GTM Strategy Playbook: Marketing × Sales × CS Integration 2025

Chapter 1: What is GTM Strategy?

GTM Definition & Framework

GTM (Go-to-Market) Strategy is the integrated plan for how a company brings its product to market and grows revenue. It answers three core questions:

1. Who is the target customer? (ICP: Ideal Customer Profile)
2. How do we reach them? (Channels: Content, Ads, Outbound, Product-Led)
3. How do we convert and retain them? (Sales Process + CS Journey)

Unlike a "sales strategy" (which focuses only on closing deals) or "marketing strategy" (which focuses only on demand generation), GTM strategy integrates all three revenue functions: Marketing, Sales, and Customer Success.

┌─────────────────────────────────────────────────────────────────────────┐
│                         CUSTOMER LIFECYCLE                              │
├─────────────────────────────────────────────────────────────────────────┤
│  Awareness → Consideration → Decision → Onboarding → Adoption → Expansion
│     ↓            ↓             ↓            ↓            ↓          ↓    │
│  MARKETING     MARKETING     SALES         CS           CS         CS    │
│  (Content,     (Nurture,     (Demo,       (Kickoff,    (QBR,     (Upsell,│
│   SEO, Ads)     Events)      Close)       Training)   Support)   Renewal)│
└─────────────────────────────────────────────────────────────────────────┘

Key Insight: GTM success depends on handoff quality between stages. If Marketing sends unqualified leads to Sales, conversion rates drop. If Sales overpromises to CS, churn increases.

Sales-Led vs Marketing-Led vs Product-Led

There are three primary GTM motions. Most successful companies use a hybrid approach.

Hybrid GTM Examples

• Atlassian: Product-Led for acquisition (free tier, viral sharing) + Sales-Led for enterprise expansion (6-figure deals)
• Dropbox: Product-Led for SMB (freemium, referrals) + Sales-Led for Dropbox Business ($15K+ ACV)
• Zoom: Product-Led for individual users (free tier) + Marketing-Led for mid-market (webinars, trials) + Sales-Led for enterprise (custom pricing)

Chapter 2: Customer Journey Design

A customer journey is the step-by-step path a prospect takes from first awareness to becoming a loyal, expanding customer. Designing the journey means defining:

• What touchpoints exist at each stage (webinar, demo, onboarding call, QBR)
• What data is collected at each touchpoint (behavioral signals, firmographic data, sentiment)
• What actions are triggered at each stage (automated email, sales call, CS check-in)

Acquisition Journey (Awareness → Decision)

The acquisition journey covers the path from first brand interaction to closed deal.

Buyer Signal Mapping (Critical for Marketing × Sales Alignment)

Not all touchpoints are created equal. Map buyer signals to each stage and prioritize high-intent signals for Sales follow-up.

Related: For detailed signal detection strategies, see Buyer Signal Detection Guide.

Expansion Journey (Onboarding → Expansion)

The expansion journey begins after contract signature. This is where CS takes the lead, with Sales re-engaging for upsell/renewal opportunities.

Churn Risk Early Warning System

The most critical GTM failure point is silent churn: customers who stop using the product but don't cancel until renewal. To prevent this:

• Monitor engagement weekly: DAU/MAU ratio, feature usage depth, support ticket sentiment
• Set churn risk thresholds: 3+ red flags = high churn risk
• Auto-trigger CS intervention: Personal check-in call within 3 days

Chapter 3: Marketing × Sales Alignment

The #1 reason GTM strategies fail is Marketing-Sales misalignment. Common symptoms:

• Marketing sends 500 MQLs/month → Sales follows up on 50 (10%) → 2 close (0.4%)
• Sales complains "leads are garbage" → Marketing blames "Sales doesn't follow up fast enough"
• Neither team agrees on what "qualified" means

The root cause? Lack of shared definitions, SLAs, and feedback loops.

MQL Definition & Qualification Criteria

MQL (Marketing Qualified Lead) is a lead that meets both behavioral and firmographic criteria, indicating sales-readiness.

