Marcos Rivera

Most B2B SaaS leaders build value.
But forget to capture it.

Let me guess:

- You’re guessing your price
- You’re losing revenue
- Scaling feels stuck

What if pricing could drive growth?

Here’s what I help you do:

→ Capture more value
→ Make pricing your edge
→ Build pricing confidence

Why should you trust me?

- 25+ years in tech pricing
- Ex–Head of Pricing at Vista Equity
- Priced 400+ SaaS products
- Author of *Street Pricing*
- Trusted by MBAs and SaaS CEOs

Beyond coaching, 

I’m an:

→ Investor 
→ Speaker
→ Entrepreneur 

passionate about helping businesses unlock their full revenue potential.

Ready to take control of your most powerful growth lever—pricing?

Checkout my featured section.

Founder and CEO

We help growth-stage B2B SaaS companies design the right pricing model to scale up

Ready to shift your pricing from guesswork to framework?

Most pricing consultancies hire from McKinsey or Simon-Kucher.
We hired Emily Sanz from American Airlines and British Airways.

When I was building out the Pricing I/O team, I had a choice. 
I could hire the typical profile: ex-consultants who'd spent their careers making slide decks about pricing but never actually owned a P&L.

Or I could find people who'd lived pricing in industries that do it better than almost anyone.

Emily had spent years in airline pricing. The joint business between them. 
She'd done consumer pricing, B2B pricing, and everything in between.

Airlines invented revenue management. 
They've been optimizing for 50+ years. 

They deal with infinite data points, razor-thin margins, and customers who compare prices obsessively. If you can do pricing there, you can do it anywhere.

What Emily brought to Pricing I/O that we couldn't have gotten from a traditional consultant:

→ An obsession with customer segmentation. 
Airlines don't have "3 tiers." They have hundreds of price points for the same seat, because different customers have different willingness to pay.

→ The concept of "quality of revenue." 
Not just how much you closed, but what kind of revenue it is. A discounted seat to fill the plane is not the same as a full-fare business traveler. Same applies to SaaS.

→ A data-first mindset. 
In aviation, you don't guess. You measure, test, and iterate constantly.

When she joined back in 2023, I asked her what surprised her most about SaaS pricing.

Her answer was about how little data most companies actually use. 
They have it. They just don't look at it.

We don't hire career consultants who've never operated.
We hire people who've lived pricing in industries that do it better than anyone, and bring those lessons to SaaS.

That's how we work in the trenches differently.

CEO of Pricing I/O • Award-Winning Author • Sought after Slayer of Bad Pricing

Four years ago, it was just me and a laptop.
This room held 25 people last meeting.

We gathered the Pricing I/O team for our end-of-year off-site, and something hit me during the planning session.

We're not just growing. 
We're building something that compounds.

→ 30% revenue growth year over year.
→ Pipeline doubled since Ali joined in Q3.
→ Client satisfaction scores hitting 10 out of 10.

But here's what really gets me: the debates in that room.

Some of them going back and forth on engagement models. Others challenging assumptions. 

The whole team leaning into problems that didn't exist when we were a team of four.

I used to think scaling a consulting firm meant losing the magic.
Turns out, with the right people, the magic multiplies.

2026 is going to be even better. 

We're cooking up something new, can't share details yet, but let's just say it involves working code and a launch window in Q1/Q2.

Stay tuned.

The best hires don't just check boxes, they make you rethink what the boxes should be.

Lauren DeGirolamo, MBA, CPP joined us as a Pricing Strategist back in December.

Before Pricing I/O, she was Director of Strategic Pricing at Baker Distributing, leading a team of 9. Before that, she spent nearly three years at Resideo navigating pricing through supply chain chaos.

One thing from her background that stuck with me: she restructured a pricing matrix from over 1,400 customer conditions down to 7.

That's not optimization. That's the kind of simplify-the-complex thinking that separates good pricing people from great ones.

When I asked her what surprised her most about joining us, she didn't mention the work or the clients.

She mentioned our offsite.
"This was the first time I had ever seen a CEO involving his entire team in high-level strategic decisions, listening with open ears to hear all perspectives."

That one got me.

Because that's exactly the culture we're building. 
Not top-down mandates. Real debate. Real input. Real ownership.

Lauren called it "the secret weapon behind Pricing I/O's success."
I'd have to agree.

Her spiciest pricing take?
"Lowering prices too much can actually hurt market share, it signals to enterprise buyers that your product is less capable."

Strong opinions backed by experience. That's what we look for.

