Welcome folks! 👋

This edition of The Product-Led Geek will take 5 minutes to read and you’ll learn:

• How the best PLG companies generate significant revenue beyond direct monetisation

• How to quantify and model your product's indirect revenue potential with a practical mathematical framework anyone can apply

• Specific strategies to optimise your product for the viral referral effects that compound over time

Let’s dig in!

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Indirect Revenue: The Compounding Magic of PLG

In PLG, the focus is often on direct user acquisition and monetisation.

But there's a fascinating phenomenon at play that extends beyond your immediate user base.

What does that look like in practice?

You acquire new users, they experience value, you activate them, and get them to build product habits, then either

• Directly monetise them, and/or

• They bring in other users, some of whom may directly monetise.

And the cycle continues.

This is PLG in a nutshell.

Think of this indirect monetisation as capturing "nth degree revenue."

The Ripple Effect of Product-Led Growth

In traditional sales-led models, revenue flows directly from acquired customers.

With PLG, the story becomes more interesting:

1. 1st Degree Revenue: Users you acquire and monetise directly

2. 2nd Degree Revenue: New users brought in by existing users (through referrals, invitations, word of mouth)

3. 3rd Degree Revenue: Users brought in by your 2nd degree users

4. nth Degree Revenue: The ongoing $ cascade of user-driven acquisition

1st degree revenue is direct revenue.

2nd to nth degree revenue is indirect revenue.

The goal is for users who experience your core value proposition to become more than loyal customers.

You want them to become advocates.

At Snyk - especially in the early days - this word of mouth loop was strong.

Individual developers would bring in entire development teams.

These teams often spread Snyk to other departments or even other companies when they changed jobs.

Quantifying Indirect Revenue Potential

We can build a reasonably accurate mathematical model to estimate the impact of indirect revenue.

The Mathematical Framework

Let's define some variables:

• u: Number of directly acquired users

• r: Average referral rate (new users per existing user)

• c₁: Conversion rate for directly acquired users (1st degree)

• cₙ: Conversion rate for nth degree users

• ARR: Average annual recurring revenue per paying user

For simplicity, we'll assume the referral rate remains consistent across degrees (though you can adjust this in practice).

The total revenue potential can be calculated as:

Total Revenue = 1st Degree Revenue + 2nd Degree Revenue + 3rd Degree Revenue + ... + nth Degree Revenue

Where:

• 1st Degree Revenue = u × c₁ × ARR

• 2nd Degree Revenue = u × r × c₂ × ARR

• 3rd Degree Revenue = u × r² × c₃ × ARR

• nth Degree Revenue = u × rⁿ⁻¹ × cₙ × ARR

The sum of this series, calculated to the nth degree, becomes:

Total Revenue = u₁ × ARR × (c₁ + r×c₂ + r²×c₃ + ... + rⁿ⁻¹×cₙ)

A Practical Example

Let's apply this to a hypothetical B2B SaaS product with strong virality:

• 1,000 directly acquired users per month

• 5% conversion rate for direct users

• Each user brings in an average of 0.3 new users (referral rate)

• Conversion rates decrease slightly with each degree: 5% → 4% → 3.5% → 3%

• $1,000 ARR per paying customer

Calculating the first 4 degrees:

• 1st Degree: 1,000 × 0.05 × $1,000 = $50,000

• 2nd Degree: 1,000 × 0.3 × 0.04 × $1,000 = $12,000

• 3rd Degree: 1,000 × 0.3² × 0.035 × $1,000 = $3,150

• 4th Degree: 1,000 × 0.3³ × 0.03 × $1,000 = $810

Total Revenue Potential: $65,960

That's nearly 32% more revenue than if we only considered direct monetisation!

How Many Degrees to Calculate?

How far should you extend your calculations?

The answer depends on your context, but there are some useful guidelines based on my observations of PLG businesses.

3rd or 4th degree typically captures 95-99% of total revenue potential.

By the 5th degree, the contribution is often less than 1% of total potential.

Referring to our earlier example with a referral rate of 0.3:

• 1st degree: $50,000 (75.8% of total)

• 2nd degree: $12,000 (18.2% of total)

• 3rd degree: $3,150 (4.8% of total)

• 4th degree: $810 (1.2% of total)

We've captured ~99% by the 4th degree.

Going further adds computational complexity without meaningful insight.

However, some businesses should calculate further:

• Consumer apps with extremely high virality (referral rates >0.8) might find significant value through the 5th or 6th degree.

• Products with network effects where value increases dramatically with user count.

• Community-driven platforms where users actively recruit others.

Why PLG Amplifies Indirect Revenue

Product-led growth inherently maximises this effect for several reasons:

1. The product itself drives adoption: Users experience value before purchasing, making their recommendations more credible.

2. Built-in virality: Many PLG products include collaborative features or network effects by design.

3. Lower friction for sharing: Good PLG products make it easy to invite others.

4. Value increases with network size: More users typically means more value (Metcalfe's Law).

It’s not uncommon to find that users acquired through referrals have higher activation rates and lifetime values than those from other channels.

Optimising Your PLG Flywheel for Indirect Revenue

To maximise the compounding effect, focus on these applicable factors:

1. Focus on activating users quickly: Activated users are more likely to refer others.

2. Build in-product referral mechanisms: Make sharing and inviting easy.

3. Create appropriate referral incentives: It’s important to balance both sides of the referral equation with sufficiently motivating incentives.

4. Track referral sources: Understanding your referral chains helps you optimise the process.

5. Nurture your champions: Users who bring in multiple others deserve special attention and are great points of learning.

B2B Complexity: Users vs. Teams

In B2B contexts, the user-to-team relationship adds complexity to the Indirect Revenue model.

While a more sophisticated mathematical model for team-based businesses is possible, I’ve found that these models can quickly become unwieldy and overly complex for practical application.

1. Team-level monetisation dynamics: Users refer other users, but monetisation occurs at the team/account level.

2. Multiple spread patterns: Users can spread adoption within their own company (cross-team) or to new companies when they change jobs.

3. Attribution challenges: When multiple existing users influence a new team's adoption, clean attribution becomes nearly impossible.

4. Variable team sizes: A single referral might bring in anywhere from one to hundreds of users depending on company structure.

5. Contract complexity: Existing customers might add seats, upgrade plans, or create entirely new contracts.

While developing comprehensive models for these complex B2B dynamics is beyond the scope of this post, the core principle remains: in team-based products, indirect revenue effects are often even more powerful than in individual-user products, as a single champion can influence entire teams or organisations to adopt.

Where I’ve landed here for most B2B contexts is that for practical purposes, tracking direct conversions and maintaining some form of influence mapping (even if imperfect) provides important insights without requiring overly complex mathematical models.

The Compounding Magic of PLG: Final Thoughts

Product-Led Growth is about creating a self-perpetuating growth engine that compounds over time.

By understanding and optimising for indirect revenue, you're planting seeds that grow into forests, not just trees.

The nth degree effect transforms your initial acquisition investments into ongoing returns that traditional growth models can't match.

Successful PLG companies build their strategy around maximising this compounding effect.

They understand that every user touchpoint, sharing feature, and moment of delight potentially triggers growth waves that extend beyond what's immediately visible.

As you build and refine your PLG strategy, remember that the most powerful growth lever may not be in your marketing budget or conversion optimisation, but in the invisible networks of influence from satisfied users.

The true magic of PLG lies not just in leading with your product, but in letting your users lead your growth.

THAT’S A WRAP

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That’s all for today,

If there are any product, growth or leadership topics that you’d like me to write about, just hit reply to this email or leave a comment and let me know!

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Until next time!

— Ben

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