GTM Live: What We Taught 100+ GTM Leaders in Our Invite-Only Workshop (Nov 21, 2025)

Podcast: GTM Live
Hosts: Carolyn Dilks & Amber (Passetto)
Episode Theme: Rethinking GTM Measurement—Unlocking Efficiency with the “GTM Factory” Model

Overview

In this in-depth workshop-converted podcast episode, Carolyn Dilks (CEO, Passetto) and Amber (Head of RevOps, Passetto) deconstruct the outdated approaches dominating B2B SaaS go-to-market (GTM) strategy measurement. Drawing from their real client work and audience feedback, they expose why common funnel models fail and introduce listeners to a “GTM Factory” approach—granting end-to-end visibility, aligning sales and marketing, and centering on what actually moves revenue and unit economics. The episode is full of hands-on advice, live Q&A, and tactical frameworks, positioned squarely at GTM leaders frustrated with mere vanity metrics or superficial attribution.

Key Themes & Discussion Points

1. The Current State of GTM Measurement Is (Still) Broken

• Traditional Attribution Models: Most companies still use some flavor of source-based reporting—the “four funnel” model (Marketing, SDR, AE sourced, etc.) or marketing waterfalls (MQL, SQL, Opportunity, Customer).
  • Quote, Carolyn (06:57): “This tries to narrow it down to one thing and we’re saying, look, it’s usually a systematic, sort of like, factory process that involves more than one thing happening.”
• Why Those Models Fail Today:
  • Attribution often rewards only one team, ignoring the reality of compounded effort.
  • Models are rooted in decades-old thinking, not responsive to long B2B cycles or multi-stakeholder sales.
  • Data produced by traditional reporting creates “smoke and mirrors” and hides inefficiency under vanity metrics.

Memorable Analogy (08:33):
Carolyn compares effective pipeline management to running a precise factory:
“A factory operates with an extreme level of precision and rigor … we need to know exactly what happens at every stage. That’s why I always use the factory analogy.” (08:33)

2. Audience-Driven Pain Points

Live feedback sourced from workshop and email pre-surveys:

• Flat new ARR
• Poor alignment between marketing and sales
• No clarity on what activities actually generate revenue
• Over-reliance on legacy metrics (MQL obsession)
• Difficulty business-casing for metric change

Live Chat Reflection:
Amber notes, “It’s been great to hear feedback from the community… it really is what fuels us knowing these are takeaways you can learn from, and we all learn from each other.” (03:21)

3. Dissecting the “Four Funnel” and “Waterfall” Models

• What These Look Like (Actual Salesforce & HubSpot Screenshares):
  • Source-based pipeline reporting (Marketing, SDR, AE)
  • Waterfall: Volume at each stage (Visitors, Prospects, MQL, SQL, Won)
• The Core Issues:
  • Don't show why conversion is low (e.g., 2% MQL→Pipeline)
  • Obscure inefficiencies; only “storytell” up to the board
  • Require complex, manual reporting gymnastics

Carolyn’s Candid Callout (15:01): “I see some of the smartest CMOs, the smartest CROs… when I see the quality of the data they put in front of their board, I’m astounded that that is considered acceptable because it doesn’t tell us anything. And I was one of those people…” (15:01)

4. Enter The “GTM Factory” Model

Core Principles:

• Treat GTM like a factory: Track every stage, every touch, with discipline.
• Expand beyond “Source”: Focus on engagement, prospecting, and closing—not just who “created” the opp.
• Measuring both marketing and sales as parallel, compounding forces—not isolated silos.

Memorable Quote (17:45):
“We want to see the causal chain of events, or things that happen—linear or not—that happen from that very first moment to the end of the journey in one stitched-together view. And that is possible. Everybody can do it. There’s a framework. There’s no secret sauce.” (22:25)

Breakdown of the Three Core Stages:

1. Engage Stage:

   • First captured signal—website visit, form fill, event, etc.—until the moment sales (SDR/AE) picks up lead.
   • Measure: Signal Type, Channel, Source, Time Elapsed.

2. Prospecting Stage:

   • From the point sales starts working the contact to either opportunity creation or disqualification.
   • Most-neglected stage across all GTM organizations.
   • Track every sales attempt, triggers (e.g., what caused the SDR to pick up the lead), multi-contact efforts within an account.

3. Closing Stage:

   • Opportunity creation through to close (won/lost), all sales and marketing touches.
   • Crucial: Associate every contact to opps to maintain data integrity.

Amber on Structure vs. Status Quo (38:48):
“You want to think about this as a box that’s going down a production line. Every single time the prospecting cycle starts, you have a package that’s on the prospecting production line, and it’s getting stamped with all these details, at that moment in time.”

