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The 2024 Stage 2 Capital Catalyst Curriculum has officially kicked off! 

We've got a diverse group of founders with us this year, tackling challenges across a number of industries – both old and new. 

First a quick intro, I'm Erin Olsen, Interim Head of Marketing here at Stage 2 Capital. I'll be your guide through the Catalyst 2024 program, giving you an insider's view of the valuable insights and experiences shared during our sessions.

Here's what I'm planning to do for you: Each week, I'll be your eyes and ears on the ground of the 2024 Catalyst Curriculum. I'll capture the key insights, distill the big "aha" moments, and even dish out some homework for you to apply these lessons to your own startup journey. My goal is to bring the Catalyst experience to you and help you learn the Science of Scaling methodology right alongside our cohort.

This week, we're tackling a question that keeps many founders up at night: When is the right time to scale your startup? 

How do you know you have PMF? What data do you look at? We'll explore how to make data-driven decisions around Product-Market Fit (PMF) and Go-to-Market Fit (GTM Fit), setting youup for sustainable growth.

You won't want to miss this!

What Does it Mean to Be Ready to Scale?

Mark Roberge, Co-Founder of Stage 2 Capital, kicked things off with a simple question:

"When do you know you're ready to scale?"

This sparked many different responses from founders. Some talked about having a product that customers are willing to pay for with promising unit economics. Others shared that it's when existing customers are buying more. Some pointed to customers recommending your products to others as a key indicator. Another interesting perspective was that you're ready when you have double-digit clients signing up consecutively with very similar profiles.

These indicators? They're great, but they're not the whole story. 

The takeaway from this discussion is that figuring out when to scale is a tricky question and one that evokes many different opinions. Customer retention is ultimately the best quantifiable indicator of product market fit, but here’s the problem, retention is a lagging indicator - meaning you’re not going to know if you have it until it’s too late. You have to find a leading indicator of retention. 

Mark's position is that while each company is different, there is a consistent framework that can help you identify when your company is ready to scale. And he breaks it down into two critical areas:

1. Product-Market Fit (PMF): This goes beyond just revenue numbers. It's about customer retention and consistent value delivery.
   
   
2. Go-to-Market Fit (GTM-Fit): Understanding the economics of your customer acquisition and service model.

You’re ready to scale, when you have Product-Market-Fit AND Go-to-Market Fit and you do these sequentially. 

Let's get into each of these concepts and how to measure them effectively.

Product-Market Fit: Leading Indicators of Retention

Product-Market Fit is the holy grail of early-stage startups. It's the point at which your product satisfies a strong market demand. But how do you quantify something that can feel so intangible? Enter the concept of Leading Indicators of Retention (LIR).

The LIR is defined by a simple yet powerful formula:

P% of customers do E event every T time

Where:

• P is the percentage of customers (This is usually somewhere around 70% give or take)
• E is a specific event or action (This is the most important - it has to be objective. It can't be "customer success person thinks they're good" - nope, that's an opinion)
• T is a time frame (usually this is monthly)

💡 Pro-tip: Keep your LIR simple. Many companies are tempted to go down the path of mixing multiple variables, something that sounds like "If 80% of customers send X number of messages OR have XYZ number of users AND they are using other XYZ product (you get the idea). Yes, that's cool but Mark reminds us that it's also complicated. When you move into scale, you want it to be a powerful tool across the company. And if it's too tricky for people to easily understand, it's also going to be hard for people to execute it.

This formula helps you identify the key actions that indicate your product is providing real value to customers. Let's look at some examples from well-known companies:

• Slack: 70% of customers send 2000 team messages per month
• Dropbox: 85% of customers back up their device every day
• HubSpot: 80% of customers use five or more features in the platform every month

These metrics go beyond vanity numbers like signups or downloads. They reflect actual product usage and customer value.

As Mark Roberge challenges us: "What is the lead indicator of retention for your business?”

Identifying your LIR is crucial because it provides an early signal of customer retention, long before you see it reflected in your annual renewal rates.

Measuring Your Leading Indicators of Retention

Once you've defined your Leading Indicator of Retention (LIR), the next important step is measuring it. 

Let's break it down:

The Cohort Analysis Approach

For companies acquiring 10+ customers per month:

1. Create a cohort chart based on customer acquisition date (usually by month).
2. Track what percentage of each cohort hits your LIR over time.
3. Look for trends and improvements as you make changes to your product, onboarding, pricing, etc.
   
   

For example, a company might see:

• January cohort: 3% hit LIR after 1 month, 27% after 2 months, 40% after 5 months
• September cohort: 68% hit LIR after 2 months, 75% after 3 months

As you look down this chart, you can see the 

This improvement indicates progress towards product-market fit.

💡 Pro-tip: Don't overthink your LIR. Once you have data, you'll start to see how your progress is tracking over time and you'll likely end up changing your LIR based on this data, especially as you scale. The key is to start measuring and iterating rather than getting stuck trying to find the perfect metric from the outset.

