open to senior RevOps and GTM roles
I build revenue engines for scaling companies and the AI tooling that runs them.
Ten years turning growth targets into operating plans, forecasts people trust and sales teams that hit their numbers. Most recently leading GTM strategy for Motive’s international markets.
Built and scaled GTM at
WeWork
Aircall
Motive
Ocean OS
WeWork
Aircall
Motive
Ocean OS
WeWork
Aircall
Motive
Ocean OS
WeWork
Aircall
Motive
Ocean OS
3 unicorns + 1
Scaled GTM at three unicorns and founded an AI foundation model startup.
WeWorkAircallMotive
Founder, Ocean OS · AI foundation model for marine forecasting
Hypergrowth
Company ARR while I was in the GTM team.
WeWork$400M → $3B7.5x
Aircall$50M → $100M+2x
Motive$550Mnow
3 regions
Teams managed across EMEA, North America and APAC.
Selected work
Five problems, what I changed, and what moved
Featured
Motive · AI inbound agents
AI agents that qualify every inbound lead
70%
of inbound qualification automated
<2 min
response time to new leads
+40%
discovery data completeness
The problem
Inbound discovery was inconsistent and often missed need, fleet size, use case and buying process, which slowed deals further down the funnel. SDRs spent their time qualifying instead of building outbound skills.
What I did
Built AI inbound agents connected to Salesforce, the knowledge base and calendars. They run structured discovery, ask adaptive follow up questions, score each lead, update the CRM and route qualified opportunities to AEs with a structured handoff.
The result
Most inbound qualification now runs without a human, leads hear back within two minutes and SDR capacity moved to outbound pipeline generation.
Motive · Forecasting
One forecasting standard across four countries
30% → 15%
forecast variance
The problem
Every country leader forecast differently, some optimistic and some cautious, on different timelines.
What I did
Installed a weekly rhythm of deal reviews, business reviews and an executive forecast call. No deal counted toward commit without economic buyer contact, and every leader forecast the next quarter too.
The result
Variance halved and mid market sales cycles shortened by one to two months.
Motive · AI coaching
A coaching agent that reviews every sales call
3% → 6%
call to SQL conversion
The problem
Cold call conversion in Mexico and the UK sat well below benchmark. Transcripts showed weak qualification and missed objections.
What I did
Scoped an agent with Enablement and AI Ops that scores each transcript and sends feedback to the rep straight after the call, with a weekly manager review.
The result
Conversion doubled. The agent now also captures competitor mentions and feature requests for Product and Marketing.
Motive · Data enrichment
Automated enrichment in place of a manual research team
1% → 3%
account to SQO conversion
The problem
Leads were enriched by hand by an offshore team spread across regions. It was slow, expensive and inconsistent.
What I did
Designed a waterfall enrichment workflow that fills contact gaps automatically before an account reaches a rep.
The result
Connect rates rose from 8% to 15% and conversion to qualified opportunity tripled, at a fraction of the cost.
Aircall · Mid market relaunch
Winning bigger customers with a mid market relaunch
+9 pts
win rate
The problem
Aircall was winning small teams and losing larger ones on packaging, qualification and partner coverage.
What I did
Refreshed pricing and packaging, embedded MEDDPICC stage exit rules in Salesforce and formalised partner co selling.
The result
Win rate up 9 points, partner sourced pipeline up 42% and NRR from 109% to 116%.
Full funnel operator
Revenue strategy and GTM engineering, end to end
I design the plan the sales team runs on and build the systems that generate and route its pipeline, from the first account researched to the deal closed.
GTM engineering builds the pipelineRevenue strategy converts and forecasts it
TAM mapping
Account research
Signal tracking
Demand gen
CRMLead lands in CRM
Qualification
Scoring and routing
Pipeline management
Forecast
Closed won and expansion
GTM engineering
build
- TAM mapping and tiering
- Signal tracking
- Waterfall enrichment
- Lead scoring and routing
- AI inbound agents
- Automated outbound
- Call coaching agents
- Agent evals and token spend
Revenue strategy
plan
- Business and operating plans
- Territory and quota design
- Capacity and coverage models
- Sales methodology and MEDDPICC
- Forecast cadence
- Pricing and packaging
- Partner and reseller programmes
- Enablement and ramp
30% → 15%
forecast variance
Shared foundation
ICP modelling
Account tiering
Tool selection
ACV to OTE economics
Experience
Ten years of building GTM engines
2025 to now
Motive
AI powered fleet management
Head of GTM Strategy and Operations, International Markets
Own commercial planning for Canada, Mexico, the UK and Germany with a 130 person sales organisation and a team of five. Moved Canada upmarket toward a balanced Mid Market and Enterprise mix, brought UK SMB coverage in market and built the reseller programme from zero to $1M qualified pipeline in two quarters.
2023 to 2025
Ocean OS
AI weather forecasting
Cofounder and CEO
Built the company and its commercial engine from a blank page. Raised £1M across R&D grants and pre seed equity and personally converted three proofs of concept into paid enterprise pilots, all still live after handover.
2020 to 2023
Aircall
Contact centre SaaS
Director, Revenue Strategy and Operations
Built RevOps from one person to seven while ARR grew from $50M to over $100M. Led the quote to cash rebuild on Salesforce CPQ, NetSuite and Ironclad, and installed the operating rhythm that cut gross churn by 2.1 points.
2016 to 2020
WeWork
Flexible workspace
Senior Manager, Sales Strategy and Operations EMEA
Built territory, quota and capacity models across EMEA as the sales team grew from 15 to over 250. Rep productivity rose 34% and CAC payback fell from 14 to 9 months. Started as an Account Executive opening the first DACH and CEE sites at 85% occupancy before launch.
2013 to 2016
Earlier
Rocket Internet · Ebner Stolz
Scaled marketplace orders from 50 to 1,000 a day in Dubai and led commercial due diligence on a €90M acquisition. MSc Management with Distinction from Bayes Business School.
How I work
Three rules I run every team by
01
Cadence serves execution
Every recurring meeting earns its slot. Reporting exists to unblock deals, so I cut what nobody acts on.
02
Every blocker gets an owner
Product gaps and broken processes go up the chain with a named owner and a date attached.
03
Efficiency gates set upfront
Before a market launches I agree the ACV to OTE threshold and the review date, so reinvesting or pulling back is decided on evidence.