5. Practical Data Model & Implementation Advice

Essential Data Sources & Tools:

• Marketing Automation (HubSpot, Marketo, Pardot)
• CRM (Salesforce, HubSpot CRM)
• Sales Engagement (Outreach, SalesLoft)
• Event Platforms (Cvent)
  Special Callouts:
• Need rigorous channel/UTM tracking
• Custom objects may be required in Salesforce to fully track prospecting cycles

Data Points To Track Per Stage:

• For ENGAGE: Web visits, forms, chatbots, event signup, channel attribution (with UTMs)
• For PROSPECTING:
  • Trigger event (hand-raiser, SDR outreach, intent data, etc.)
  • Activities and signals observed while being worked
  • Disqualifications and reasons
  • Multiple “prospecting cycles” per contact/opportunity (“It takes 7 attempts across 6 months on average for many clients,” Carolyn, 39:38)
• For CLOSING:
  • Opportunity amount, type, contacts attached, activities and marketing signals during pipeline

Contact–Opportunity Mapping is Critical

“Classic flaw that most companies have… the thread that stitches the whole journey together is your ability to know what’s happening at the contact level.” (35:41)

6. Q&A and Nuance in Implementation

Sample Questions Addressed:

• “How do you track dark funnel signals?”
  Amber: “If you can track it, you can pull it in as a signal… some of the dark funnel’s still dark. But if you could track it, you could pull it in.” (26:44)
• “Should a meeting auto-create an opportunity?”
  Carolyn: “Definitely not… an opportunity object is not meant to capture something that maybe isn’t qualified yet.” (28:03)
• “How do you prospect into multi-contact accounts?”
  Amber/Carolyn: “It’s typical, especially higher ACV—track lifecycle per contact; an opportunity may have 5 or 6 prospecting cycles attached.” (29:37)
• “What about Salesforce’s limitations?”
  Add custom objects if needed—possible in all common CRMs.

Notable QA Quote (Amber, 28:46):
“Breaking out your prospecting cycle separately opens up a lot more granularity and visibility and strategies for you here.”

7. Measurement Ecosystem: What’s Possible With Better Data

• Prospecting Analytics: Table-stakes data, essential for performance/efficiency, lives natively in CRM with right config.
• Signal Analytics: Quantifies first-party interactions—what marketing activities actually drive movement at each stage.
• Engagement Diagnostics (Advanced): Behavioral analysis—quantity/timing/depth of engagement by stage, what’s typical of closed-won versus closed-lost.

Key Takeaway (44:16):
“This quantifies the stuff that we are doing in marketing—what is likely to have the greatest impact on pipeline and revenue, what is not… We commonly see things that companies spend a lot of money on that really don’t show up at all. We want to isolate that, stop doing these things because they’re not having an impact.”

Notable Quotes & Memorable Moments

| Timestamp | Speaker | Quote | |---|---|---| | 06:57 | Carolyn | “This tries to narrow it down to one thing and we’re saying, look, it’s usually a systematic, sort of like, factory process that involves more than one thing happening.” | | 08:33 | Carolyn | “A factory operates with an extreme level of precision and rigor … we need to know exactly what happens at every stage. That’s why I always use the factory analogy.” | | 15:01 | Carolyn | “I see some of the smartest CMOs, the smartest CROs… when I see the quality of the data they put in front of their board, I’m astounded that that is considered acceptable because it doesn’t tell us anything. And I was one of those people…” | | 22:25 | Carolyn | “We want to see the causal chain of events, or things that happen—linear or not—that happen from that very first moment to the end of the journey in one stitched-together view. And that is possible. Everybody can do it. There’s a framework. There’s no secret sauce.” | | 28:03 | Carolyn | “Definitely not… an opportunity object is not meant to capture something that maybe isn’t qualified yet.” | | 29:37 | Carolyn | “An opportunity might actually have five or six prospecting cycles attached to it… prospecting to somebody is often complex.” | | 38:48 | Amber | “You want to think about this as a box that’s going down a production line. Every single time the prospecting cycle starts, you have a package that’s on the prospecting production line, and it’s getting stamped with all these details, at that moment in time.” | | 44:16 | Carolyn | “This quantifies the stuff that we are doing in marketing—what is likely to have the greatest impact on pipeline and revenue, what is not…” |

Timestamps for Major Segments

• 00:00–06:03: Host intros, context for the session, community-driven pain points
• 06:03–13:06: Breakdown of traditional four funnel and waterfall models
• 13:06–19:29: Problems with legacy reporting; board-level reporting’s shortcomings
• 19:29–26:44: Introduction to the GTM Factory Model; end-to-end pipeline tracking
• 26:44–32:00: Rapid-fire Q&A—dark funnel, opportunity qualification, target accounts, CRM limitations
• 32:00–39:38: Step-by-step GTM factory data model—engage, prospecting, closing stages, required sources
• 39:38–44:16: Prospecting complexity, measurement ecosystem, advanced analytics

Summary Takeaways

• The “source-based” playbook is dead weight; dissect your GTM like a factory for granular insights at every stage.
• Prospecting is the black hole—build structure there first: multiple contacts, cycles, triggers, and true touch attribution.
• Assign contacts to every opp—never lose the thread from first signal to closed deal.
• Use signal analytics to eliminate wasted marketing and sales spend, focusing only on measurable, repeatable impact.
• You don’t need fancy software—just set up the right objects and tracking in CRM, or use BI tools for advanced analysis.
• Expect resistance; be prepared to business-case for these data-centric changes.

For further frameworks, live examples, and to register for future practical workshops, the hosts recommend checking passetto.com/events.

Podcast Tone: Direct, practical, no-nonsense, focused on real value rather than theory or fluff—mirroring the “cut through the noise, no vanity metrics” ethos repeated by the hosts throughout.