Step 1: Define MQL Criteria (Joint Marketing + Sales Workshop)

Run a 2-hour workshop with Marketing and Sales leadership. Agenda:

1. Review historical data: Which leads converted to closed deals in the past 6 months? What behaviors did they exhibit?
2. Identify patterns: Job titles, company sizes, engagement levels (content downloads, demo requests, pricing visits)
3. Draft MQL criteria: Combine firmographic + behavioral filters

Step 2: Test & Iterate (30-Day Validation Cycle)

After defining MQL criteria, run a 30-day test:

• Measure: MQL-to-SQL conversion rate (target: 30%+ for healthy funnel)
• If below 30%: MQL criteria are too loose → Tighten behavioral filters
• If above 50%: MQL criteria are too strict → Loosen to increase volume

Key Metric: MQL-to-SQL conversion rate = (# of SQLs / # of MQLs) × 100

Marketing-to-Sales Handoff Process

A broken handoff = lost revenue. Design a structured handoff workflow with clear SLAs.

Signal-Based Lead Prioritization

Not all MQLs are created equal. Use buyer signal scoring to prioritize leads with the highest conversion probability.

Example: Two MQLs with identical firmographic fit (same company size, job title, industry):

• Lead A: Downloaded 1 ebook 28 days ago (Score: 100 points)
• Lead B: Visited pricing page 3 times this week + requested demo yesterday (Score: 250 points)

Which should Sales prioritize? Lead B (10x higher conversion probability).

Implementation: Add "Lead Score" column to CRM views. Sales reps sort by score (highest first) and work down the list.

Related: For detailed signal scoring strategies, see Buyer Signal Detection Guide.

Chapter 4: Sales × CS Alignment

The second most critical handoff is Sales → CS. A broken handoff here leads to:

• Onboarding delays: Customer waits 2+ weeks for kickoff call
• Expectation mismatches: Sales promised Feature X, CS discovers it doesn't exist
• Early churn: Customer never achieves "aha moment" in first 30 days

Sales-to-CS Handoff Design

Design a structured handoff workflow with a detailed handoff document.

Handoff Document Template

Create a standardized handoff template in your CRM or Google Docs. Example fields:

Upsell & Cross-Sell Opportunity Detection

The best time to upsell is when the customer is actively getting value. CS monitors usage data and flags expansion opportunities for Sales.

Upsell Signals (CS → Sales)

Churn Risk Early Warning System

CS monitors leading indicators of churn risk and triggers Sales re-engagement when necessary.

Churn Risk Scoring

Assign points to negative signals. Churn Risk = High if total score ≥ 3 red flags.

Escalation Rule: If churn risk score ≥ 3, CS notifies Sales and schedules joint "executive sponsor" call to re-engage decision-maker.

Chapter 5: Data Integration & Tool Stack

Data silos are the #1 killer of GTM execution. When Marketing, Sales, and CS use separate tools with no data sync:

• Marketing can't see which MQLs closed → Can't optimize campaigns
• Sales can't see customer support tickets → Miss churn risk signals
• CS can't see sales notes → Don't know what was promised

The solution? CRM as the central hub with bidirectional data sync to all GTM tools.

CRM as the Central Hub

Your CRM (HubSpot, Salesforce, Pipedrive) should be the single source of truth for all customer data:

• Contact data: Name, email, company, job title (from Marketing)
• Behavioral data: Web visits, email opens, content downloads (from MA platform)
• Sales activity: Calls, emails, demos, deal stage (from Sales team)
• CS activity: Support tickets, NPS scores, product usage (from CS platform)

Marketing Automation Integration

Connect your Marketing Automation (MA) platform to CRM for bidirectional sync:

CRM → MA (Downstream Data Flow)

• Sales status updates: When Sales marks lead as "SQL" → MA stops nurture emails
• Deal closed updates: When deal closes → MA sends "Welcome" onboarding email

MA → CRM (Upstream Data Flow)

• Behavioral data: Email opens, link clicks, form submissions → Update lead score in CRM
• Campaign attribution: Which campaign/ad drove the MQL → Update CRM field for ROI analysis

CS Platform Integration

Connect CS platform (ChurnZero, Gainsight, Vitally) to CRM to share churn risk signals with Sales:

CRM → CS Platform

• Customer profile data: ACV, contract start date, renewal date, champion contact info
• Sales notes: Customer goals, promised features, red flags from handoff document

CS Platform → CRM

• Health score: Green (healthy), Yellow (at-risk), Red (high churn risk)
• Product usage data: DAU/MAU, feature adoption rate, login frequency
• NPS score: Promoter (9-10), Passive (7-8), Detractor (0-6)
• Upsell signals: User count approaching limit, feature usage exceeding plan

Breaking Data Silos

Even with integrations, data silos persist if teams use different definitions. Solutions:

1. Create a Data Dictionary

Define all key metrics in a shared document (Google Doc, Notion, Confluence). Example:

2. Use Shared Dashboards

Create a unified GTM dashboard (in CRM or BI tool) where all teams view the same metrics:

• Marketing: MQL volume, MQL-to-SQL rate, CAC
• Sales: SQL-to-Opportunity rate, Win Rate, ACV, Sales Cycle Length
• CS: NRR, Churn Rate, NPS, Time to First Value
• Unified: Revenue Growth Rate, CAC Payback Period, LTV/CAC

3. Weekly GTM Sync Meeting

Schedule a recurring 30-minute meeting with Marketing, Sales, and CS leads to review:

• MQL-to-SQL conversion rate (Is Marketing sending quality leads?)
• SQL-to-Opportunity conversion rate (Is Sales qualifying effectively?)
• Churn rate (Are we delivering on sales promises?)
• Data quality issues (Duplicate contacts, missing fields, sync errors)

Chapter 6: GTM KPI Design

You can't manage what you don't measure. But measuring the wrong KPIs is worse than measuring nothing at all.

Common mistake: Each team optimizes for its own KPIs without regard for overall revenue impact:

• Marketing optimizes for MQL volume → Sends 1,000 unqualified leads to Sales
• Sales optimizes for deal count → Closes 50 small deals instead of 10 big deals
• CS optimizes for NPS → Ignores expansion revenue opportunities

The solution? Align all team KPIs to unified GTM metrics (Revenue Growth, NRR, CAC Payback).

Marketing KPIs

Sales KPIs

Customer Success KPIs

Unified GTM KPIs

These KPIs span all three teams and measure overall GTM effectiveness:

How to Build a Unified GTM Dashboard

1. Choose a platform: CRM (Salesforce, HubSpot), BI tool (Looker, Tableau), or RevOps tool (Clari)
2. Connect data sources: CRM, Marketing Automation, CS Platform, Accounting (for ARR data)
3. Define calculations: Use data dictionary definitions (Chapter 5) to ensure consistency
4. Create views:
   • Executive view: Revenue Growth, NRR, CAC Payback, Magic Number
   • Marketing view: MQL volume, MQL-to-SQL rate, CAC, Marketing Contribution
   • Sales view: Pipeline Coverage, Win Rate, ACV, Sales Cycle
   • CS view: NRR, Churn Rate, NPS, TTFV, Expansion Rate
5. Schedule weekly reviews: Review dashboard in weekly GTM sync meeting

Chapter 7: RevOps Organization Design

RevOps (Revenue Operations) is the organizational function that unifies Marketing Ops, Sales Ops, and CS Ops under one team to break silos, align KPIs, and own the entire revenue tech stack.

What is RevOps?

Traditionally, each revenue function had its own operations team:

• Marketing Ops: Manages marketing automation, lead scoring, campaign attribution
• Sales Ops: Manages CRM, sales forecasting, quota setting
• CS Ops: Manages CS platform, health scoring, churn analysis

The problem? Each Ops team optimizes for its own function, not for overall revenue. RevOps solves this by centralizing all revenue operations under one leader (VP RevOps or CRO).

When Do You Need RevOps?

Marketing Ops × Sales Ops × CS Ops Alignment

Even if you don't have a formal RevOps function, you can align existing Ops teams through shared processes:

1. Weekly Ops Sync Meeting

Schedule a recurring 30-minute meeting with all Ops leads:

• Agenda: Data quality issues, integration failures, new process rollouts, tool updates
• Example topics:
  • "Marketing Ops: We're adding a new lead source field. Sales Ops, can you add it to your reports?"
  • "Sales Ops: We changed Opportunity Stage definitions. CS Ops, update your handoff workflow."
  • "CS Ops: Churn rate spiked 2% last month. Marketing Ops, can we analyze which campaigns drove these customers?"

2. Shared SLAs

Define cross-functional SLAs (Service Level Agreements) to ensure handoff quality:

Building Data-Driven Culture

RevOps success depends on cultural buy-in. How to build a data-driven culture:

1. Make Data Visible

• Display unified GTM dashboard on office TVs (or Slack channel for remote teams)
• Share weekly KPI snapshots in all-hands meetings
• Celebrate wins publicly ("Marketing hit 35% MQL-to-SQL rate this month!")

