I turn complex partner portfolios into operating systems that run, get measured, and grow.
Most recently, I owned the partner success motion for three of Cloudflare’s largest platform partners — spanning global systems integration, managed services, and digital experience — within one of the company’s largest partner revenue portfolios. 15+ years across Apple channel sales and Cloudflare partner success, with AI as the analytical layer underneath the work.
Supported one of Cloudflare’s largest partner revenue portfolios across GSI, MSP, and digital experience platform partnerships.
🔎 Revenue Leakage Identified
Surfaced a seven-figure unrecognized revenue opportunity and a six-figure unbilled services gap through manual reconciliation and partner-footprint analysis.
📉 Churn Pattern Surfaced
Surfaced recurring churn in an untracked resell book and helped shift renewal accountability to the partner’s SDM team, enabling new tooling, tighter customer ownership, and a multi-cloud consolidation win.
🎯 11 quarters / $84M+
Consecutive quarters at or above quota at Apple, on an annual channel territory of $84M+. Designed onboarding toolkit that supported a 2x increase in US Channel Sales headcount.
Approach
AI replaces the data team behind the partner manager that most companies don't have.
That's the thesis underneath everything below. Partner work is bottlenecked on two things: data and influence. AI dissolves the data half — install-base-wide audits, custom reporting, methodology encoded as tooling. The influence half is still relationship work. Teaching the partner what they don't see. Framing the problem in their language. Having the conversation everyone has been avoiding.
Good partner work starts with empathy and the details of the partner's business. You learn how the partner makes money before you tell them how to grow it. You read their internal incentives before you push for change.
In commercial terms: pipeline that wasn't there. Co-sell motions that didn't exist a quarter ago. Renewals the partner runs without you. Migrations that stop drifting and start closing.
Case studies
Case study · 01
From Renewal Blind Spot to Partner-Owned Motion
A global managed-services partner. Half their business is MSP. The other half is resell.
Signal Recurring YoY churn surfaced in an untracked resell book, two years running.
Action Joint 180/90/60 renewal cadence and tracker, run manually for a year.
Impact Partner SDM team took ownership of renewals, built their own tooling, won a major multi-cloud consolidation that would have churned under the prior motion.
As Cloudflare continued investing in its partner ecosystem, one global managed-services partner was operating across two different motions: a managed-services business and a resell business. The managed-services side had clear ownership and renewal discipline. The resell side had less visibility, which made churn harder to see and harder to act on.
My formal scope centered on partner success: supporting the partner’s technical team, improving post-sales health, and strengthening the managed-services renewal process. But the partner stakeholders I worked with every day were accountable for the broader customer relationship, so I looked for ways to help them see the full picture.
I manually reconciled available renewal and account data to identify patterns in an under-tracked resell book. The analysis surfaced a recurring churn issue that had not been visible in the existing operating model.
I brought the signal into the QBR and reframed the issue around partner ownership: the team did not need blame, they needed visibility, clear renewal accountability, and a simple operating rhythm.
I then built and ran a joint 180/90/60-day renewal cadence for the resell book, supported by a lightweight tracker across both account teams. For a year, I operated the process manually: keeping upcoming renewals visible, forcing the right conversations earlier, and giving the global alliance team the evidence they needed to argue for a more durable operating model.
Over time, the partner built its own customer-insights tooling modeled on the tracker, moved renewal ownership into its SDM team, and strengthened its ability to retain and consolidate strategic customers.
The judgment call worth naming: I had built a more polished dashboard that would have been more useful than the version they were running. I deliberately did not make that the center of the process. The goal was not dependency on my tooling; it was partner ownership. They needed to build the habit, accountability, and operating rhythm internally.
The hard part was the QBR. The dashboard was just what made the conversation possible.
Case study · 02
Operationalizing an Embedded Platform Partnership
A digital experience platform partner with a large embedded customer base built on Cloudflare’s CDN and security layer.
Part A — The revenue Cloudflare wasn't capturing
Signal Six-plus years of order history; active customers without corresponding orders.
Action Reconciled order history against per-customer data-transfer metrics using AI.
ImpactSurfaced material revenue coverage gaps and created a repeatable audit path for partner-account hygiene.
This partner relationship had grown over multiple years across renewals, platform changes, and internal ownership transitions. The data existed, but it lived across different systems and views. There was no simple operating layer that connected active customer footprint to active commercial coverage.
I built an AI-assisted reconciliation workflow to compare historical order records against customer-level usage signals. The goal was not to assign fault. It was to make an invisible operating gap visible enough that both teams could validate it and act on it.
The analysis surfaced a material set of active customer records that required commercial review. I packaged the findings for the partner and internal stakeholders in a way that made the issue clear, actionable, and tied to customer footprint rather than blame.
The lesson: partner scale creates hidden operational debt. You do not fix that with another meeting. You fix it by building the missing view.
Part B — The migration the partner couldn't operationalize
SignalA long-running embedded-customer migration lacked account-level scoping, readiness visibility, and a durable commercial model.
