Mark Roberge

Boy Dad x2, Co-Founder @Stage2Capital, Prof @HarvardHBS, Founding CRO @HubSpot, Author of Best Sellers, The Science of Scaling & The Sales Acceleration Formula

[Mark Roberge @markroberge]

@Joubinmir @KPGrit Link to the episode is here. Joubin is such a good interviewer. https://t.co/49r7YVpYj1

Link to The Science of Scaling book is here. 100% of proceeds are donated to mental health: https://t.co/ichEuSkxL9

[Mark Roberge @markroberge]

Great to catch up again with my friend @Joubinmir on the @KPGrit podcast

This time, we kind of turned the tables, rolled up our sleeves, and worked on his new startup, Roadrunner, to answer a question every founder is asking:

Should I be scaling faster?

It's interesting that we have so many rigorous frameworks to recognize our revenue—bookings, GAAP, net income—but almost no quantitative frameworks to calculate how fast we should scale revenue.

Imagine you're planning to scale from $10M to $50M ARR by hiring 10 new sales reps every month this year.

How do you know if that's the right plan?

The answer starts with building a revenue scaling speedometer—a set of leading and lagging indicators that inform us if we should scale faster by measuring two things:

1. Product-Market Fit

Are customers consistently receiving the value you promised?

The lagging indicator is customer retention. But retention takes time. The leading indicator of retention (LIR) is much more actionable:

P% of customers complete Event E every T time period.

If we are hitting the LIR, customers are seeing value. They will retain and expand in the longer term. We have PMF.

2. Go-to-Market Fit

Can you acquire customers and deliver that value profitably?

The lagging indicator is unit economics.

The leading indicators come from working backward through the revenue velocity formula:
[Opportunities × Win Rate × ACV] ÷ [Sales Cycle]

Dashboard these inputs, and you'll know whether your go-to-market engine is ready to absorb more investment.

Together, these two metrics inform whether we should be scaling faster.

But what threshold indicates I should accelerate?

It depends on the blitzscale pressure of your category.

If you're competing in an AI-native category with well-funded competitors, set a lower tolerable P% (say 40%) and a higher tolerable payback period (around 20 months) because time is of the essence. You need to take more risks and build the plane while you are flying it. Joubin’s company is in this category.

If you're in a more protected market—with long-term contracts, regulatory requirements, or little room for product defects—set a higher P% (perhaps 90% activation) and a shorter payback period before accelerating your hiring from 10 reps per month to 15.

Whether you're growing from $10M to $100M or from $1B to $10B, every company needs a way to determine whether it should scale faster. Measure product-market fit. Measure go-to-market fit. Let the data—not intuition—determine your pace of scaling.

For more 1st principles frameworks to guide your agentic GTM strategy, check out The Science of Scaling. 100% of proceeds are donated to mental health. The links to the book and the full GRIT episode are in the comments.

[Mark Roberge @markroberge]

Is product market fit… a feeling?

I’d argue the opposite. PMF shouldn’t be based on intuition. It should be easily defined, and it’s something you can outline early in your sales process.

In The Science of Scaling, I share a data-driven way to define product-market fit without waiting a full year for retention data. The core principle: PMF should be measurable, repeatable, and observable in real time.

The framework is simple:

Product-Market Fit is “True” when P% of customers achieve E event every T time.

P (Percentage) — P is the minimum required percentage of customers achieving the E event. If P is surpassed, we have product-market fit. Usually startups use a P between 60% and 80%.

E (Event) — E is the actual customer action, behavior, or result that correlates with long-term retention. E events around product setup, usage, and value outcomes are commonly used. The E should be objective, instrumentable, aligned with customer success and value creation, and correlated to the company's unique value proposition.

T (Time) — T is the time frequency used to evaluate the E event. The shorter the better to maximize the pace of learning. However, T needs to be long enough to yield statistical significance and normalize volatility. Most startups use a T of “monthly”.

With this structure, early teams can stop guessing about PMF and start tracking it with precision. If you can't define and measure your LIR, you risk scaling too early and failing unnecessarily.

In Chapter 2 of “The Science of Scaling: Using Data to Decide When - And How Fast - To Scale Revenue”, I provide frameworks on defining the P, E, and T variables for your business, and provide examples for a range of product and market contexts. Order your copy below. 100% of the proceeds are donated to mental health.
https://t.co/MwmShgNqBm

[Mark Roberge @markroberge]

In a way, the B2B software ecosystem has evolved from "the best sales team won" in the 80s/90s to the "best product team won" in the 2000s to "starting with great product and adding great sales" in the 2010s. I wonder where the AI era will take us.

Learn more in this episode of #TheScienceOfScaling with Mike Gamson, the Founding CRO at LinkedIn https://t.co/UAoLoV1KLa

[Mark Roberge @markroberge]

Congratulations! You’ve just been hired as the CRO of a unicorn. Unfortunately, many CROs have witnessed their companies lose that status over time, often due to macro conditions beyond our control.