2. Tie Compensation to GTM Metrics

Align bonuses to unified KPIs, not just individual team metrics:

3. Weekly Data Review Ritual

Institute a weekly GTM meeting with Marketing, Sales, and CS leads (30-45 minutes):

1. Review unified dashboard (5 minutes): Revenue Growth, NRR, CAC Payback
2. Deep dive on one metric (15 minutes): Rotate weekly (Week 1: MQL-to-SQL, Week 2: Win Rate, Week 3: Churn Rate)
3. Identify action items (10 minutes): What needs to change to improve the metric?
4. Assign owners and deadlines (5 minutes): Who will do what by when?

Chapter 8: Common GTM Failures & Solutions

Even with the best strategy, GTM execution often fails. Here are the 3 most common failure modes and how to avoid them:

Failure #1: Departmental Silos

Symptoms

• Marketing and Sales blame each other for missed quota ("Leads are garbage" vs "Sales doesn't follow up")
• CS discovers churn risk only at renewal time (no early warning from Sales)
• Teams use different definitions for the same metric (e.g., "Opportunity" means different things to Sales and Marketing)

Root Cause

Organizational structure rewards departmental optimization, not cross-functional collaboration. Each VP (Marketing, Sales, CS) is measured on their own KPIs, not on unified revenue metrics.

Solution

1. Hire a CRO (Chief Revenue Officer) who owns all revenue functions (Marketing, Sales, CS). All VPs report to CRO.
2. Create shared OKRs: 50% of each VP's bonus tied to unified GTM metrics (Revenue Growth, NRR, CAC Payback).
3. Weekly GTM sync meeting: Force cross-functional communication (see Chapter 7).

Failure #2: Definition Misalignment

Symptoms

• Marketing reports "100 MQLs this month," Sales says "We only got 50"
• Sales says "We closed 20 deals," Finance says "We only booked $300K ARR (should be $400K)"
• CS reports "5% churn," but actual revenue churn is 8%

Root Cause

No single source of truth for data definitions. Each team uses their own tool (Marketing: HubSpot, Sales: Salesforce, CS: Gainsight) with different field definitions.

Solution

1. Create a Data Dictionary (see Chapter 5): Define every metric in a shared doc. Include: metric name, calculation, source of truth (which CRM field).
2. Enforce with automation: Use CRM validation rules to block incorrect data entry (e.g., "Opportunity Amount must be > $5K").
3. Quarterly data audit: RevOps reviews top 10 metrics for discrepancies and fixes definitions.

Failure #3: Tool Sprawl

Symptoms

• Company uses 15+ SaaS tools (CRM, MA, CS Platform, Analytics, Slack, Zoom, DocuSign, etc.)
• Data doesn't sync between tools → Manual CSV exports and imports
• New hires take 2 weeks to get access to all tools
• Annual SaaS spend is $200K+ for a 30-person team ($6,667 per person/year)

Root Cause

No centralized procurement or tool rationalization. Each team buys tools independently. No one owns the overall tech stack.

Solution

1. Conduct a tool audit: List all SaaS tools, owners, costs, integrations, and usage data.
2. Consolidate where possible:
   • Replace 3 point solutions with 1 platform (e.g., HubSpot Marketing + Sales + Service Hub instead of Marketo + Salesforce + Zendesk)
   • Cut tools with < 50% adoption rate
3. Centralize procurement under RevOps: All new tool purchases must be approved by VP RevOps (to prevent shadow IT).
4. Integration-first buying: Only buy tools that integrate natively with your CRM (avoid custom API work).

Chapter 9: 180-Day Implementation Roadmap

GTM integration is a 6-month journey, not a weekend project. This roadmap breaks implementation into three 60-day phases:

Days 1-60: Foundation (Analysis, KPI, Integration)

Week 1-2: Current State Analysis

Goal: Understand the current GTM setup (tools, processes, KPIs, pain points).

Week 3-4: Define GTM Strategy

Goal: Align leadership on unified GTM strategy, KPIs, and target outcomes.

• Workshop with leadership (CRO, VP Marketing, VP Sales, VP CS): Define ICP, GTM motion (Sales-Led vs Marketing-Led vs Product-Led), unified KPIs
• Create Data Dictionary: Define MQL, SQL, Opportunity, Churn, NRR (see Chapter 5)
• Set 180-day goals: Improve MQL-to-SQL from 23% → 35%, reduce sales cycle from 67 days → 50 days, increase NRR from 102% → 115%

Week 5-8: Quick Wins (Data Integration)

Goal: Implement high-impact, low-effort integrations to demonstrate ROI.

