time. I work with RMs, product partners, and leadership to make sure new initiatives actually stick.
I lead cross-functional teams through ambiguous problems: defining territory coverage models, designing incentive structures, building competitive research functions, and creating the governance frameworks that let distributed teams make consistent decisions.
Here's what transformation actually looks like.
Illustrative figures shown for format only — see result below for the real numbers.
Our top relationship managers were running client deepening strategy sessions once a year, mostly off memory and scattered spreadsheets. Good RMs know their clients. But knowing isn't the same as having the data in front of you when you need it.
I owned the strategy and rollout for our client deepening program, where RMs take their top 8-12 clients each year, sit down with product partners, and pitch new solutions. That meant designing the annual cadence, driving change management across RMs and product partners, and building the reporting underneath it, including a unified intelligence platform on Power BI and Tableau pulling from multiple Salesforce instances, covering 500+ users and 12,000+ accounts.
Average deepening revenue per client roughly doubled year over year, from around $60k to $130k+ on average, program-wide.
Ahead of an internal strategy session, the RM walks in already knowing the client cold. The product partners in the room usually don't. Not because they don't care, but because there's no real channel for that information to reach them unless the RM briefs each one by hand.
An AI-generated packet that goes out by email ten days before the internal strategy session, ahead of the RM and product partners sitting down together. It pulls from Salesforce, internal source systems, and external data like Dun & Bradstreet, and turns all of it into one summary everyone reads before they're in the room.
Manual research time cut by more than half, and product partners walk into the session already caught up instead of hearing the client's story for the first time live.
Coverage existed, but nobody could see all of it at once. Different groups inside the bank managed their own account and territory assignment models, some by geography, some by industry, some by account size, with no shared documentation. If you needed to know who owned a given account or prospect, the honest answer was usually "check a spreadsheet, or ask around."
I led the initiative to fix that. I benchmarked how competing banks handle territory coverage, pulled in outside research from firms like McKinsey, and turned that into a concrete recommendation: a governed data source with defined owners for each model, documentation standards every group would follow, and a searchable coverage directory that answers who covers what and why. I didn't stop at the recommendation. I built a working prototype of the lookup tool myself, so leadership could see the concept before being asked to invest in it.
Leadership signed off on the governance model and the phased roadmap. This one's still an active initiative I'm driving, not a closed case, and that's part of the point: this is the kind of ambiguous, cross-team problem that lands on my desk, and how I go about solving it.
Eleven-plus years in enterprise revenue operations, GTM strategy, and program management at a Fortune 500 bank, currently VP, Revenue Operations & GTM Strategy. MBA from Western Kentucky University, where I also teach as an adjunct professor, covering management, finance, AI, and entrepreneurship to 100+ students a year. Salesforce Certified Administrator and Microsoft Certified AI Transformation Leader.
I don't dabble in AI. I build it, deploy it, and put it in front of revenue teams that need it to actually work. Same with systems, frameworks, and programs—my job is to make the thing real, not just make the presentation.
I move fast. I care about outcomes, not politics. I work best with leaders who want the thing actually built, not just talked about.