000%

Govind
Sharma

GTM engineering with a closer's instinct

six years carrying a bag. now building the systems.

0+
cold calls
0+
emails + dms
$0M+
deal value
$0M+
pipeline sourced

across saas and real estate · 2017 to present

live signal

Every case study on this site is about finding signal in noise. This one's yours.

LOCATION--
LOCAL TIME--
SOURCE--
DEVICE--
DWELL00:00
SCROLL0%
SIGNALS0 detected
SCORETIER 3, monitor

Runs entirely in your browser. Nothing is stored, nothing is sent.

Every idea becomes a system. Every system closes a deal. Every deal funds the next idea.

about

Six years carrying a bag taught me where deals actually come from. Now I build the systems that find them.

Software engineering sits at 2 on purpose. Knowing where my edge ends is the skill. I direct the person who writes the code, I don't pretend to be them.

I create commercial grade content: brand assets, films, and the creative that drives inbound.

signal
clayBold. We both know that's not true.
zoominfo
n8n
demandbase
claude code
g2
codex
apollo
openmart
revenue
salesforceSix years say otherwise.
outreach
hubspot
salesloft
sales navigator
instantly
smartlead
creative
davinci resolveI've graded more footage than most GTM engineers have opened tables.
capcut
lightroom
not this
pythonNo. I'd direct someone who does.
apexNo. Knowing that is the skill.
soqlNo. Ask the person I'd hire.
lookerNo. I'd read the dashboard, not build it.
blenderAbsolutely not.
case studies 01 / case study

Building the GTM Engine for Ask Arthur

An AI voice agent for restaurants needed to know exactly who to sell to and how, not just that everyone with a phone was a prospect.

impact / results
Scored, segmented TAMcuts hours of research before a rep dials
3 buyer motionsright pitch per buyer type, lifts reply rates
Turnkey handoffteam runs it without me, no ongoing cost
list→ disqualify→ score→ segment→ outbound
clayclaygentfoursquare places apifind jobsclay sequencer
read the full build → 02 / case study

Signal Based Account Prioritization for Procore Sales Reps

Replaced gut feel account prioritization with a live signal engine that tells reps who to call first and why, then automates the alert straight to Slack.

impact / results
An hour of research to a Slack pingwith the reasoning already attached
Lifts win ratesreps work accounts already showing buying intent
One engine, both booksnew prospects and existing accounts, no rebuild
filter→ enrich→ signals→ tier→ slack alert
clayclaygentfind jobsslackmeta prompting
read the full build → 03 / case study

Signal Scored Account Prioritization for GTM Agencies

Built a live scoring system that reads funding, hiring, and product signals to tell reps exactly which accounts are in a buying window right now.

impact / results
Cuts prioritization timea ranked queue replaces a flat, random order list
Lifts reply ratesopeners grounded in what a company shipped last week
Fewer touches to bookaccounts hit inside a real buying window
filter→ score signals→ weight→ tier→ outreach
clayclaygentfind jobsmeta prompting
read the full build → 04 / case study

Turning Event Sponsorship From a Guess Into a Signal

Replaced gut feel sponsorship decisions with a system that shows exactly where target accounts cluster and validates it against real event activity.

impact / results
Protects sponsorship spendmarkets picked on where accounts cluster, not gut feel
Days of research to one querylive event data, self refreshing on every run
Reusable across bookssame build runs on prospects or existing customers
find accounts→ enrich leaders→ match events→ cluster→ decide
clayticketmaster apihttp api functions
read the full build →
contact govindpunjsharma@gmail.com
bygovind.com linkedin