Days 61-120: Execution (Process Redesign, Training)

Week 9-12: Handoff Process Redesign

Goal: Redesign Marketing-to-Sales and Sales-to-CS handoff workflows.

• Marketing-to-Sales:
  • Implement MQL-to-Sales handoff workflow (Slack notification, lead scoring, SLA tracking)
  • Set SLA: Sales must respond within 5 minutes (hot leads) or 24 hours (warm leads)
  • Track SLA compliance weekly (target: 90%+)
• Sales-to-CS:
  • Create handoff document template (customer goals, promised features, red flags)
  • Make handoff form mandatory (CRM validation rule: can't close deal without completing form)
  • Set SLA: CS must schedule kickoff call within 3 business days of contract signature

Week 13-16: Team Training & Enablement

Goal: Train all GTM teams on new processes, tools, and KPIs.

Days 121-180: Optimization (Refinement, Scale)

Week 17-20: Performance Review & Iteration

Goal: Review KPI performance, identify bottlenecks, and refine processes.

• Weekly GTM sync meeting: Review dashboard, deep dive on underperforming metrics, assign action items
• A/B test MQL criteria: Test different lead scoring weights to improve MQL-to-SQL rate
• Refine handoff workflows: Based on feedback, simplify forms or automate additional steps

Week 21-24: Scale & Automation

Goal: Automate remaining manual tasks, scale successful processes across teams.

• Automation rollout:
  • Auto-assign hot leads to Sales reps based on territory (round-robin or lead score-based)
  • Auto-trigger CS check-in email 7 days after kickoff call
  • Auto-flag churn risk when 3+ red flags detected (health score drops, NPS < 6, usage drops 30%)
• Scale successful playbooks:
  • If hot-lead Slack notifications improved response time, implement for warm leads too
  • If Sales-CS handoff form reduced onboarding delays, create similar Marketing-Sales handoff checklist

Week 25-26: Final Review & Future Planning

Goal: Measure 180-day outcomes, celebrate wins, plan next phase.

• KPI comparison: Baseline (Day 1) vs Current (Day 180)
  • MQL-to-SQL rate: 23% → 37% (+61% improvement)
  • Sales cycle: 67 days → 52 days (-22% faster)
  • NRR: 102% → 118% (+16 percentage points)
  • Revenue growth: 22% → 38% YoY (+16 percentage points)
• Celebrate wins: Share results in all-hands meeting, recognize top performers
• Plan next 180 days: Advanced automation (AI-driven lead scoring, predictive churn models), international expansion (multi-region GTM), new product launches

Chapter 10: GTM Implementation Checklist

Use this checklist to track your GTM integration progress. Print it, put it in Notion, or copy it to your project management tool.

Phase 1: Foundation (Days 1-60)

• ☐ Conduct current state analysis (customer journey, tool audit, stakeholder interviews)
• ☐ Baseline all key KPIs (MQL volume, MQL-to-SQL rate, Win Rate, ACV, Sales Cycle, NRR, Churn Rate)
• ☐ Define GTM strategy (ICP, GTM motion, unified KPIs, 180-day goals)
• ☐ Create Data Dictionary (define MQL, SQL, Opportunity, Churn, NRR with source of truth fields)
• ☐ Connect Marketing Automation to CRM (bidirectional sync, test with 10 contacts)
• ☐ Set up Slack notifications for hot leads (200+ points → #sales-leads channel)
• ☐ Build unified GTM dashboard (CRM or BI tool with Marketing, Sales, CS, Unified KPI views)
• ☐ Define MQL criteria in joint Marketing + Sales workshop (behavioral + firmographic)
• ☐ Test MQL criteria for 30 days and measure MQL-to-SQL rate (target: 30%+)

Phase 2: Execution (Days 61-120)

• ☐ Design Marketing-to-Sales handoff workflow (Slack notification, lead scoring, SLA tracking)
• ☐ Set and track Marketing-Sales SLA (5 min for hot leads, 24h for warm leads, 90%+ compliance)
• ☐ Create Sales-to-CS handoff document template (customer goals, promised features, red flags, go-live date)
• ☐ Make Sales-CS handoff form mandatory (CRM validation rule)
• ☐ Set and track Sales-CS SLA (kickoff call within 3 business days, 100% compliance)
• ☐ Train Marketing team on new processes (MQL definition, lead scoring, handoff workflow)
• ☐ Train Sales team on new processes (hot-lead SLA, handoff document checklist, CRM updates)
• ☐ Train CS team on new processes (handoff document review, churn risk scoring, upsell signals)
• ☐ Conduct all-teams GTM dashboard walkthrough (KPI definitions, how to use dashboard)
• ☐ Launch weekly GTM sync meeting (30-45 min with Marketing, Sales, CS leads)