Defining Your Ideal Customer Profile (ICP)

As you start to see the data from your cohort analysis, you'll also start to see which customers are hitting your LIR and which ones are not. This is going to help you understand what your ideal customer looks like. You'll start to see patterns emerging, which will be key in refining your Ideal Customer Profile (ICP).

Mark reminds us that you want to be precise around your ICP and used an example of a company that does AI for customer support teams. They defined their ICP based on attributes such as:

• Systems used
• Geography
• Team readiness
• Contracting process
• Integration team

The key is to categorize potential customers into three groups:

1. Green: Home run fit. These are your ideal customers.
2. Yellow: Potential fit. You wouldn't proactively target them, but you might sell to them if they come inbound.
3. Red: Poor fit. Disqualify immediately, even if they come inbound.

How does this work in practice? Your ICP serves as a guide for your teams, helping them know when to proceed, when to act opportunistically, and when to politely decline. Here's how it might play out:

• Green (Ideal fit): Your BDR team creates cold calling lists exclusively from this group. Your marketing team targets only these prospects in email campaigns.
• Yellow (Potential fit): You don't proactively target these prospects, but if they come to you, you're open to exploring the fit.
• Red (Poor fit): Even if these prospects reach out, you should politely decline. This can be challenging, especially when a salesperson sees a potential commission, but as the CEO, you need to maintain discipline and say no to protect your long-term strategy.

Remember, your ICP isn't about proving a billion-dollar market right away. It's about finding the least risky path from zero to $1 million, and then from $1 million to $10 million. You can expand your target market over time, but starting with a precise ICP allows you to build repeatable solutions and achieve product-market fit more efficiently.

Understanding Go-To-Market Fit (GTM-Fit)

Once you've achieved Product-Market Fit, the next step is finding Go-To-Market (GTM) Fit. This is where you optimize the economics around your product and target market. 

Mark explains, that just like in Product-Market-Fit where, the best internal statistical metric for you to understand is customer retention, you need leading indicators for your GTM.

The key metric for GTM-Fit is unit economics - the profitability of your go-to-market motion in acquiring and servicing customers. Unlike GAAP accounting profitability, unit economics scales with your customer base.

Measuring GTM Fit: LTV to CAC Ratio

While there are various ways to measure unit economics (payback period, magic number, burn ratio), Mark used the example of Lifetime Value to Customer Acquisition Cost (LTV to CAC) ratio. The industry has accepted a general standard that your LTV to CAC ratio should be greater than 3. (We'll discuss this further in Module #2, including how a Cohort-CAC-payback approach offers greater accuracy. However, it's valuable to master the LTV to CAC formula, as it remains a common metric investors use for evaluation.)

Here's a simplified breakdown:

1. LTV (Lifetime Value) = Annual Contract Value (ACV) × Gross Margin ÷ Churn
2. CAC (Customer Acquisition Cost) = Cost to acquire a lead ÷ Close rate

For example:

• If your ACV is $20,000
• Your cost per lead is $1,000
• Your close rate is 5%

You can plug these numbers into the formula to see if you're achieving the desired LTV to CAC ratio.

Rules to Follow When Defining GTM-Fit

1. Don't focus on unit economics too early. In the PMF phase. For example, it's okay to have discounted rates for early customers.
2. Once you're confident in your PMF, start getting serious about economics. This is when you consider pricing, hiring professional sellers, and investing in marketing.
3. Use leading indicators of unit economics to guide your decisions, just as you used LIR for PMF.
4. Remember, achieving GTM-Fit comes after PMF. Do these sequentially.

Next week, we have an entire Module of the Catalyst Curriculum dedicated to implementing GTM-Fit so keep an eye out for more!

Key Take-Aways from Catalyst’s Module 1: Science of Scaling and PMF

Here are the five essential lessons.

1. Phased Approach to Growth: Progress sequentially through Product-Market Fit (PMF), Go-To-Market Fit (GTM-Fit), and Growth and Moat phases.
2. Measure What Matters: Use Leading Indicators of Retention (LIR) to assess PMF and Leading Indicators of Unit Economics (LIUEs) to evaluate GTM-Fit. These metrics form your scaling "speedometer."
3. Time Your Scaling: Start scaling when you've achieved both PMF and GTM-Fit. Scale by setting a hiring pace and adjusting based on your speedometer readings.
4. Evolve Your GTM Strategy: As you progress through scaling phases, adapt your Go-To-Market system, including target market, playbooks, demand generation, pricing, and compensation.
5. Define and Refine Your ICP: Focus your Ideal Customer Profile (ICP) on segments where you can achieve PMF and GTM-Fit. Start with smaller, more tolerant segments to accelerate learning and iteration.

That’s it for this week! 

We invite you to apply these concepts to your own startup and encourage you to complete the following exercises:

• Define your Leading Indicator of Retention (LIR)- Analyze correlations between user behavior in the first 30 days of usage and long-term retention / user engagement
• Define your Ideal Customer Profile (ICP) - Identify segment(s) with high LIR performance
• Create the LIR dashboard (you can find more details and a template to guide you here). Populate the dashboard with available historic data and instrument its population for future data.

Stay tuned for upcoming posts in our Inside Catalyst series and pop your questions in the comments section.