Q2 GTM Organization Plan
Status: Draft
Created: 2026-03-21
Updated: 2026-03-21 (AI Execution Model)
Author: Cursor Agent
Model: Platform Team Organization (Initiative → Project → Issue)
Research: Bain, McKinsey, Accenture, Slalom best practices
Execution: AI-executed (Cursor Agent automation)
Teams: Marketing, Sales (2 teams)
1. The Model: Platform-Style GTM Organization
Why This Approach
After studying how top technology consultancies (Bain, McKinsey, Accenture, Slalom) organize GTM and applying Platform team’s proven structure, we organize GTM work as:
Initiative (Strategic Theme)
├── Project 1 (Workstream)
│ └── Issues (Work items with owners, estimates)
├── Project 2 (Workstream)
│ └── Issues
└── Milestones (Phase gates)
Benefits:
- Clear strategic alignment (every issue rolls up to an initiative)
- Workstream visibility (projects show capacity allocation)
- Phase-gated execution (milestones prevent drift)
- Stakeholder reporting (initiative health at a glance)
- AI-executed: Agent can create, migrate, and organize autonomously
2. GTM Work Categories (Research Synthesis)
Based on analysis of top consulting firms’ GTM models, B2B services sales orgs organize around 6 core work categories:
Category 1: Demand Generation
What it is: Creating awareness and buying intent 6-18 months before purchase
Research insight: 80% of leads never convert because companies skip demand gen and jump to lead capture (Fullcast, 2024)
Brainforge application:
- Thought leadership (LinkedIn, events, content)
- SEO and organic content
- Partner co-marketing (Omni, Snowflake, Amplitude)
- Community building
Category 2: Pipeline Generation
What it is: Capturing and qualifying active buying signals
Research insight: 72% of enterprise sales outreach targets accounts at the wrong time; signal-based targeting improves conversion 58% (MarketsandMarkets, 2024)
Brainforge application:
- Outbound campaigns (ICP-targeted, signal-based)
- Inbound lead response
- Event follow-up and nurture
- Referral and expansion pipeline
Category 3: Sales Execution
What it is: Converting qualified opportunities to closed deals
Research insight: Top-quartile sales teams deliver 4-5x higher growth than bottom-quartile (McKinsey)
Brainforge application:
- Proposal development and SOWs
- Demo delivery and proof-of-concepts
- Contract negotiation and close
- Sales process optimization
Category 4: Account Expansion
What it is: Growing existing client relationships
Research insight: Bain’s Commercial Excellence 360 emphasizes post-sale value realization as key to expansion
Brainforge application:
- Client health monitoring and proactive touchpoints
- Expansion opportunity identification
- Renewal and upsell campaigns
- Case study and reference development
Category 5: Sales Enablement
What it is: Equipping sellers with tools, content, and training
Research insight: Accenture’s Reinvention Services include dedicated Client Success for commercial strategy and delivery governance
Brainforge application:
- Sales assets (decks, one-pagers, case studies)
- Demo environments and proof packs
- Training and methodology
- Competitive intelligence
Category 6: GTM Operations
What it is: Infrastructure, reporting, and optimization
Research insight: 80% of aligned sales-marketing teams reach goals vs. 50% overall (60% improvement) (Pipeline360, 2024)
Brainforge application:
- Pipeline hygiene and forecasting
- CRM automation and data quality
- Weekly/monthly business reviews
- Tooling and process optimization
3. Q2 GTM Initiative Structure
Proposed Initiatives (2 Core)
Based on research, current audit, and two-team structure (Marketing + Sales), organize Q2 GTM into 2 strategic initiatives:
Initiative 1: Q2 Revenue Pipeline
Status: Active
Target Date: 2026-06-30
Summary: Generate qualified pipeline for Q2 and Q3 via campaigns, events, and outbound
Owner: Luke (Sales), Hannah (Marketing)
Scope:
- Active campaigns (Blotout, Bask Health, Gov Evidence, Agency Intelligence, dbt, MotherDuck)