Phase 3: Optimization (Days 121-180)

• ☐ Review KPI performance weekly in GTM sync meeting (deep dive on one metric per week)
• ☐ A/B test MQL criteria (adjust scoring weights, re-test for 30 days, compare MQL-to-SQL rates)
• ☐ Refine handoff workflows based on team feedback (simplify forms, automate steps)
• ☐ Implement hot-lead auto-assignment (round-robin or lead score-based routing to Sales reps)
• ☐ Implement CS check-in automation (auto-trigger email 7 days after kickoff call)
• ☐ Implement churn risk alerts (auto-flag when 3+ red flags detected, notify CS + Sales)
• ☐ Scale successful playbooks (e.g., warm-lead Slack notifications if hot-lead worked)
• ☐ Conduct final KPI review (compare Day 1 baseline vs Day 180 current state)
• ☐ Celebrate wins publicly (share results in all-hands meeting, recognize top performers)
• ☐ Plan next 180 days (advanced automation, new markets, new products)

Ongoing (Post-180 Days)

• ☐ Maintain weekly GTM sync meeting cadence (30-45 min with Marketing, Sales, CS leads)
• ☐ Review unified GTM dashboard daily (check for anomalies, spike in churn, drop in MQL volume)
• ☐ Conduct quarterly tool audit (remove tools with < 50% adoption, consolidate where possible)
• ☐ Conduct quarterly data audit (RevOps reviews top 10 metrics for definition discrepancies)
• ☐ Update Data Dictionary when adding new metrics or changing definitions (notify all teams)
• ☐ Run annual GTM strategy offsite (review ICP, GTM motion, KPIs, re-align on 12-month goals)

Conclusion: 3 Steps to Start Today

GTM integration is not a one-time project. It's a continuous process of aligning teams, breaking silos, and optimizing for revenue growth.

But you don't need 180 days to see results. Start with these 3 quick wins today:

Step 1: Define Your MQL Criteria (2 hours)

Schedule a 2-hour workshop with Marketing and Sales leadership. Review past 6 months of closed deals. Identify patterns:

• What job titles closed? (VP, Director, Manager?)
• What company sizes closed? (50-200 employees?)
• What behaviors preceded closing? (Pricing page visit? Demo request? Case study download?)

Draft MQL criteria: Firmographic (job title, company size, industry) + Behavioral (2 out of 4 engagement signals).

Expected outcome: By end of day, you have a documented MQL definition that both Marketing and Sales agree on.

Step 2: Set Up Hot-Lead Slack Notifications (30 minutes)

Use Zapier (or native CRM integration) to send Slack notification when a lead hits 200+ points (demo request, pricing page 3x visit, etc.):

1. Create #sales-leads Slack channel
2. Set up Zap: "When lead score ≥ 200 in CRM → Send Slack message to #sales-leads with lead name, company, recent activities"
3. Set Sales SLA: Respond within 5 minutes to hot leads

Expected outcome: Hot leads get instant Sales attention. Response time drops from 2 hours to 5 minutes. Conversion rate improves 15-30%.

Step 3: Create a Unified GTM Dashboard (1 week)

Build a dashboard in your CRM (Salesforce, HubSpot) or BI tool (Looker, Tableau) with 4 views:

• Executive view: Revenue Growth Rate, NRR, CAC Payback Period, Magic Number
• Marketing view: MQL volume, MQL-to-SQL rate, CAC, Marketing Contribution to Pipeline
• Sales view: Pipeline Coverage, Win Rate, ACV, Sales Cycle Length
• CS view: NRR, Gross Churn Rate, NPS, Time to First Value, Expansion Rate

Schedule a weekly 30-minute GTM sync meeting with Marketing, Sales, and CS leads to review the dashboard.

Expected outcome: All teams have visibility into the same KPIs. No more "Marketing says this, Sales says that" discrepancies.

Further reading:

• → Buyer Signal Detection Guide: Detect high-intent leads across Marketing, Sales, CS touchpoints
• → AI Sales Automation Design Philosophy: Automate GTM workflows with AI