r/gtmengineering

was gonna make it give "constructive feedback." it does not do that. it just cooks every email you feed it. tried to soften it and gave up, it's funnier this way.

paste your cold email → roast + score + a rewrite that's actually better. made with claude, free, no signup.

cold-email-roaster-final.vercel.app

post your score, curious if anyone can beat it. errors = rate limit, just retry.

Want to start gtm automation agency. Is it dead?

I think most outbound fails because we're looking for ICPs instead of buying signals.

For years I did what everyone else does.

Define the ICP.

Buy a list.

Enrich it.

Write a personalized email.

Hope someone replies.

The problem wasn't the email.

The problem was I had no evidence that any of those companies actually needed what I was selling.

Recently I came across hundreds of GTM playbooks built around something completely different.

Instead of asking, "Who fits our ICP?"

They ask, "What public signal proves this company has a problem today?"

That completely changed how I think about prospecting.

One example was using FDA warning letters to identify companies with documented compliance issues. Instead of pitching a service, the outreach offered a free review of the exact issue they were already dealing with.

Another campaign used OSHA citations.

Another tracked ADA lawsuits.

Others looked at building permits, SEC filings, audit findings, hiring patterns, government databases, and even competitor technology footprints.

None of these campaigns started with, "We help companies like yours..."

They started with proof.

It reminded me of going to the dentist.

If a dentist walks up to me on the street and says I need a root canal, I'd ignore them.

If I'm already sitting in the chair because my tooth hurts, I don't need to be convinced I have a problem. I need someone to help me understand it.

That's what good outbound should feel like.

Less convincing.

More diagnosing.

Now I'm trying to build every campaign around publicly available signals instead of demographics.

Curious what everyone else is using.

What are the best public directories, regulatory databases, or overlooked data sources you've found that reliably indicate a company is actually in the market for a solution?

Hey guys I’m a sophomore studying computer science trying to get into gtm engineering. I’m currently working as an SDR intern, and have built a few lead gen workflows using Claude code, codex and other ai tools. I’m working on a project and I wasn’t some harsh but fair advice on the idea. Basically it’s a workflow that scrapes public APIs for new business filings in major metros (along with other signals). I then would connect with commercial service companies (I’m thinking cleaners) and give them X amount of leads that they can connect with so they’re the first person to contact the new business opening every week I’m thinking every Monday. Lmk if it’s a good idea needs some work or just complete trash in completely open to any criticism. Thanks a lot!

Not sure if this is the right place to post this, but I honestly need some advice.

I graduated recently in Mechanical Engineering from NIT Warangal. If someone had asked me a year ago what I'd be doing after graduation, GTM Engineering would've probably been the last answer.

I started off learning data analytics because I enjoyed working with data. I spent months learning SQL, Python, Excel, Power BI, Tableau... hoping I'd get into an analyst role.

Instead, I got an internship as a GTM Engineer at a startup.

I almost didn't apply because I had no idea what GTM Engineering even meant. But I took the chance, and it turned out to be one of the best learning experiences I've had.

I worked on ICP building, cleaning and validating huge datasets, Apollo, Clay, Crunchbase, Serper, a bit of n8n automation, testing different ways of finding companies, figuring out why automations failed, and basically spending hours understanding companies instead of just ticking boxes.

The funny thing is... I actually enjoyed it. I liked solving those problems. I liked that every week I was learning something new.

Now the internship is over, and I'm back to applying.

And honestly... it's been rough.

I wake up, open LinkedIn, apply, send connection requests, ask for referrals, refresh my email, sleep, and repeat the same thing the next day. Some days I feel like I'm making progress. Most days it just feels like I'm shouting into the void.

I'm not someone with 2-3 years of experience. I'm just a fresher who happened to get exposure to a field that I genuinely want to continue in.

I'm looking for GTM Engineering, RevOps, GTM Ops, Sales Ops, Business Ops or even Data/Business Analyst roles. Bangalore, Hyderabad or remote works for me.

If you've been in a similar situation or know companies that hire freshers for these kinds of roles, I'd genuinely appreciate any advice or leads.

Thanks for reading.

Been building outbound systems for B2B clients and this is the pipeline I run end to end. Sharing the whole thing because I'd rather have it torn apart here than in a client's dead campaign. Diagram attached — flow below.