Oh, and her karaoke song is "Remember the Name" by Fort Minor. 
If you know, you know.

Welcome to the team, Lauren. 
Love seeing you win already.

25 people. $10M bootstrapped. Zero outside funding.
And the culture is the best I've ever been a part of.

I'm not saying this to brag. 
I'm saying it because it almost didn't happen this way.

The original plan was me, myself, and I.

But here's what I've learned building Pricing I/O:
The company you build reflects the problems you solve.

We help companies capture value. 
So we had to build a company that captures its own value, through people, not just process.

We teach teams to own pricing long-term. 
So we had to build a team that owns their work, not just executes tasks.

We work in the trenches with clients. 
So we had to hire people who want to get their hands dirty, not just advise from a distance.

Every value we preach to clients, we had to live internally first.

That's what makes the culture real. It's not a poster on a wall. 
It's the business model.

We're still figuring it out. Still learning. Still making mistakes.

But building in public means being honest about the journey, not just the wins.

Clio scaled from 250 to 1,000+ employees.
Their pricing strategy? "Sporadic" and "on a needs basis."

Here's the thing most people miss about hyper-growth: 
the faster you scale, the more your pricing cracks show.

When we started working with Clio, they had a cultural resistance to monetization. 

The team genuinely wanted to deliver "outsized value" to customers, which sounds noble until you realize it was capping their ability to reinvest in the very innovation customers were asking for.

So we ran a full revision of all their products and service offerings.

The foundation? Their own "law firm maturity model", a blueprint that let us design pricing and packaging that grows alongside their customers, not against them.

The results hit across the board: NRR improved. ARPA improved. LTV improved.

But here's what changed the game long-term:
Pricing is now part of every single new product launch and release at Clio.

Not an afterthought. Not a "we'll figure it out later." A strategic lever from day one.
That's the shift. 

→ From reactive to proactive. 
→ From sporadic to systematic.

And it doesn't happen by accident, it happens when you treat pricing like the growth engine it actually is.

Me and Min S. FitzGerald talked about it on my podcast.
You can watch the full episode on Pricing IO Youtube channel.

Most pricing projects start with excitement and end with a deck nobody opens.
I've seen it happen dozens of times.

Great research. 
Solid recommendations. 
And then... nothing changes.

Why?

Sometimes it's because nobody owned the implementation.
Sometimes it's because the company wasn't ready, they didn't have a clear product strategy, and pricing can't fix that.

But when the foundation is solid, and you have a partner who works in the trenches with your team?

That's when pricing goes from "expense" to "investment."
Swipe through for what actually works, and what doesn't.

Failure

How long does it take your company to launch a new pricing model?

If the answer is "we'd need to check with engineering" or "probably a quarter," you have an infrastructure problem.

Most billing systems were architected when pricing was three simple tiers and annual contracts. 

Adding each new capability felt manageable, usage tracking here, credits there, custom packages for enterprise.

But step back and look at what you've built right now. It's infrastructure. 
Complex, mission-critical infrastructure that nobody planned for.

Now there's a gap opening up. 
Some companies can test new pricing in days. 
Others need months for basic changes.

Some can close deals with flexible packages. 
Others lose deals because their system literally can't support what the customer needs.

That gap isn't about engineering talent. 
It's about whether your monetization infrastructure was designed for the world we're in now or the world we left behind.

Tomorrow, Manish Choudhary from Flexprice and I are walking through how this shift happened, why it caught everyone off guard, and what separates companies that can move fast from companies that are stuck.

How Monetization Became Infrastructure and No One Noticed
January 15, 10:00 AM EST
Register here ↓
https://skd.so/LBzBi3

Vibe coding is going to kill more B2B SaaS companies than AI competition will.
Here's why ↓

Right now, there are CEOs downgrading every SaaS subscription to the cheapest tier, and building custom tools on top with Lovable, Bolt, and Claude.

The CRM becomes "just a dumb database."
The premium analytics features? Vibe-coded in an afternoon.
The RevOps workflows you charge extra for? Replaced by something stitched together over a weekend.

The implication for pricing is massive:
Differentiation that used to last 5-6 years in client-server days... then 1-2 years in SaaS... now lasts weeks or days.

When your customer can vibe-code a "good enough" version of your premium features themselves, your pricing power evaporates.

So what becomes the moat?
Two things:
→ Distribution (can they find you before they build it themselves?)
→ Depth of integration (are you so embedded they can't rip you out?)
→ Data (do you have proprietary data they can't replicate?)

If your pricing strategy assumes feature differentiation will protect you, you're already behind.