This happened to Carina Brockl, the former CRO at Aurora Solar and Stage 2 Capital LP. She and I sat down in this episode of #TheScienceOfScaling to discuss her journey. When she joined, Aurora was one of the hottest climate tech companies around. However, due to an unfortunate sequence of macro changes, the trajectory shifted, placing pressure on her as a leader.

1. When considering a future leadership opportunity, financial diligence extends far beyond ARR and valuation. Is the valuation multiple reasonable? Are the future growth aspirations realistic? How do the historical levers of the GTM math compare to the requirements for achieving future growth? How is customer health, retention, and expansion performing? We often focus too much on high-level valuation without evaluating the fundamentals.

2. As we pivot to new markets, we can be overly optimistic about how the components of the go-to-market system designed for the prior market will translate to the new one. In this instance, the new market was the enterprise sector. We need to navigate the product-market fit and go-to-market fit sequence before aggressively scaling the new segment.

3. It’s always a grind. It always feels like chaos, even in the most successful companies. I’ve never heard of a founder who came up with an idea, raised a ton of money from investors, built that product, had tons of customers buy it, and everyone loved, they went public, and the rest is history. There is always a pivot. There is always adversity. It always feels chaotic; if it doesn’t, the culture may have gotten too soft, and tougher times are ahead.

Listen to the full episode with Carina here: https://t.co/W3cxZbL52O

#SalesLeadership #StartupTips #SaaS #B2BSales #CRO #GoToMarket #RevenueGrowth #ScalingStartups #TechLeadership #QuotaSetting

[Mark Roberge @markroberge]

A trend I am observing in selling AI-native products is a reversal of the “Bring Your Own App” philosophy in the Office of the CIO. This is particularly true among buyers in the tech sector.

What seems to be happening is that the CIO is challenging the organization on whether the sprawl of function-specific apps is still necessary. Instead, can the organizational needs be met with singular horizontal solutions, or even by working directly with the foundational Models, streamlining the application layer, and making data centralization and reconciliation easier?

In this episode of #TheScienceOfScaling, Andy Shorkey, CRO at Writer and Stage 2 Capital LP, discusses the unique hurdles of bringing functional native AI products to market and the evolution of turning the CIO into a partner, rather than an adversary. This is a crucial go-to-market requirement for application-layer native AI products.

Listen to the full episode with Andy here: https://t.co/zFdhX0VBOY

#SalesLeadership #AI #StartupTips #SaaS #B2BSales #CRO #GoToMarket #RevenueGrowth #ScalingStartups #TechLeadership

[Mark Roberge @markroberge]

A common error when transitioning from the Discovery to the Presentation stage of the sales process is the content of the first slide. Many founders and early sellers often start by bragging about their company.

We have over 1,000 customers.

We have 500 employees.

We have raised $100M from [Insert Big Name VC]

We won Employer of the Year for 3 years in a row.

The buyers is sitting there like, “Who cares?”

As we move from the discovery phase to the presentation phase, the ideal first slide summarizes the buyer’s situation as we understand it.

“Thank you all for your time. We have held several meetings with various members of your team, and they are truly impressive. During our discussions, we learned that your demand generation pipeline has experienced a 20% drop over the past two quarters due to a shift in buyer behavior from search engines to large language models (LLMs).

You mentioned that you are working on evolving your strategy and are considering hiring a new agency. Additionally, there is an executive offsite planned for the end of the month, where the team will evaluate options and make a decision.

Is that an accurate summary?”

Imagine being the buyer here. Finally, there is someone who understands you and may be able to help.

Check out the full YouTube episode on closing big ticket deals here: https://t.co/FmAPxOT6ZG

And subscribe to the #TheScienceOfScaling Channel here: https://t.co/8I28Rd6IVh

#SalesLeadership #EnterpriseSales #SaaS #B2BSales #GoToMarket #RevenueGrowth #ScalingStartups

[Mark Roberge @markroberge]

I’m blessed to speak with C-level executives from numerous successful companies on a weekly basis. Through these conversations, I've noticed some interesting patterns. One consistent observation is the size of the team at which leaders typically stop personally interviewing every candidate. Sometimes they continue to do so even when their team exceeds 1,000 people.

It's not that they lack trust in their team leaders. In fact, they are typicaly no longer assessing candidates based on functional skills—those aspects are well managed by their teams. Instead, they focus on determining whether the candidates are a good cultural fit. They understand that a few mis-hires in the wrong direction can be detrimental to the company culture and, consequently, to the organization as a whole.

I have always struggled with the concept of "cultural fit." I've come to realize that this universal term is remarkably unique to each company. In this episode of #TheScienceOfScaling, I discuss this topic with Greg Holmes, the Founding CRO and LP at Stage 2 Capital. He shares how the company's cultural obsession with "delivering happiness" unites their hiring practices, sales processes, reward systems, and even their job titles.