ActionBuilt the operational scoping layer: DNS-readiness audits, package mapping, pricing logic, and a partner-facing dashboard.
ImpactPartner sales and renewals teams adopted the dashboard, and the corrective pricing framework became the model for go-forward migrations.
The same partner was also navigating a complex customer migration: legacy deployment patterns, new packaging, and a new platform experience all had to move together. The strategic direction was understood. The blocker was operational clarity.
I built the layer that made the migration manageable: DNS-readiness audits across the customer base, account-level package mapping, pricing logic, and best-practices guidance for configuring the new model at scale. As the conversations evolved, the reporting evolved with them. Eventually, that became a partner-facing dashboard used by sales and renewals teams to scope and manage the migration.
The harder discovery was commercial. Early migration data showed that the partner’s default renewal motion could create long-term pricing misalignment. The framing that worked was not “this hurts Cloudflare.” It was “this creates a future-state model that may not serve your customers, your margin strategy, or your ability to grow the partnership.”
I proposed a corrective approach: discount-to-upgrade rather than discount-to-stay, with the dashboard's upsell logic giving the partner's sales team a reason to push customers up the package stack. I surfaced the systemic pricing risk to internal leadership and escalated to my GPAM peer. The corrective framework became the model for go-forward migrations.
The hard part was not finding the number. It was translating the number into a partner-owned business problem.
Case study · 03
Reconstructing a Strategic Partner Footprint
A global systems-integration partner with a large, complex resell portfolio and limited customer-level reporting.
SignalCustomer-level visibility was limited, making it difficult to assess footprint, service coverage, expansion potential, and migration timing.
ActionBuilt a 3,500+ account audit that turned limited partner reporting into customer-footprint visibility across industries, geographies, verticals, and service usage.
ImpactSurfaced material service-coverage gaps, created a usable customer map, and gave internal and partner teams a stronger foundation for expansion and migration-planning conversations.
After a recent partnership renegotiation, customer-level reporting remained limited. Most people would have treated that as the end of the conversation. I treated it as the start of the audit.
I built a 3,500+ account portfolio audit to recover customer-level visibility from the data available on our side, mapping accounts by industry, geography, vertical, and service usage. The output was the customer map we did not have: a practical view of the partner’s footprint, service coverage, expansion potential, and migration-planning risk.
What the audit gave us first was standing. It proved the data was retrievable and could be turned into an operating view. From there, the work became a translation problem. The same analysis told different stories depending on who needed to act.
For the internal product manager, it was about migration sequencing: which customers were in scope, where the strategic risk sat, and why timing needed another look. For the partner’s alliance manager, it was about resell expansion: two potential product-line conversations grounded in actual customer footprint rather than abstract catalog strategy.
The internal work was making the case visible. Not pushing a roadmap that was bigger than me, but giving the people who could influence it the data and strategic-customer argument they needed.
Working with AI
I use AI as a working tool, not a branding point.
In my partner work, I used Claude and other frontier models as daily analytical partners for the infrastructure underneath the case studies on this site: portfolio audits, package logic, migration planning, pricing-model analysis, dashboard prototypes, and operational workflows that turned ambiguous partner problems into repeatable operating systems.
The model did not make the strategic choices. It helped me move faster once the judgment call was clear.
The work generally falls into a few patterns.
Portfolio-scale audits. Workflows that normalize large sets of account, usage, and customer-footprint data to surface patterns that would be difficult to find manually. The 3,500+ account customer map and install-base DNS-readiness audit both started here.
Methodology encoded as tooling. Package matrices, pricing logic, migration-readiness checks, customer-footprint analysis, and commercial-coverage reviews. The value was not asking AI for an answer. The value was turning a repeatable methodology into something durable enough to run across a full partner portfolio.
Dashboards that survive the partner manager. Interfaces and trackers that partner and internal teams could use after the initial analysis was done. The goal was not to make people dependent on me; it was to give them a working operating view they could keep using.
Operational automation. Draft communications, intake tracking, order-flow support, and other workflow automation that reduced partner-manager overhead and made follow-through easier.
The work that follows is not really about the model. It is about what changes when a partner manager has analytical leverage they did not used to have. Investigation stops being bottlenecked on whether someone has time to manually reconcile a thousand-row export.
This is the kind of work I want to keep doing.
Background
Cloudflare — Partner Success. Owned partner success across three of Cloudflare’s largest platform partners, supporting one of the company’s largest partner revenue portfolios across GSI, MSP, and embedded-platform relationships.
Apple — Channel Sales, 12 years. Ran an $84M+ annual territory across consumer and wireless channel. 11 consecutive quarters at or above quota. Designed the onboarding toolkit that supported a 2x increase in US Channel Sales headcount. Ran a partner-website pilot that drove +16% sell-through on Apple Watch (amazon.com) and +21bp on MacBook Pro (bestbuy.com).
Sprint — Channel, prior. Same domain, earlier in career.