RevOps & GTM automation

Your revenue system leaks where your tools meet.

Every tool in your stack works. The handoffs between them don't — so people become the integration layer. I find where that's costing you most, then build the smallest system that stops it.

For B2B SaaS teams and growth agencies · Remote · US · UK · AU · IN
REVENUE PIPELINE — TYPICAL STATE ▲ 3 MANUAL BREAKS
CAPTURE ENRICH QUALIFY ROUTE ENGAGE REPORT 01 02 03
01

Research by handSomeone opens LinkedIn and the company site to decide if a lead is worth working.

02

Assignment by SlackOwnership is decided in a thread, not a rule. Leads sit while people are asleep.

03

Reports rebuilt weeklySomeone exports, pivots, and pastes the same numbers into the same deck.

Works in HubSpot Salesforce Make n8n Zapier Clay Airtable Claude
What's breaking

Four problems that knock over everything downstream.

These aren't independent. Each one causes the next. Fix them in the wrong order and you spend budget without moving a number.

Leads go cold before anyone touches them

A form fills at 11pm. It's enriched by hand the next morning, assigned after standup, and worked in the afternoon. The buyer has already booked with whoever replied first.

Knocks over
  • Conversion rate drops, so CAC rises
  • Paid budget is judged on a broken funnel
  • Reps blame marketing for lead quality

Nobody fully trusts the CRM

Duplicate accounts, blank fields, stages that mean different things to different reps. So people keep private spreadsheets, and the real pipeline lives outside the system of record.

Knocks over
  • Forecast becomes an opinion, not a number
  • Automation built on this data misfires
  • Every meeting starts by debating whose report is right

Your closers are doing data entry

Call notes, field updates, follow-up scheduling, list building. An hour here, an hour there — until the person you hired to sell is spending half their week not selling.

Knocks over
  • Effective headcount is far below actual headcount
  • Good reps leave; admin isn't the job they took
  • You hire to fix capacity you already paid for

No single source of truth across teams

Marketing reports one number, sales another, finance a third. Each is defended, none reconcile, and the discrepancy is rediscovered every quarter.

Knocks over
  • Decisions get made on the loudest number
  • Board and investor reporting becomes stressful
  • Nobody can prove what actually worked

And underneath, the constant friction

None of these will sink you on their own. Together they eat a day a week, every week, and nobody logs the hours.

Building lists by hand
Copy-pasting call notes
Chasing status updates
Merging duplicate records
Manual handoffs to onboarding
Re-writing the same outreach
Checking ad spend too late
Rebuilding the weekly deck
Fixing broken Zaps nobody owns
Why it keeps happening

The problems above are symptoms. These are the causes.

Treat the symptoms and they return in a new form within two quarters. This is what actually has to change.

CAUSE 01

The stack was bought, never designed

Each tool was added to solve one urgent problem — a CRM here, an enrichment tool there, a scheduler, a dashboard. Every tool works. Nobody ever designed how work moves between them, so the seams became human. Your team is the integration layer.

CAUSE 02

Process lives in people's heads

How a lead gets qualified, who owns what, when a deal moves stage — it's known, not written, and definitely not encoded. That works until someone is on leave, until you hire, until volume doubles. Then it doesn't.

CAUSE 03

Nobody owns the whole pipe

Marketing owns the top, sales the middle, customer success the end. Each optimises their section. The losses happen at the boundaries, which is exactly where nobody's targets are measured — so the leaks stay invisible and unfunded.

CAUSE 04

Automation was attempted tool-first

The step that's easiest to automate gets automated. Not the step that's costing the most. You end up with a dozen small workflows that save minutes each, while the expensive break sits untouched because it's harder to reach.

CAUSE 05

Nothing was measured before it was changed

Without a baseline, improvement is invisible. You can't prove the automation worked, so it never gets extended, and the next budget conversation starts from zero. Measurement isn't reporting overhead — it's what makes the work defensible.

