Welcome to the era of ‘Profitable Efficient Growth’.

Click here to learn more about PEG

This isn’t about running ChatGPT on top of a broken motion.

It’s about rebuilding your GTM from the ground up: with intent, precision, and AI as your co-pilot.

If you're just chasing reply rates or plugging new tools into old processes, this isn't for you.

But if you're leading a team, building a pipeline engine, or rewriting how your org goes to market — this guide will help.

Introduction

Over the last few weeks, since some of my LinkedIn posts have gone viral, I’ve had some interesting conversations.

From revenue leaders, AE’s, CROs, founders, and revenue operators who are all seeing the same thing happening:

The systems we built from 2015–2021 aren’t built for the way buyers behave in 2025.

In the past 7 days, I’ve had conversations with:

• A $40B global enterprise still running on 1990 systems

• A 10-person startup trying to build its first GTM motion

• A RevOps leader managing 30 reps and 10 tools — none of them talking to each other

• A fractional CRO trying to untangle their client’s CRM while teaching reps to use AI

• An agency fixing broken HubSpot setups that should’ve been sorted years ago

Different logos. Same problem.

Teams are automating outreach before they fix enrichment.
They’re buying AI before defining their ICP.
They’re chasing signals, but ignoring system design.

This newsletter is the product of those conversations.

We’ll break down what top GTM leaders are doing differently and what it actually looks like to build a scalable, signal-driven, AI-powered GTM motion that doesn’t depend on adding more headcount.

Let’s get into it.

Salesforce or HubSpot isn’t where pipeline starts. It’s where it gets recorded.

The best GTM teams today don’t rely on CRM fields to tell them where to go.

They act on upstream signals — hiring trends, content engagement, job postings, LinkedIn data — long before a “lead” ever appears.

• Waiting for MQLs or “interested” leads to show up

• Relying on static Salesforce fields (industry, headcount, lifecycle stage)

• Manually checking LinkedIn for company updates or hiring

• Working a 2-month-old lead list with no signal strength attached

• Sending templated email follow-ups to contacts no longer working in the company

Use ChatGPT and Clay to work outside the CRM:

• Ask GPT:

  “Summarise this company’s last quarterly earnings call. What are their growth goals, hiring priorities, and product focus?”
  

• Use Clay to track:

  • New job postings (e.g. “Director of Revenue Operations”)

  • Tech stack installs (e.g. added HubSpot + Gong)

  • Recent company blog posts, partner marketplace activity, or founder podcast appearances

This gets your reps reaching out with actual relevance — not just timing. Your reps aren’t waiting for a form fill. They’re triggering outreach based on live context.

At Cabot, we’ve built Clay workflows for clients that completely bypass stale CRM data and act on real-world change.

Here’s a use case:

They didn’t touch their CRM once.
The rep just saw the Slack ping and with the data.

This is the infrastructure behind profitable growth in 2025.

The “spray and pray” days are done.
Buyers are flooded with automation. Sequences without relevance get ignored.

It’s not that outbound stopped working — it’s that your current motion is built on static lists, weak signals, and generic copy.

• Download a list of 1,000 accounts that “match ICP” based on industry & employee count

• Write a semi-custom sequence: {first_name}, saw you’re hiring

• Blast it out and hope something sticks

• No signal → no timing → no reply

Use GPT + Clay to build signal-driven sequences without code:

• GPT prompt to create messaging:

“Act as a senior AE selling to fintech companies expanding into EMEA. Based on this LinkedIn post and this job ad, draft 5 different first-line email referencing their stated goals that I can review.”

• Clay can surface:

  • New VP hires in revenue-related roles

  • Job posts with keywords like “expansion,” “retention,” or “revamp”

  • Google News alerts for funding events

Start small: pick 10–20 accounts, pull 2–3 strong signals, and write 1 personalised message per day.

Outbound becomes smarter already.

Here’s what Cabot builds for GTM teams that want precision at scale.

Here’s a use case:

Now they know what signal → led to what reply → led to what meeting.

No spray.

Just outbound that actually earns attention.

Generic outreach doesn't cut it and we’re now getting to a stage where generic personalisation doesn’t cut it. Effective outreach needs to be hyper-relevant, highly personalised, and timely, responding precisely to your prospect's current business context.

• Sending generic messages like "Congrats on funding" or “Congrats on the recent job” without deeper context.

• Manually scanning LinkedIn, press releases, or company news randomly to find insights.

• Maybe have Google News alerts set up and then spend hours taking action.

• Figuring out what company the person used to work at and checking if they’re a customer.

• Time-consuming and rarely effective.

Step-by-step approach:

Step 1:
Use Clay to automatically monitor and scrape LinkedIn posts, company news pages, and press releases for predefined signals such as funding announcements, strategic hires, or expansion plans.

Step 2:
Set Clay workflows to flag these signals in real-time and automatically generate tasks or notifications prompting timely outreach.

Step 3:
Leverage AI (Gemini or ChatGPT) integrated with Clay to instantly draft personalised outreach messages referencing these triggers.

Step 4:
Review and refine the AI-generated message before sending.

Step 1 (Deep Automation with Clay):
Configure Clay to automatically monitor multiple news sources (Crunchbase, LinkedIn, company blogs, Google News APIs) for deeper, multi-dimensional insights on a daily schedule.

