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How do you scale sales in the AI age?
This and other questions get a thorough treatment in a new book by Mark Roberge, founding CRO at Hubspot, titled “The Science of Scaling” after his preceding podcast, as Roberge, an investor, a presenter, and a prominent voice on business, talks strategy from a variety of interesting angles, including automation in the equation.
I wanted to talk about a few things that are in this book that can really help business leaders to chart a course through what, to all of us, are uncharted waters. You can’t go back to the 1950s to find insights about how to use AI in business. You’ve got to row forward.
To which point, Roberge introduces a lot of new language to cover this ground, starting with the aforementioned “science of scaling frameworks,” but I’ll get to that. I sat in on a talk by this fellow a while ago, and was impressed – by his casual style, direct and relatable narration, by his ability to take questions throughout, and by his incisive filleting of such ideas as customer retention and churn. But let’s look at some aspects of this new book that drive us to consider how AI changes that relationship between merchant and customer.
I took this list of failure vectors directly from the Amazon blurb on Roberge’s book, because I think it’s a good starting point for jumping off into more discussion. Roberge identifies five scaling pitfalls as:
I put this list into ChatGPT and asked it to simplify, for those of us who have not yet had our morning coffee. You’re welcome:
• Focusing on revenue too early instead of consistently creating value for customers
• Not using real data to determine whether customers truly want the product
• Not understanding what marketing and sales systems need to be in place before hiring salespeople
• Hiring salespeople too early instead of waiting until the business is ready
• Mistaking short-term success for a long-term competitive advantage
What do all of these have in common? There’s a sense that you need a little bit of patience, to combine intuitive understanding with data, instead of just “winging it” with one or the other.
I also thought that Roberge’s use of the term “RevOps” speaks to the ideas of the book in a central way. But what is “RevOps?”
It was immediately evident to me that the revenue buzzword follows the prior use of “DevOps,” which describes a blending of traditional steps in software engineering processes. Beyond that, here’s how Jenny Kelley describes this idea at Synthesis RevOps:
“Let’s be honest: RevOps sounds like something a CFO mutters before calling in the CRM police. But RevOps isn’t just a tech stack buzzword—it’s the beating heart of any growing organization that wants to scale with intention … At its core, Revenue Operations is the strategic alignment of your revenue-generating functions or commercial operations (sales, marketing, and customer success). The practice helps unify and coordinate efforts under shared goals, data, tools, and processes. It makes connections between the customer journey and your internal workflows.”
I was very tempted to again put this into GPT and have it translated into something very scannable that a non-tech person would grok better. But essentially, that phrase “strategic alignment” points to a unification that correlates to what DevOps does for software engineering – the idea that you can break down walls, eliminate silos, and “fluidize” a process.
Another thing that I remember from Roberge’s talk was his focus on something called “product market fit,” which is, in a way, exactly what it sounds like: do people want my product?
But there are different ways to measure this – intuitively, with statistics, or with definitions building on the kinds of strategic ideas that are the coin of the realm for marketers, tools for scaling, and more. I’ll give you a direct quote from Roberge that I found on YouTube:
“I'm proposing to you that you should quantify product market fit on retention in the long term and invent a leading indicator of retention that you will measure for the rest of your lives in your business.”
Add that to the mix.
As for ‘science of scaling frameworks,’ Roberge suggests that these are a “first principles design template” for business. This is more fully explored in the pages of this book, which I think is a valuable guide for implementers in a time of great competition, where automation is changing the landscape quickly.
Stay tuned.
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