If nothing changes

The cost compounds quietly, and never appears as a line item.

None of this shows up in a P&L as "revenue operations debt." It shows up as targets missed for reasons nobody can quite name.

Revenue leaks you never see

Lost deals don't get logged as "we replied too late." They get logged as lost to a competitor, or not logged at all.

A forecast you can't defend

When the underlying data is soft, every number you present is one question away from falling apart in the room.

Scaling multiplies the mess

Hiring into an undesigned process doesn't fix it. It adds people whose job is to absorb the friction manually.

Your best people leave

Strong operators and closers don't stay in roles that are 50% admin. The ones who tolerate it usually aren't the ones you want to keep.

Spend optimised against bad data

If attribution is broken, you scale the channel that reports well rather than the one that actually converts.

The founder becomes the bottleneck

When the process isn't encoded, the person who remembers how it works gets pulled into every exception. That's usually you.

Before we talk solutions

What most teams try first — and why it doesn't hold.

These are reasonable instincts. They're also the reason the same problems come back next quarter.

Common belief

"We need more leads."

What's usually true

You're losing a meaningful share of the leads you already pay for — to delay, bad routing, and follow-up that never happened. More volume into a leaking pipe raises spend, not revenue.

Common belief

"AI will sort this out."

What's usually true

AI applied to an undefined process automates the mess faster and with more confidence. The model isn't the hard part — deciding what should happen, and when, is.

Common belief

"We'll clean up the CRM later."

What's usually true

Data rot compounds. Every week of delay adds records to fix and decisions made on bad numbers. "Later" arrives as a migration project nobody has time for.

Common belief

"We're too small for RevOps."

What's usually true

Small teams pay the highest tax per person, because the manual work is spread across people who have no slack. The cost is real; it's just distributed enough to stay invisible.

Common belief

"We just need the right tool."

What's usually true

Adding a tool adds two more seams. Tools are rarely the constraint — the undesigned flow between them is. New software on top of that makes the diagram more complicated, not the work less manual.

Common belief

"We'll hire an ops person to own it."

What's usually true

That hire inherits an undesigned system with no documentation. Without a redesign first, you've hired a very expensive human API — and created a single point of failure.

The everyday versions of the same mistake

Automating before auditing. Building the workflow that's obvious rather than the one that's expensive.

Measuring activity instead of outcomes. Counting emails sent tells you nothing about whether the pipe is leaking.

Undocumented automations. They break silently, months later, and nobody knows they were ever running.

One person holding every workflow. When they leave, the system leaves with them.

No baseline before "improving." If you didn't measure it first, you can't prove it worked or justify doing more.

Copying someone else's stack. Their constraints aren't yours. A template built for a 200-person team breaks a 15-person one.

The method

Diagnose first. Then fix the cause, not the symptom.

I don't sell automations. I find where your revenue system is losing the most, and build the smallest thing that stops it.

That means the first engagement is diagnostic, the recommendation might be "don't automate this yet," and nothing gets built until we both know what it's worth. When the root cause is fixed, most of the symptoms above resolve without being addressed individually — which is the point.

Diagnosis before prescription

Every engagement starts by mapping how work actually moves through your stack — not how the org chart says it should. The expensive break is usually not the one people complain about.

Built for your constraints

Your team size, your tools, your budget, your data quality, who'll own it after I leave. No templates. A system your team can't maintain is a liability, not an asset.

Measured, or it didn't happen

Baseline before the build, measurement after. You get a number you can defend, and a clear basis for deciding what to do next.

How an engagement runs

Six stages. The order is the method.

Building before diagnosing is how teams end up with automations that solve the wrong problem elegantly.

STAGE 01 Days 1–3

Map

Every tool, every handoff, every place a human moves data between systems. Short interviews with the people actually doing the work — because the documented process and the real one are rarely the same.

