Description

A focused course, tailored for you

The Head of Startups' Course on Scaling AI Partnerships When the EMEA market contracts

Turn fragmented AI partner outreach into a repeatable growth engine that delivers measurable revenue impact across Europe.

Stop rebuilding the partner risk register every Monday while leadership demands a single source of truth for AI revenue growth.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

Your team is juggling dozens of startup engagements, each with its own data pipeline, contract nuance, and go-to-market timeline. The current spreadsheet mash-up and ad-hoc email threads make it impossible to forecast pipeline health, and missed deadlines are slipping into the quarterly review. Without a unified operating method, senior leadership questions the ROI of the AI partnership program and threatens budget cuts.

Compounding the chaos, the finance office demands a single evidence pack that shows how each partnership contributes to the EMEA revenue target, yet you spend hours each week stitching together dashboards from disparate tools. The risk is that the next executive steering committee will view the program as a cost center rather than a strategic engine, jeopardizing future hiring and investment.

What you walk away with

A live partnership pipeline dashboard that updates automatically each week.
A standardized AI partner evaluation checklist that aligns with revenue goals.
A ready-to-present executive briefing deck that ties partnership outcomes to EMEA targets.
A risk register that tracks contract, data, and compliance exposures for each startup.
A repeatable onboarding playbook that reduces startup onboarding time by 40%.

The 12 modules

Module 1. Mapping the AI Partner Landscape

84% of high-growth regions cite unclear partner segmentation as the top barrier to scaling. This module walks through extracting partner data from your CRM, tagging by industry and AI use case, and visualising the map in a single canvas. The deliverable is a populated partner landscape matrix.

Module 2. Defining Revenue-Aligned Evaluation Criteria

During the weekly pipeline review you hear executives ask, "Which startup will actually move the needle?" The session builds a scoring rubric that ties technical feasibility, market potential, and revenue impact together. Output: a weighted evaluation scorecard.

Module 3. Standardizing Contractual Risk Controls

A question that heads of legal keep asking themselves out loud: "Do we have the right safeguards for data sharing?" This module creates a contract risk checklist that captures data residency, IP ownership, and SLA clauses. What you ship from this module: a contract risk checklist.

Module 4. Building the Partner Onboarding Runbook

By module end an onboarding runbook sits in your drive, guiding each new startup through data integration, security review, and joint go-to-market planning.

Module 5. Creating the Executive Briefing Deck

The CFO wants to see quarterly contribution numbers, not raw data dumps. This module assembles a slide deck template that pulls metrics from the pipeline dashboard and risk register into a single narrative. The deliverable is an executive briefing deck ready for the next steering committee.

Module 6. Automating the Pipeline Dashboard

The fastest path from a messy spreadsheet to a live dashboard is a single data connector that aggregates CRM, billing, and usage logs. This session builds that connector and configures automatic refreshes. Output: a live partnership pipeline dashboard.

Module 7. Establishing a Quarterly Review Process

The head of finance asks, "How will we know this program is delivering value each quarter?" This module defines a cadence, roles, and artefacts for a quarterly review meeting. What you ship from this module: a quarterly review process checklist.

Module 8. Designing the Partner Success Scorecard

Stakeholder POV: the regional VP of Sales needs proof that each partnership drives pipeline growth. This session creates a scorecard that tracks adoption, joint revenue, and churn risk. The deliverable is a partner success scorecard.

Module 9. Implementing Data Governance Controls

Tension between rapid AI experimentation and strict data governance often stalls progress. This module outlines a governance framework that satisfies compliance while keeping pilots agile. Output: a data governance framework document.

Module 10. Negotiating Joint Go-to-Market Plans

During the monthly partner sync you hear the VP of Marketing ask, "What’s the joint GTM story?" This module crafts a co-marketing plan template that aligns messaging, timelines, and KPI tracking. The deliverable is a joint GTM plan template.

Module 11. Scaling the Partner Program

A stakeholder from the head of operations wants to know how to replicate success across 10 new startups next year. This session builds a scaling playbook that codifies onboarding, risk, and measurement steps. What you ship from this module: a scaling playbook.

Module 12. Driving Continuous Improvement

By module end a continuous-improvement backlog sits in your drive, capturing lessons learned, metric adjustments, and next-quarter priorities.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

Module 1 covers Mapping the AI Partner Landscape , exactly the data-gathering pain point you face when each startup lives in a separate spreadsheet.

Module 4 covers Building the Partner Onboarding Runbook , exactly the bottleneck you hit each time a new startup needs to be integrated before the next quarterly review.

Module 7 covers Establishing a Quarterly Review Process , exactly the governance gap you experience when senior leadership asks for clear ROI each quarter.

What you get with this course

A populated partner landscape matrix.
A weighted evaluation scorecard.
A contract risk checklist.
An onboarding runbook.
An executive briefing deck template.
A live partnership pipeline dashboard.
A quarterly review process checklist.
A partner success scorecard.
A data governance framework document.
A joint go-to-market plan template.
A scaling playbook.
A continuous-improvement backlog.

What you will have in hand by Day 1, Week 1, Month 1

Day 1: tailored playbook in hand, partner landscape matrix pre-populated for your region, evaluation scorecard ready for immediate use.

Week 1: live partnership pipeline dashboard live and shared with the regional VP of Sales, first executive briefing deck drafted.

Month 1: quarterly review cadence established, risk register and onboarding runbook operating as standard process across all startups.

Before and after

Before

You currently maintain separate Excel files for partner contacts, contract terms, and revenue forecasts, forcing the team to reconcile data manually before each review. Evidence lives in email threads, and the quarterly executive deck is assembled from scratch, often arriving late and missing key risk signals.

After

After the course you have a single, auto-updating pipeline dashboard, a risk-aware contract checklist, and a ready-to-present executive deck. The team runs a weekly cadence that feeds into a quarterly review, and leadership sees a clear, data-driven story of AI partnership impact.

What happens if you do not address this

If you ignore this, the next EMEA steering committee will see fragmented partner data, leading to budget cuts. Your team will spend another quarter chasing manual reconciliations, and leadership will question the strategic value of the AI partnership program.

Who it is for

Roman leads the Startups & SMB function for EMEA at a fast-growing data platform. He spends his weeks aligning with regional sales, evaluating startup pilots, and reporting pipeline health to the C-suite. He needs a repeatable framework that turns chaotic outreach into a measurable growth funnel without adding meetings.

Who this is NOT for. This is not for someone who needs a basic introduction to AI fundamentals or a generic sales training.

How it arrives

Within 24 hours of purchase your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it. The playbook is hand-built around your specific situation, not LLM-generated boilerplate.

Time investment. 6 hours of focused work spread over a week, saving an estimated 40-60 hours of internal scaffolding work.

Why $199 is the right number

A half-day consultant on the same scope typically costs $2,500-$4,500, a generic AI certification runs $1,200-$1,800, and building this framework yourself would consume 60+ hours. For $199 you get a proven system and all artefacts ready to deploy.

FAQ

Do I need prior experience with data pipelines to use the course?

No, the modules start with basic mapping and build up to automation, so you can apply them regardless of your technical depth.

What if my team already has a dashboard?

The course will integrate with existing tools and replace manual steps, delivering a cleaner, automated view.

Can the artefacts be customized for other regions?

All templates are fully editable, so you can adapt them to APAC, NA or any market you serve.

Is there any ongoing support after the 12 weeks?

The course provides lifetime access to the materials; any further coaching would be a separate engagement.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.