Check out the episode and learn how he built the GTM foundation for a historic company: https://t.co/8KX0VBFz4e

#SalesLeadership #StartupTips #SaaS #B2BSales #CRO #GoToMarket #RevenueGrowth #ScalingStartups #TechLeadership #QuotaSetting

[Mark Roberge @markroberge]

Learn more about the details behind this process in this episode of #TheScienceOfScaling podcast with Chris Merritt, Founding CRO at Cloudflare: https://t.co/Gn18xkNWsO

#SalesLeadership #StartupTips #SaaS #B2BSales #CRO #GoToMarket #RevenueGrowth #ScalingStartups #TechLeadership #QuotaSetting

[Mark Roberge @markroberge]

Startups often move upstream and/or transition from selling a single use case to a more platform-oriented sale. When that happens, teams often underappreciate the correlating complexity of the decision-making process spread across multiple constituencies. (1/3)

[Mark Roberge @markroberge]

Sellers need to understand not only the unique organizational priorities but also the individual priorities of each member in the decision-making unit. The framework below defines common players in the decision-making unit and elaborates on some general tendencies regarding their preferences. (2/3)

[Mark Roberge @markroberge]

Early sales hires, especially during the pursuit of product-market fit, need to know how to summarize market feedback and communicate it to product and engineering teams.

Here’s an interview exercise I conduct with a first sales hire candidate.

Between the first and second interviews, provide the candidate access to the product. Instruct them to use the product over the next few days, show it to people in their network, and generate a list of feedback. In the next interview, allocate time for the candidate to present their findings to the product and engineering teams.

This hire will 10x the touchpoints between your company and the target market. If the candidate excels in this exercise, the timeline to achieve product-market fit will accelerate.

On this episode of #TheScienceOfScaling, I sit down with Greg Holmes, the Founding CRO at Zoom and Stage 2 Capital LP. Check out the episode and learn how he built the GTM foundation for a historic company: https://t.co/3G7IBRvLzd

#SalesLeadership #StartupTips #SaaS #B2BSales #CRO #GoToMarket #RevenueGrowth #ScalingStartups #TechLeadership #QuotaSetting

[Mark Roberge @markroberge]

Check out the episode to learn more about how he built the GTM foundation for this historic company: https://t.co/jxGHM9KOkR

#SalesLeadership #StartupTips #SaaS #B2BSales #CRO #GoToMarket #RevenueGrowth #ScalingStartups #TechLeadership #QuotaSetting

[Mark Roberge @markroberge]

In this episode of #TheScienceOfScaling, I sit down with Greg Holmes, Founding CRO at Zoom and Stage 2 Capital LP, to discuss how he established the go-to-market (GTM) foundation for one of the most well-known tech companies in the world.

Here are a few key takeaways: (1/5)

[Mark Roberge @markroberge]

3. In his initial conversations with customers, Greg focused on understanding their goals, demonstrating how to achieve those goals with the product, and allowing customers a week or so to experience its value before discussing pricing and other commercial terms. This approach is optimal GTM behavior during the pursuit of product-market fit. (4/5)

[Mark Roberge @markroberge]

How to push the scope of you early customer interviews to a contract and pre-payment in order to de-risk "false positive" signals before investing engineering time.

Learn more in this episode of #TheScienceOfScaling with Mike Gamson, the Founding CRO at LinkedIn https://t.co/UAoLoV2iAI

[Mark Roberge @markroberge]

@ryanmilligan90 @Stage2Capital @QuotaPath See the details of Ryan’s approach in this article: https://t.co/aVydTmY1sK

#AI #GenAI #SalesLeadership #StartupTips #SaaS #B2BSales #GoToMarket #RevenueGrowth #ScalingStartups #TechLeadership

[Mark Roberge @markroberge]

Imagine being able to build a sales pipeline without needing to hire a sales development representative (SDR). That's precisely what @ryanmilligan90 achieved with his team at @Stage2Capital portfolio company, @QuotaPath.

At QuotaPath, Milligan devised a strategy to execute outbound campaigns entirely without SDRs, successfully generating a tangible pipeline while avoiding the costs associated with a conventional outbound sales team. (1/4)

[Mark Roberge @markroberge]

The most impactful utilization of AI was not on the execution but on the ideation and strategy formation.
1.Building the workflow itself: “AI has helped us actually build a number of these flows,” Ryan said. “Show me how I get this data here, here, and here.”
2. Campaign ideation: They used ChatGPT to brainstorm new campaign plays and even surfaced the idea of targeting former reps.
3. Building the workflow itself: “AI has helped us actually build a number of these flows,” Ryan said. “Show me how I get this data here, here, and here.”
4. Campaign ideation: They used ChatGPT to brainstorm new campaign plays and even surfaced the idea of targeting former reps. (3/4)