- Partner co-sell motions (Omni, Snowflake, Amplitude office hours)
- Event pipeline (Omnivision, NYC brunch, partner events)
- Outbound SDR/BDR lead generation
- Content distribution for pipeline (LinkedIn, SEO, email)
Non-Goals:
- Brand awareness without pipeline tie-in
- Content without distribution plan
- Events without follow-up automation
- Delivery work (lives in client teams)
Projects:
- Active Campaigns — Execute and optimize live campaigns (Sales-owned)
- Partner Pipeline — Co-sell with technology partners (Marketing + Sales)
- Content for Pipeline — Demand gen content driving to capture (Marketing-owned)
Milestones:
- M1: Campaign briefs finalized (Week 1-2)
- M2: First touches executed (Week 3-4)
- M3: Mid-quarter optimization (Week 6)
- M4: Q3 pipeline commit (Week 10-12)
Initiative 2: Sales Velocity
Status: Active
Target Date: 2026-06-30
Summary: Improve proposal-to-close conversion through better assets, demos, and process
Owner: Luke (Sales), Hannah (Marketing)
Scope:
- Sales assets (decks, one-pagers, case studies)
- Demo environments (Snowflake, Omni, Amplitude)
- SOW and proposal templates
- Competitive positioning
- Training and methodology
Non-Goals:
- New service development (lives in Service Line initiatives)
- Pure brand marketing without sales tie-in
- Website redesign
- Client delivery work
Projects:
- Sales Assets — Case studies, decks, one-pagers (Marketing + Sales)
- Demo Environment — Live demo instances for prospects (Sales + Platform)
- Proposal System — SOW templates, estimation, approval workflow (Sales-owned)
Milestones:
- M1: Active case studies completed (Week 2-4)
- M2: Demo environments live (Week 4-6)
- M3: Proposal template v2 deployed (Week 6-8)
- M4: Sales asset library complete (Week 10-12)
4. Project Consolidation Map
Current State → Future State
| Current | Team | Future Initiative | Future Project |
|---|---|---|---|
| Campaign Briefs (Gov, Blotout, Bask, Agency) | Sales | Q2 Revenue Pipeline | Active Campaigns |
| Outbound SDR/BDR | Sales | Q2 Revenue Pipeline | Active Campaigns |
| Partner office hours (Omni, Amplitude, Talisma) | Marketing | Q2 Revenue Pipeline | Partner Pipeline |
| LinkedIn Organic Content | Marketing | Q2 Revenue Pipeline | Content for Pipeline |
| General LinkedIn | Marketing | Q2 Revenue Pipeline | Content for Pipeline |
| SEO Content | Marketing | Q2 Revenue Pipeline | Content for Pipeline |
| Case Studies (15 backlog) | Marketing | Sales Velocity | Sales Assets |
| Decks (SaaS, Product Analytics, Ecom) | Marketing | Sales Velocity | Sales Assets |
| Adhoc Sales Assets | Marketing | Sales Velocity | Sales Assets |
| Demo Environments | Sales | Sales Velocity | Demo Environment |
| WBR/MBR Metrics | Sales | Sales Velocity | Proposal System |
| GTM Operations | Sales | Sales Velocity | (absorbed into projects) |
5. Label Taxonomy (Standardized)
Initiative Labels
initiative:q2-revenue-pipeline
initiative:sales-velocity
Team Labels
team:sales
team:marketing
Work Type Labels
work-type:campaign
work-type:content
work-type:event
work-type:asset
work-type:ops
Stage Labels
stage:discovery
stage:icp-research
stage:asset-prep
stage:active
stage:nurture
stage:closed
Service Line Labels
service:data-platform
service:e2a
service:ai-agents
service:reporting
service:omni
Priority Labels
priority:p0-revenue
priority:p1-velocity
priority:p2-enable
priority:p3-ops
6. AI Execution Plan
Step 1: Create Initiatives (2)
1. Q2 Revenue Pipeline (targetDate: 2026-06-30, status: Active)
2. Sales Velocity (targetDate: 2026-06-30, status: Active)
Step 2: Create Projects (6 Total)
Under Q2 Revenue Pipeline:
- Active Campaigns
- Partner Pipeline
- Content for Pipeline
Under Sales Velocity:
- Sales Assets
- Demo Environment
- Proposal System
Step 3: Migrate Issues (AI-Executed)
Rule-Based Migration (Agent-Executed):
| Rule | Destination Initiative | Destination Project |
|---|---|---|
| Issue title contains “campaign” OR label = campaign | Q2 Revenue Pipeline | Active Campaigns |
