GTM Systems · Vertical AI · Enterprise B2B SaaS

We ran the GTM. The revenue followed.

Across vertical AI and enterprise SaaS, we rebuilt GTM systems from the ground up -- ICP, category narrative, partner motion, sales playbook -- and watched deal velocity improve. This is what that looked like.

Start a Conversation See the Work
2x
ACV in under 3 months with pricing and packaging reset around economic buyers
65%
Improvement in qualified leads by repositioning a $400M+ complex multi-product portfolio
3x
Growth in partner influenced revenue by relying on strategic sales plays rather than relationships
What We Ran

Four problems that kept showing up.
Four systems we built to fix them.

Most GTM failures are a combination of targeting failures, narrative failures, motion failures. We ran the diagnosis, made the call, and built the system.

01

Defined a wedge that actually lands

Strong products often struggle to enter new markets because the entry point is unclear. We defined a narrow, credible use case, aligned it to how buyers evaluate solutions, and created a path to initial adoption.

ResultShorter cycles, higher win rates in the prioritized segment
02

Sharpened the category and narrative

When positioning is unclear, sales cycles stretch and teams improvise. We clarified the category, tightened the core narrative, and made value defensible in enterprise conversations.

ResultFaster qualification, fewer stalled discovery calls
03

Aligned GTM to how enterprise deals actually work

Deals stall when GTM is not aligned to buying dynamics. We aligned messaging to the economic buyer, connected ABM to deal qualification, and improved how opportunities progress.

ResultPipeline quality improved, ACV expanded, win rates moved
04

Designed a scalable route to market

Growth slows when targeting and execution are not aligned. We refined ICP and segmentation, prioritized outbound, and connected inbound and outbound into a single coordinated motion.

ResultPredictable pipeline, efficient coverage, no headcount increase
Case Studies

The call that was made. What changed.

Four engagements across different markets and problems. Each started with a clear diagnosis and a decision -- not a discovery workshop.

Case 01
US Market Entry
Insurance AI Platform
"An insurance AI platform with traction in Asia and Europe needed to prioritize the strongest entry motion for US expansion."
What Changed
  • Analyzed pipeline patterns across use cases such as claims and underwriting.
  • Compared US and similar EU deals for buyer patterns.
  • Identified the best entry point for US growth.
Commercial Impact
Clearer US entry focus and a more disciplined view of where sales and marketing resources should concentrate.
Case 02
Scaling Growth Without Increasing Costs
Construction Tech AI
"A construction tech AI company needed to scale growth efficiently without a proportional increase in sales and marketing spend."
What Changed
  • Analyzed recent deals to refine ICP in the contractor segment.
  • Narrowed a broad account universe into a prioritized target list.
  • Created a repeatable outbound motion with personas, entry messages, and weekly cadence.
  • Established tracking for early signs of improving pipeline quality.
Commercial Impact
Sharper ICP and account prioritization helped align paid media and sales targeting around the same growth motion.
Case 03
Clarifying Category Narrative
Workforce Analytics Platform
"A workforce analytics platform needed to shift the buyer conversation from activity tracking to operational intelligence and service delivery performance."
What Changed
  • Analyzed website, case studies, and sales conversations to identify narrative friction.
  • Reframed the category around operational intelligence for service delivery.
  • Built guidance for privacy, culture, and change-management concerns.
  • Created SDR messaging and discovery questions for US buyers.
Commercial Impact
Clearer category narrative, repeatable sales story, and tools to address buyer concerns earlier in the cycle.
Case 04
Aligning ABM and MEDDPICC
Enterprise SaaS - Data Governance / CRM Data Control
"Early qualification signals were inconsistent, and pipeline coverage varied across target segments. ABM needed to connect directly to deal qualification and stage progression."
What Changed
  • Aligned ABM targeting and early qualification on the same firmographic and technographic signals.
  • Built account briefs with economic buyer, competitive positioning, stakeholder map, and 30-day messaging cadence.
  • Mapped ABM assets into MEDDPICC stages, including account intelligence, ROI and competitive proof, executive references, and compliance docs.
  • Built a deal support kit with CIO and VP Data wedge narratives, ROI frameworks, competitive positioning, and executive decks.
Commercial Impact
Pipeline quality and coverage discipline improved, with stronger buyer-stage alignment across the enterprise motion.
How an Engagement Works

Diagnosis first. No retainer before we know the problem.