Step 2 (Advanced Integration):
Use Make.com or Zapier integrations to push these signals instantly into your CRM, Slack or a database, adding detailed context and automatically segmenting based on triggers (e.g., funding rounds, new executives, geographical expansion).

Step 3 (Real-Time Personalisation at Scale):
Trigger Clay and AI to proactively generate entire sequences of highly targeted outreach messages—each precisely tailored to the unique context Clay identified.

This transforms outreach from generic and reactive to strategically personalised, automated, and always timely, significantly increasing engagement and conversion.

Account planning shouldn’t live in a static deck or be revisited once a quarter. In 2025, great reps use real-time signals to build dynamic, living account plans.

• Using slide decks or Excel to map out accounts once a quarter.

• Guessing at stakeholder priorities based on outdated info.

• Siloed research that never makes it back into the workflow.

Step-by-step approach:

Step 1:
Use Clay to centralise all key signals—funding, hiring, tech stack changes, executive movements, job posts, intent data, website updates and score accounts in real-time.

Step 2:
Set up filters or scoring logic (e.g., companies hiring for CX roles, using HubSpot, recently raised Series B) that reflect your ICP. Clay lets you stack these together with zero-code logic.

Step 3:
Visualise and categorise accounts into tiers based on readiness, fit, and engagement. Sync this plan into your CRM or outreach tools to drive next steps.

Example Filters in Clay:

• Companies hiring for Customer Experience or RevOps roles.

• Using Salesforce + Gong in tech stack.

• Recently expanded headcount by 20% in EMEA.

• Posted a job with the term “retention” in the description.

Step 4:
Export your dynamic account plans into a Notion dashboard or Google Sheet (auto-updated via Clay) that you can use for weekly pipeline reviews.

Step 1: Build a Real ICP Scoring Model in Clay
Use Clay's native logic builder to create a scoring model using real-time firmographic and intent data.

Example:

• +20 points if company raised funding in last 6 months

• +10 if they use Salesforce + HubSpot

• +15 if hiring for Ops or CX roles

• +5 if CEO posted on LinkedIn about retention

Clay continuously updates this score based on live data refreshes.

Step 2: Automatically Re-Tier Based on Score Thresholds
Set up a simple tiering rule inside Clay:

• Score >75 = Tier 1 (High intent)

• Score 50–75 = Tier 2 (Warm)

• Score <50 = Tier 3 (Low priority)

Clay updates these tiers in real-time. You can add tags or custom columns to reflect tier status across workflows.

Step 3: Trigger Next Steps Automatically (Using Clay's Native Integrations)
Clay has direct integrations with CRMs like HubSpot and Salesforce. Based on changes in score or tier:

• Automatically create or update CRM records

• Push high-scoring accounts into outbound tools like Smartlead or Instantly

• Generate tasks for AEs to follow up

• Trigger webhook-based workflows for more advanced GTM actions

Following up after a sales call is where deals are won or lost. It’s your chance to demonstrate you listened, understood, and can act fast. But most follow-ups today are too slow, too vague, or just plain lazy.

• Manually writing follow-up emails based on rough notes or memory

• Important points get missed, action items are forgotten

• No system or structure, inconsistent quality and speed

Most AEs today use tools like Gong or Chorus to auto-record and transcribe calls. These tools summarise the conversation, flag objections, and sometimes suggest action items or next steps.

• Transcripts are searchable

• Post-call summaries help frame the conversation

• You still have to manually translate insights into strategic follow-up

It’s better, but it’s still reactive. You’re only working from what was said.

This is how fast the space moves…As I was writing out what you could do with call transcripts with Gong or Otter.ai I.E. downloading the transcript, pasting it into ChatGPT, prompting it to summarise pain points, buying signals, objections, and suggested follow-up copy — this email lands in my inbox (no joke):

Clay just launched a direct integration with Gong.

You can now:

• Pull Gong transcripts directly into Clay tables

• Use AI to extract insights, objections, buying signals, or feature requests

• Automatically trigger workflows based on what was said in the conversation

Step-by-step approach:

Step 1: Clay pulls your Gong calls into a live table.

Step 2: It extracts the transcript and runs an AI summarisation block to generate:

• A short summary of key themes

• Buying signals and objections

• Suggested follow-up copy

Step 3: Clay enriches the account with real-time data:

• New hires

• Tech stack changes

• Recent funding

• Website or product updates

Step 4: Based on the content of the call and the enrichment:

• Create a personalised follow-up email

• Push that into your CRM

• Alert a rep in Slack

• Trigger a task if a new stakeholder or competitor is mentioned

Example Use Cases:

• Competitor mentioned → auto-draft battle card follow-up

• Feature requested → alert product team in Slack

• New stakeholder referenced → enrich their LinkedIn + CRM record automatically

This is no longer theory — it’s live.

You can now turn Gong conversations directly into personalised GTM workflows.

That’s how I’d do it today.

Everyone is going to be in a different situation and circumstances.

“But, my company won’t let me…”

“We’re not allowed…”

There is a way around everything if you really want to do something, so do it.

If you’re an AE trying to keep up, steal the workflows. If you lead a sales team and want to implement this across the board, let’s talk. And if your team’s still talking about ‘personalisation’ while sending the same template to 500 leads — send them this.

Click here to learn more about PEG and how we can implement these systems and processes into your GTM strategy.

Stephen Bates

Founder - cabot-insights.com