You get
  • Full stack and data-flow map
  • Every manual handoff, listed
  • Where the process differs from the documentation
STAGE 02 Days 3–5

Quantify

Put hours and money against each break. How long does this take, how often, done by whom, at what cost. This is the baseline — without it, nothing that follows can be proven.

You get
  • Cost per break, in hours and currency
  • Baseline metrics, recorded
  • Ranked list by cost, not by ease
STAGE 03 Week 1

Prioritise

Which single fix knocks over the most downstream problems. Sequenced against your real constraints — team capacity, data quality, budget, and what has to keep running while we work.

You get
  • A written roadmap, sequenced
  • What to fix now, next, and never
  • Honest scope: what isn't worth automating
STAGE 04 Weeks 2–3

Build

Built in your environment, not a sandbox. Failure modes handled deliberately — expired credentials, rate limits, empty states, bad input. An automation that works only on the happy path is a future incident.

You get
  • The working system, live
  • Error handling and alerting
  • An audit trail of what it did
STAGE 05 End of build

Hand over

Your team has to be able to change it without me. Written documentation, a recorded walkthrough, and a live training session with whoever will own it day to day.

You get
  • Documentation: what it does, how to change it
  • Recorded walkthrough
  • Training session and a defined support window
STAGE 06 Ongoing

Operate

Optional. Systems drift as your process changes — new fields, new stages, new tools. A retainer keeps things monitored and extends the system as the business moves.

You get
  • Monitoring and fixes
  • New automations as needs emerge
  • Results measured against the baseline
What gets built

The systems that usually come out of this.

Each one replaces something a person on your team is doing by hand, on a schedule, right now.

Speed to lead

Routing & enrichment

A form fires. The lead is enriched, scored, assigned by rule, and logged — before anyone opens their inbox. Nights and weekends included.

Data integrity

CRM hygiene agent

Dedupes, normalises, fills gaps and flags rot on a schedule — so the number you take to a board meeting is one you can defend.

Rep capacity

Call transcript → CRM

Transcripts become structured notes, updated fields, and next steps, written back automatically. No post-call admin.

Visibility

Pipeline & spend digests

Weekly pipeline summaries and ad-spend anomaly alerts, assembled and delivered without anyone rebuilding a deck.

Background

I came to automation from GTM, not from software.

I'm an independent consultant providing revenue operations and go-to-market automation services internationally — primarily to B2B SaaS companies and marketing and growth agencies.

The work is auditing GTM and CRM systems, designing and building AI-powered workflow automation, and advising teams on adopting AI agents and no-code tooling to remove manual operational work.

Before automation, my background was paid media, revenue operations, and go-to-market strategy. That's the relevant part: I've owned the funnel metrics and defended them to stakeholders. The systems I build are shaped around how a pipeline behaves commercially, not just what a workflow tool can technically do.

FOCUSRevOps & GTM automation
CLIENTSB2B SaaS, agencies
DELIVERYRemote · project or retainer
MARKETSUS · UK · AU · India
BASEDMumbai, India
Engagement models

Three ways to start.

Fixed scope, 50% upfront. Most engagements begin with an audit, then move to a build and a retainer.

Start here

GTM Stack Audit

From $500 · 1 week

Stages 01–03. Your stack mapped, every manual break costed, and a sequenced roadmap — with a walkthrough. Stands alone; you can take it and build in-house.

Start an audit
Ongoing

Monthly Retainer

From $1,500/mo

Stage 06. Monitoring, maintenance, and new automations as your process changes. Available after a sprint, not before.

Discuss a retainer
Proof of work

Case studies, as engagements close.

First engagements are currently underway. Walkthroughs and results will be published here as they're delivered — measured against the baseline, with real numbers rather than projections. If you'd like to see a system in progress before then, ask on a call.

Start with the diagnosis.

Thirty minutes. I'll ask how a lead moves through your business and where people are filling gaps by hand. If there's nothing worth fixing, I'll tell you that.