The GTM Efficiency Crisis

“It’s like dragging a truck of dead bodies over the finish line.” Chamath’s sentiment on creating alpha for his LPs in 2023 perfectly encapsulates how GTM leaders feel today.

GTM feels broken, and the metrics that GTM machines churn out validate this feeling. CAC is up, retention is down, and board meetings feel like chewing glass for most CXOs.

GTM Efficiency, which looks at the sales and marketing costs required to generate $1 of Net New ARR, does a great job of highlighting this problem. David Spitz, the man behind the metric, has shown us that public tech companies are 57.86% less efficient today compared to 2019. (And it’s worse for private companies.)

This is clearly a problem, but what should we do about it?

The answers from within the GTM community involve reducing the slack and thrash within GTM teams. Focusing less on “Growth At All Cost strategies” and being “more aligned.”

So far, I have been in violent agreement with my compatriots, but the more I think about it, the more I diverge from their point of view. It just feels too easy that the answers to all our problems are within GTM.

Hard to find and easy to lose
Aside from death and taxes, another certainty in our world is that distribution keeps getting harder.

With the supply of tech companies increasing at 7% per quarter, competition and saturation are worsening daily. Inboxes are busier, cold calling is less effective, and GTM teams are spending most of their time screaming into the abyss.

AI will only make this worse.

As models get bigger, smarter, and cheaper, we’ll be able to use them to build transformative new products faster than ever before. That means more competition.

But, with the pace of change we are seeing in AI right now, what feels transformative today might quickly feel obsolete. That means your technical competitive advantage might be a fleeting one.

A lot of AI powered GTM tech is turning out to be spray and pray tech 2.0. Banal messages catapulted out to obscenely large lists of contacts, enriched with a few so-so insights. That means inboxes will be noisier, and capturing attention will be harder.

Fine, we’ll have higher CAC, but at least we’ll have high switching costs to help hold onto customers. But, not so fast… AI Agents will help with customer onboarding, reducing switching costs dramatically. That means retention is going to become much harder.

If you are an AI believer, then this is the world you need to prepare for. A world where customers are harder to find and easier to lose.

You then have to ask yourself if these powerful headwinds can be negated through more operational excellence and better alignment within GTM. Are those problems big enough for the improvements to counter the massive AI headwinds GTM teams are going to be dealing with?

Or is the overall problem more severe and the solution more holistic?

Burn Multiple > GTM Efficiency
Almost every GTM team in the tech world has room for improvement and should strive for it. But what happens when those efforts still fail to move the needle on GTM efficiency? What if conditions worsen because of AI?

If GTM Efficiency continues to deteriorate and everything else stays the way it is today, then we are in trouble. But, if we can balance out the increased costs in GTM somewhere else, and maintain a healthy Burn Multiple, then we might be fine.

For all the risks AI poses to GTM, it does provide a lot of opportunities to find efficiencies in other parts of our organizations. AI Agent startups are on a tear, with 156 deals in this space over the last 12 months (81.4% YoY increase). These companies are building AI Agents that could provide substantial cost savings in software development, customer service, finance, and legal.

Additional cost savings are available through intelligent offshoring. I spoke to a founder last week who has a 25 person engineer team, of which 24 of them are in India. Risky right? “Not when done well” was his take.

These cost savings are increasingly available, and understanding how to leverage them is becoming crucial. Those who do will be able to stomach the additional GTM costs. The math will math at the P&L level, which is what really matters.

There will also be another group that will be fine, which is those who are able to find and hold onto extreme Product Market Fit. Those companies have always had great GTM metrics, irrespective of where the interest rate is. But being Wiz is hard, which is why we are all so enamored by them.

On the other hand, I worry for those who believe that deteriorating GTM Efficiency is just a GTM problem. This group risks letting siloed thinking place them on a flimsy plank by a windy cliff – some might hold on for dear life, but most will be swept away into the unknown.