The pipeline:

1. Define ICP — as a testable hypothesis, not a fixed profile. Every attribute is tagged "data" (from real customers) or "guess" (assumption to validate).
2. Deliverability setup, in parallel — separate domains, mailboxes, warmup. Kicked off at the same time as the ICP work because of the ~2–3 week warmup lag.
3. Pull companies matching the ICP → pull contacts at those companies → enrich → verify emails (hard gate — nothing unverified gets sent) → load into a central data store.
4. Draft copy with an LLM — email sequences, LinkedIn scripts, cold-call talk tracks, per segment.
5. Run 3 channels — email sequencer, LinkedIn automation, manual calls to high-intent accounts.
6. Track replies + performance → log to CRM → work the pipeline.
7. Feedback loop: reply data flows back into the ICP, turning "guesses" into "data" for the next campaign.

What I actually want your take on:

• Three channels for a lean operation — overkill? I keep going back and forth on whether cold calling earns its slot or whether I should run email + LinkedIn well instead of three thinly.
• Where do you put enrichment vs. verification? I verify after enrich, before the DB. Some people verify twice. Curious what breaks for you at scale.
• The feedback loop is the weakest part of my setup. In practice it's manual — I eyeball reply data and adjust. How are you closing that loop without it turning into a full-time analysis job?

What does your flow have that mine doesn't? Genuinely trying to find the step I'm missing before a client does.

European based GTME with focus on building complex systems (not boring list building and outbound campaigns management) is looking for interesting projects.

Background:
- 3 years of experience in GTME space (have started right with the first wave of Clay hype)
- Over 6 years in lead gen/sales/sdr (when it was boring stuff with manual researching and copyrighting. Do you remember that times?)
- Have deep knowledge of various tools and services including: Claude code, Codex, n8n, Zapier, Make, Hubpost, Attio, TwentyCRM
- Have built waterfall enrichments, signals systems, AI agents, speed to lead, inbound lead sorting
- Experienced in implementing Automations, building internal portals, etc
- Worked in large projects in sales/outbound/data SaaS space (Heyreach, Apollo, Zoominfo competitors)

If you are interested, DM or comment.

I have been seeing GTM Engineering everywhere lately and I'm trying to figure out if my background is enough to break into the field or if I'm still missing key pieces.

Background:

• 2.5 years in B2B lead generation.
• Built and managed cold email + LinkedIn outbound campaigns.
• Hands-on with Instantly, Apollo, Prospeo, LinkedIn Sales Navigator, Serper, n8n, Antigravity, AI models, and enrichment APIs.
• Built outbound strategies from scratch, including ICP definition, messaging, targeting, and campaign execution.
• Strong in copywriting, identifying winning outreach angles, and researching ICPs.
• Outbound campaigns have generated reply rates ranging from 2% to 11%, depending on the ICP and offer.
• Over the last year, I've shifted from running outbound to building automations for it.

Things I've built:

• LinkedIn intent monitoring that finds prospects actively looking for agencies, vendors, hiring key roles, asking for recommendations, etc.
• Automated lead sourcing that scrapes LinkedIn, company websites, Apollo, and other sources while enriching and verifying business emails.
• AI-powered ICP scoring that:
  • Finds missing company websites.
  • Scrapes websites and LinkedIn.
  • Enriches company and prospect data.
  • Scores accounts against predefined ICP criteria with reasoning.
• RAG-powered email reply assistant using company knowledge and previous Instantly conversations to draft replies for account managers.
• LinkedIn engagement tracking that captures people interacting with relevant posts and adds them into outreach workflows.
• Automated LinkedIn connection requests and follow-up sequences (currently testing) with automatic reply detection.
• AI workflow that classifies inbound replies and drafts suggested responses.
• Local business and directory scraping workflows.
• Sales call transcript to proposal generator cutting time from 1 hour to 5 mins for proposal post sales call
• Competitor ad and messaging monitoring.
• Various custom n8n workflows integrating AI, APIs, Google Sheets, CRMs, and other GTM tools.

My question:

• If you were hiring for a junior GTM Engineer today, would this background be enough to get an interview?
• If not, what specific projects, skills, or experience would you want to see before hiring someone like me?

Looking for honest feedback from people already working in GTM Engineering. I want to spend the next few months building the things that actually matter.