Most engagements start with a structured diagnostic -- not a proposal. We identify the misalignment, present the diagnosis, and then scope what it takes to fix it.

01

GTM Diagnostic

We run a structured assessment across your ICP, positioning, motion, and pipeline data. You get a clear view of where the system is broken and why -- before any work is scoped.

02

The Diagnosis Call

We present what we found, make the call on priority, and recommend a scope. You decide what to fix first. No deliverable decks -- just a clear decision framework.

03

System Build

We run the work: ICP refinement, narrative rebuild, account scoring, playbook, partner motion. Engagements are scoped by outcome, not by hours. You get a system that runs without us.

GTM Friction Audit

A commercial diagnosis of your GTM narrative -- not a copy review.

Find out whether your GTM friction is a messaging problem or a structural issue before you spend more on campaigns, hiring, or a website overhaul.

Fixed Price
$2,450
Delivery
14 days

Who This Is For

  • Generating pipeline but losing deals earlier than expected
  • Preparing for a US market push and pressure-testing narrative before scaling spend
  • Seeing content and campaign activity without enough conversion
  • Suspecting the problem is upstream of sales execution
Request the Audit
ICP Clarity
Is there a defined, prioritized ideal customer?
Value Proposition
Does the core claim hold across content?
Use Case Specificity
Are the strongest wedge use cases visible?
Proof Point Strength
Does the proof match the category claim?
Route-to-Market Fit
Does the motion match the buyer and segment?
Narrative Consistency
Does the story hold across the content set?
  1. 01
    Intake
    Submit your website URL and up to 4 external assets -- blogs, customer deck, white papers, case studies.
  2. 02
    Signal Analysis
    External GTM signals reviewed across six dimensions before the call.
  3. 03
    Discovery Call
    60 minutes with your CEO, CRO, CMO, or VP Sales to pressure-test the hypothesis.
  4. 04
    Report + Walkthrough
    Structured findings with severity rating and prioritized next steps sequenced by commercial impact.

Why the severity rating matters. A messaging problem needs sharper narrative. A structural problem means something bigger is off: wrong ICP, weak wedge, route-to-market mismatch, or a category claim without proof. Better copy will not fix a structural GTM problem. This audit tells you which one you have before you commit more budget.

Insights

From The GTM Operator

Published on Substack. Written for founders and GTM leaders who have traction and are trying to figure out what's blocking scale.

Category Design
FDEs Should Not Just Deploy AI -- They Should Define and Defend the Category
The implementation role is a category-defining moment. Most companies let it pass. Here is what it looks like when they don't.
Read on Substack →
AI and GTM
Where AI Actually Helped My Enterprise GTM Work
Not a list of tools. A specific account of where AI moved the work forward and where it didn't -- in real GTM engagements.
Read on Substack →
Modernization
AI Won't Fix a Bad Mainframe Modernization Strategy
AI changed the mainframe modernization conversation, and not entirely for the better. The hard part was never the code.
Read on Substack →
Vertical AI
Vertical AI GTM: The Implementation Gap That Stalls Deals
Most vertical AI deals stall after the demo. The problem is rarely the product. Here is what the implementation gap looks like and how to close it.
Read on Substack →
About
Mac Gupta, Founder of Precision GTM
Mac Gupta Founder, Precision GTM

Mac Gupta

I started out as a software engineer and kept getting pulled into go-to-market decisions. Eventually I stopped resisting and ran them full time. That was 20 years ago. Since then I have worked across product marketing, partner GTM, and sales enablement at companies like IBM, Software AG, Pitney Bowes, WealthEngine and Rocket Software -- most of them complex, multi-product portfolios selling into enterprise accounts.

What I kept finding was that the GTM system was broken upstream of where people were looking. The product was fine. The team was working hard. But the ICP had drifted, or the narrative wasn't landing with the actual economic buyer, or the partner motion was running on relationships instead of a repeatable play. Precision GTM is built around fixing those things specifically. I have an MBA from Chicago Booth, and a Masters and Bachelors in Computer Science.

See selected work →

Start Here

If you have traction and your GTM isn't converting it -- that's the conversation.

We start with a diagnostic. If there's a fit, we'll tell you what's broken and what we'd build to fix it. No proposal decks, no vague retainer scope.

Request a Diagnostic Read the Substack First