| Issue in “Outbound SDR/BDR” project | Q2 Revenue Pipeline | Active Campaigns |
| Issue title contains “office hours” OR “partner” OR “event” | Q2 Revenue Pipeline | Partner Pipeline |
| Issue in “LinkedIn” project OR label = linkedin | Q2 Revenue Pipeline | Content for Pipeline |
| Issue title contains “case study” OR “deck” OR “one-pager” | Sales Velocity | Sales Assets |
| Issue title contains “demo” OR “proof of concept” | Sales Velocity | Demo Environment |
| Issue title contains “proposal” OR “SOW” OR “WBR” | Sales Velocity | Proposal System |
| No matching rule → Human review queue | (pending) | (pending) |
Step 4: Apply Labels (AI-Executed)
Auto-Label Rules:
- SAL-* issues →
team:sales - MAR-* + CON-* issues →
team:marketing - Campaign issues →
work-type:campaign - Case study/deck issues →
work-type:asset - LinkedIn/SEO issues →
work-type:content
Step 5: Close/Archive (AI-Executed with Human Approval)
Auto-Close Rules:
- Issues not touched since Feb 1, 2026 AND no assignee → Close
- Issues with status = Canceled → Close
- Duplicate issues (CON-372/373) → Close lower priority
- Stale WBR tickets (older than 2 weeks) → Close
Human Review Queue:
- Issues without clear initiative match
- High-priority issues (p0, p1) before closure
- Campaign status unclear (Gov Evidence?)
7. Comparison: Before vs After
Before (Current)
- 2 teams (Sales, Marketing) — ✅ Correct
- 50+ open issues per team
- 15+ case studies in backlog
- No initiative hierarchy
- Mixed project naming
- Unclear state usage
After (Proposed)
- 2 teams (Sales, Marketing) — preserved
- 2 initiatives (Revenue Pipeline, Sales Velocity)
- 6 projects (3 per initiative)
- 30-35 focused issues per initiative
- 5 active case studies, 10 archived
- Clear hierarchy: Initiative → Project → Issue
- Standardized states and labels
8. Success Metrics
| Metric | Before | Target (AI Execution) |
|---|---|---|
| Initiatives created | 0 | 2 |
| Projects created | 15+ scattered | 6 consolidated |
| Issues without initiative | 100+ | 0 |
| Issues migrated to initiatives | 0 | 80%+ |
| Labels applied | Inconsistent | Standardized |
| Stale issues closed | Manual | AI-identified, human-approved |
| Execution time | 3 weeks human | 1-2 days AI |
9. AI Execution Advantages
- No Migration Effort Concern — Agent performs bulk operations via Linear API
- Rule-Based Consistency — Same logic applied to all issues, no human error
- Fast Execution — Hours vs. weeks for manual reorganization
- Reversible — Linear archive/close is reversible if needed
- Human-in-the-Loop — High-priority or ambiguous items flagged for review
10. Research References
- Bain & Company — Commercial Excellence 360, holistic GTM diagnostic framework
- McKinsey — Enterprise tech GTM reinvention, omnichannel orchestration, 4-5x growth differential
- Accenture — Reinvention Services structure (7 specialized units + 3 engines + Client Success)
- Slalom — Industry-vertical account management structure
- Fullcast/Pipeline360 — Demand vs lead generation distinction, 80% lead failure rate
- MarketsandMarkets — Signal-based targeting (58% higher conversion)
11. Open Questions
- Gov Evidence Intelligence campaign — active or archive?
- Which case studies are true Q2 priorities vs. icebox?
- Who has Linear admin rights for bulk operations?
- Should we auto-close or auto-archive stale issues?
- Any issues to exclude from AI migration (keep as-is)?
12. Next Steps
- Approve 2-initiative structure (owner: Uttam)
- Confirm Luke and Hannah as initiative owners
- Verify Linear API access for agent
- Answer open questions (Gov campaign, case study priorities)
- Execute AI migration (agent)
- Review human queue (Luke, Hannah)
13. Related Resources
- Linear audit notes: [agent conversation 2026-03-21]
- Q2 cleanup plan:
knowledge/plans/q2-gtm-linear-cleanup-plan.md - Platform Q2 initiatives: Linear (Q2 2026 Platform Planning, Sales Engineering Q2, etc.)
- LMNT initiative structure: Linear (LMNT | Documentation, LMNT | Reporting, etc.)