I'm building a tool to help salespeople improve their sales communication. Recently, I was talking to a founder, and he said:

"Imagine this is a self-improvement product. Most individuals won't buy it. But companies that want their employees to improve their communication will."

That completely changed how I thought about my product.

I shifted from targeting a large audience to a much smaller, higher-value segment. Instead of trying to convince thousands of individual users, I'm now focusing on the people who have the budget and a stronger reason to buy.

I also realized I don't want to spend too much time explaining what my product does. The right audience should immediately understand the value.

My takeaway: your real customer might not be your end user. Sometimes, it's the person who benefits from helping the end user improve. You don't always have to sell directly to the people using the product.

You don't need the perfect plan from the beginning. Sometimes, talking to a few people is enough to completely change your direction.

Had the same conversation with 3 clay certified agency owners last month

Quick content:

-Clay moved to dual meter pricing in march (credits + actions)

-Bills now swing 30-50% month to month

-Agencies can't confidently price there work anymore

-3 agencies I know moved off Clay last month

The problem isn't that clay is very expensive, actual problem is: agency margins depend on predictable costs

When a workflow costs you $4k one month and $6k the next.. with no obvious change for the client, someone absorbs the difference. Either the agency loses margin or the client questions the invoice, and the biggest change is.. actions.

Every workflow step, AI call, CRM write and automation is billable, specially ****automation heavy agencies, that's where most of the bill now comes from and it's the hardest part to forecast.

These 3 agencies I spoke to:

-Run outbound for early stage saas

-Enterprise account research

-Fractional revops

Totally different ICPs and price points. All 3 rebuilt workflows to reduce action usage first and eventually said they were spending more time managing clay than building for clients.

(I run a clay alternative and 2 of these 3 switched to us. That's why agency owners tell me this stuff. But the advice below applies whether you choose us or any other tool)

Before choosing any tool, ask an agency that's been using it for 6+ months:

-What does your bill actually look like each month?

-Has pricing been predictable?

-Would you choose the same tool again?

That's where you'll learn what owning the tool actually feels like.

I think more then a clay problem, It's what happens when usage based pricing meets service business margins.

Clay was first. I wouldn't be surprised if more gtm tools head the same way.

Anyone else seeing this? Especially curious whether in house revops teams are starting to feel it too or if this is still mostly agencies

the real reason was cost plus complexity, clay's great but the workflow builder has a learning curve and every icp tweak meant rebuilding graphs.

moved linkedin monitoring and account research over to Swan. Simple prompting there was way faster than rebuilding a clay workflow every time our targeting shifted. kept core enrichment on the old stack for now, data coverage there still isn't quite where clay's is for some of our niche verticals.

ended up folding what used to be three separate point tools into that one piece, which i wasn't expecting going in. onboarding with Swan was quick, mostly through slack, which was the one part of this migration that didn't involve a headache. props to the team.

this said, it’s not a full clay replacement for us yet, more like we finally split the workload between two tools instead of forcing one to do everything. good stuff though. anyone else done a partial migration like this instead of an all or nothing switch?

I want to share this GTM strategy that is unorthodox and will not sit well with some of you. But it works and it contributed to the 10x growth of our user base in 5 months. So here goes.

As a solo founder scaling to 1M ARR, I have to be very creative and deploy strategies that are leveraged; a small input from me, but with a high risk and hopefully a high expected output. My goal is to grow aggressively, and I always found that the best way to to get new potential users is to engage them directly. In fact, It is in my opinion that the best way to arouse a stranger's attention to action is to:

1. Namedrop someone that your potential user is likely to know whether by reputation or personally
2. Pique his curiousity
3. Implement FOMO

With that in mind, the GTM hack is that I have a prospecting agent that sends a cold email to people in similar roles (lookalike persona) in competing companies of every new user that signs up on NinjaPear. The idea is that if a user signs up and tries out NinjaPear, that he is likely to belong to our ideal customer profile (ICP) and so will his competitors since they are in the same industry and so will the person with a similar role as the new user.

For example, if the Patrick Collison, the CEO of Stripe signed up on my site, then he is likely to be an ICP of ours and my prospecting agent will also reach out to:

• Jack Zhang of Airwallet
• Christian Owens of Paddle
• Pieter van der Does of Adyen
• Jack Dorsey of Block
• Kristo of Wise
• Dan Engel of Fastspring
• etc

And these people are also like to be an ICP of ours.

