A Brief Masterclass on "GTM Engineering" — What it is, Why it's important, and How to do it:

GTM engineering is essentially the process of identifying a quality segment within a TAM, then crafting a 1-of-1 message that resonates deeply with the segment persona you're looking to sell to.

Why is this an important concept to understand?

Because this is how we craft messaging that is actually USEFUL to the prospects that we reach out to.

We are identifying a real need for their sub-industry and role within their company, then tying in our solution in a unique way to their specific situation.

This is a message that, for people who are in the market for solving their problem, would have wished to receive earlier, or potentially even PAID for.

At @RevGrowthAI, we follow the following GTM engineering process for each of our clients to uncover messaging that truly resonates with their ICP:

1. Analyze TAM

First we create an overview list of all the potential companies that our client can work with, their entire Total Addressable Market.

We can use databases such as Apollo, Crunchbase, BuiltWith, Clay, Ocean, or Pandamatch to build out your initial TAM list.

Examples of this can be all SaaS companies, E-commerce brands, Hospitality businesses, etc.

2. Develop Market Segments

Now we’ll start narrowing the TAM into ideal segments.

This is where the real engineering happens, we’ll use AI to analyze our overall TAM and our service offering to give us unique segments that we can best service with our solution.

These will be the people we want to reach out to.

We can break down our TAM into segments according to persona job roles, company sub-industries, employee count, intent signals, and any other scrapable relevant data.

We’ll build our lists around these segments using Clay + other relevant providers.

3. Find unique relevancy within segment

This is where we’ll discover message-market-fit.

We’ll do a deep dive into each of these segments to sniff out specific pain points or needs that are 1-of-1 to their situation.

For example, I just had a coaching call today with @ClientAscen students and one of the students was working with a client who helps companies track the condition and status of their supply chain at scale more efficiently.

At different employee counts, logistics become more intense for these companies, meaning that at each level each of these companies will have their own unique pain points, as well as the different roles in the companies (we uncovered all of this info with AI).

4. Tie into offer solution

Now that we have an understanding of each segment’s pain points and needs, we can tie our offer in as the solution seamlessly in a way that’s tailored to each situation.

The goal here really is to show the prospect that you have a deep understanding of their situation and can make the value of your offer clear to them for solving bottlenecks for their unique situations.

Referring back to the logistics companies example, a persona that we can resonate with is cross-dock operations managers at cross-docking companies.

We can mention how our solution solves the common pain point of preventing mixed or mislabeled freight with real-time documentation during transfers at scale.

5. Craft messaging

From here crafting the messaging is simple:

-> Lead with the pain point of freight being mixed or mislabeled, resulting in potentially millions in failed logistics costs
-> Present solution of all-in-one application that manages freight effectively to prevent lost costs
-> Call-to-action around testing solution or implementation
The messaging falls into place seamlessly once you layout your target segment in detail and do the research.

Hope you found this one useful & feel free to shoot me a DM if you have any questions, cheers.