The companies that win will price for outcomes and depth of integration, not feature access.

Because features are getting commoditized faster than anyone predicted.
How are you thinking about this in your pricing model?

Credit-based pricing is an admission that you don't understand your value yet. 
I've been watching the AI pricing space closely, and here's what I'm seeing across dozens of companies ↓

They're adopting credits and tokens not because it's the best model, but because they're uncertain about two things:
→ What use cases will actually drive adoption
→ What value those use cases deliver

So they default to tracking costs (tokens, compute, API calls) instead of outcomes. 
And here's the thing, that's not necessarily wrong at this stage.

But there's an important distinction to make here.

Cost-plus credits tied to tokens or compute? 
That's transitional. 

When you're genuinely uncertain about value delivery, it buys you runway to learn. 
But it shouldn't be a destination.

Action-oriented credits tied to meaningful outcomes? 
That's different. 

Companies like Clay AI and HubSpot have built successful credit systems because the credits correlate to actions that derive value, updating a contact, enriching a record, taking a step that moves the business forward. 

Easy to understand, easy to connect to ROI.

The difference is whether credits measure what you spend or what the customer gains.

Three questions to ask yourself if you're running credits today:
1/ Are you tracking which actions correlate with customer success?
2/ Do you know which use cases drive the most willingness to pay?
3/ Do your credits reflect cost consumption or value delivered?

If your credits are just a proxy for compute, you're not pricing strategically, you're billing for infrastructure.

What's your take, are your credits measuring cost or value?

AI companies can capture more value than SaaS ever could.
Here's why ↓

On-premise software captured roughly 5% of the value it created. 
You were paying for access, that's it.

SaaS changed the game. 
Suddenly you could track activity, usage, outcomes. 
Value capture jumped to 10-15%.

AI changes it again. 
Usage patterns vary wildly. 
One customer might use 10x what another does, and get 10x the value.

The companies figuring this out are capturing far more than the old SaaS playbook allowed.

But here's what most are getting wrong:
They're still pricing AI like it's SaaS. Flat seats. Fixed tiers. One-size-fits-all.

That made sense when usage was predictable. It doesn't when one user generates 50 API calls and another generates 5,000.

The shift isn't just about pricing models. It's about how you think about value exchange entirely.

Your CFO now needs data science skills to understand AI unit economics. Performance margins can swing from 10% to 75% depending on which model you're running.

This is a different game with different rules.
Are you still playing by the old ones?

You're not going to lose your customers if you raise your prices.
I know. It doesn't feel that way.

I've heard this from hundreds of founders and CEOs. 
Smart people. Running great companies. 
Paralyzed by the thought that one pricing change will undo everything they've built.

Here's what actually happens:
We help them build the case. 
Research. Data. Competitive benchmarks. 
They see the evidence that they're underpriced.

Then comes the hard part: actually telling customers.
They start with a few. Hold their breath. Wait for the backlash.

And most of the time?
Customers say yes.

Not all of them. But enough. 
And suddenly the fear dissolves. 

They realize they were leaving money on the table for years because of a story they told themselves.

Here's what we've learned from 400+ engagements:
We almost never recommend lowering prices across the board.

What we find is companies are underpriced in segments they didn't realize, while over-discounting in others.

The problem isn't usually "we charge too much."
It's "we're not charging for the right things, to the right people, in the right way."

If you've been putting off a price increase because you're scared of the reaction, you're not alone.

But the fear is almost always bigger than the reality.

Nobody wakes up thinking "today's the day I fix pricing."
But by the time pricing feels urgent, you've already paid the price.

It usually gets pushed. Delayed. Deprioritized.

There's always something more urgent, a product launch, a reorg, a board deck due Friday.
Meanwhile, the warning signs pile up quietly.

Your best rep starts discounting 30% "just to stay competitive." Finance notices tier 1 is overflowing while tiers 2 and 3 collect dust. A prospect tells you "you're too expensive", then signs with a competitor charging 40% more.

Each one feels manageable in isolation.

But together? They're symptoms of pricing that stopped reflecting your value a long time ago.
The hardest part isn't the fix. 

It's admitting you've been leaving money on the table while focused on everything else.

I've seen this exact pattern in hundreds of companies. 

If you want to win it, start by recognizing the early signals and acting before the damage compounds quarter over quarter.

How many of these signals are showing up at your company right now?

$300K to $30M ARR in two and a half years.
100x growth.

One change: the pricing metric.

The product was a dispatching tool for insurance companies. Seat-based pricing.