From a technical perspective, what our prospecting agent does is that it will perform a lookalike person lookup with our Similar People Endpoint, and lookup the work email (again with our own API) for each lookalike person and send a cold email that looks something like this:

>

WIth this email, sent at the right time, you will

1. be able to namedrop your new prospect's competitor by name (although we do not namedrop by name, only company name)
2. pique his curiousity as to what his competitor can do to him
3. establish FOMO so the user can quickly sign up and find out what's going on

And if you think about it, this is essentially what GTM and BDR teams do manually. They look through their existing customer base or establish an ICP hypothesis, find out who else is in that ICP and give them a call or send them a cold email. Except that we're doing it autonomously with our AI agent and NinjaPear competitive intelligence data.

Hope this little hack forms yet another piece of your engine to 1M ARR as a solo AI founder!

I am currently working as a freelancer helping founders with foundational GTM - Pretty much everything that moves sales motion until they make a professional sales hire.

1. Setting up content and ABM motion, lead gen data pipelines.
2. Full fledged Outreach using Avatar linkedin (about 170 profiles ) as well as emails.
3. Lead score all engagements using BANT framework before loading the lead to the client’s calendar.

I am trying to get out of freelancing to a more stable contract or fulltime spot. I am reasonably comfortable with AI including Claude code, Manus and Lovable but I am not a developer by profession and thats where I am hitting a wall in my interviews.

I have played the role of founding GTM at 2 startups. The founders love my work. It goes beyond just finding clients. I prewire them with atleast 10+ introductions before they walk in to any event, got them spots at demo events, hyperscaler round tables, pitching and fund raise events. But they haven’t made much progress and I am stuck.

I live 45 mins from NYC and willing to travel. Past experience in account management and recruiting for over 10 years in investment banking. Any recommendations for a role is appreciated?

GTM Engineer / Partnership Channel Owner (Remote, Commission)

Role Type: Remote, build-from-scratch, own the channel end to end

Pay Structure: Commission only to start. You own the revenue directly attributed to the partnerships you build. No cap. Strong performance opens the door to something more durable down the line, this isn't a token gesture, but it's not something I'm going to name a number on here.

Niche: Bootstrapped B2B SaaS built for trade contractors. Plumbers, electricians, GCs, handymen across the U.S.

Right now our only acquisition channel is direct outbound on phone. We want to build a second channel from zero: partnerships with trade schools, continuing-ed providers, and license prep companies, the places that touch a contractor right at the moment they're entering the trade, before they've picked any tools.

This isn't a list someone hands you and you execute. You're building the target list, finding the right person at each org, running the outreach, owning deliverability, and closing the actual partnership. If you want a defined playbook waiting for you, this isn't that role.

Looking for someone who has actually built an outbound motion before, not just run campaigns inside infrastructure someone else already set up. Bootstrapped-company experience is a plus, not a requirement.

If you're interested, DM me for the application link.

Interned at an early stage startup for 6 months and looking for similar full time opportunities.

During my internship I worked on building an end-end icp list building process using tools like n8n,clay,apollo,crunchbase.

I recently graduated with a B.Tech in Mechanical Engineering from NIT Warangal and will complete my GTM Engineering internship at Reo.dev in late July. During my internship, I worked on GTM automation, ICP development and validation, business analytics, data quality, and workflow automation using Apollo, Clay, n8n, Python, SQL, and Power BI.

I'm currently looking for full-time opportunities in GTM Engineering, RevOps, Business Operations, Data Operations, or Business/Data Analytics.

I wanted to reach out to see if anyone in your network or at your company is hiring for similar roles. If someone comes to mind, I'd really appreciate an introduction or any guidance.

The primary goal is to reduce the LLM API costs on the forntier models keping peroformance the same.

Example cases:

1. Files/Docs to Flowchart generation (10000 files/day)
2. Generic web content to structured output (20000 pages/day)
3. Image generation for blog articles in a particular style (1000 images per day)

The output is challenging enough for us to always use frontier models for the best performance but want to reduce the cost it will incur.

We're approaching this with finetuning open sourced models using traning data from frontier models.

We want to know if others are also facing the heat from the API costs, we would like to chat and build an easy solution to handle this at scale for everyone.