Here's the problem, the better we performed, the less revenue we got.

Customers optimized routes, needed fewer seats, and downsized at renewal.
We were penalizing ourselves for delivering value.

So we tested five or six different metrics. Ran correlations. Talked to customers.

Per claim made the most sense.

It aligned with how insurance companies already tracked value and cost. 

Claims scaled with their business. Our revenue finally moved with theirs.

That's when I realized: pricing isn't a math problem. It's a value alignment problem.

The metric you choose determines whether you grow with your customers, or get left behind.

If you're adding AI to your SaaS product, you're about to face a pricing decision that most companies get wrong.

Do you charge per seat? Per usage? Per outcome? Some combination?

The answer depends on how you layer your pricing model. And there are really only three layers to work with.

Base 
Your platform, features, functionality. What customers get access to regardless of how much they use.

Allowance 
What's included before overage kicks in. This is where most companies mess up. Too little creates friction before customers see value. Too much kills your expansion revenue.

Meter 
The unit you charge for when they scale. Get this wrong and customers game the system. Get it right and revenue grows with their success.

Every hybrid pricing model is just a different combination of these three layers.

Access Tiers? Just Base. 
Platform fee plus usage? Base + Meter. 
Credits with overage? All three layers working together.

I broke down five models we see working in the market right now, with specific examples like Intercom Fin's $0.99/resolution and when each model fits best.

Here's what I've learned after 400+ pricing engagements: the model you pick matters less than whether it matches how your customers actually buy and scale.

Most companies copy competitors. 
The ones that win design for their own customer journey.
Which model fits how your customers grow?

Labeling something as "AI" actually lowers trust.
I know. It sounds backwards.

Every company is racing to slap "AI-powered" on their product. 
The assumption is it increases perceived value.

The data says otherwise.
In willingness-to-pay research, the AI label barely moves the needle on what customers will pay. And in some cases, it actively creates skepticism.

Why?
Because the market is shifting from "play AI" to "may I", as in, "may I see proof this actually works?"

Early adopters bought the hype. 
The next wave of buyers wants evidence.

ClickUp figured this out. 
Their standard plan is $7. Their AI plan is $28, 4x the price.

But they didn't just slap "AI" on it and hope for the best.
Their positioning: "This replaces 4-5 other AI tools you're already paying for."

The value prop isn't "we have AI." 
It's "we simplify and centralize what you're already doing across multiple tools."

Simplification + consolidation = worth the premium.

The companies winning at AI pricing aren't selling AI. They're selling outcomes that happen to be powered by AI.

What are you actually selling?

If your sales team doesn't believe your solution is worth the price, they won't sell it.

They'll discount it. They'll apologize for it. They'll position it as "a bit expensive, but..."

I had a client where the salesperson literally felt bad charging customers. 
Not because the product was bad. Because SHE didn't believe it was worth what they were asking.

That feeling? It bleeds into every demo, every negotiation, every close.

You can have the perfect pricing model. The perfect packaging. The perfect positioning.

But if your own team doesn't buy what they're selling, your customers sure as hell won't.

The problem isn't your price. 
It's that you never convinced your team of the value first.

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Pragmatic Marketing, Product Management Certification Level 4

Invited as guest lecturer for lab to market capstone courses to speak on topics of product management, general management, and technology trends

I managed to work my way through all four years of college while achieving Provost honors.

Warren College - Minored in Japanese Language and Studies.

Hi, I'm Marcos Rivera

•  I have 25+ years of pricing expertise in Tech
•  I was the Head of Pricing for Vista Equity Partners
•  I have helped price 400 products...and counting​
•  I teach pricing confidence from MBA students to world-class CEOs
•  I am an award-winning author, speaker, investor, and entrepreneur

Here's My Story in a Nutshell

I was raised by a single mother in a one-bedroom apartment in the Bronx. The streets were hard on me, but I survived by applying what my mom taught me:  Stay curious, take the lead, and give help.

Fast forward to today, Software as a Service has transformed almost every business, from music to marketing to medicine. I learned a lot straddling dual roles as a product executive and pricing expert my entire career, but my AHA moment came to me after noticing an unwavering pattern:

Most B2B SaaS leaders spend time building value but not enough time capturing it!

So in the spirit of staying curious, I discovered that many B2B SaaS leaders see pricing as a "black box"; they guess, fumble, and wing it most of the time.  They needed help!

From there, I decided to take the lead and help B2B SaaS businesses by dedicating a practice that teaches them step-by-step directions for monetizing value and unlocking growth.

And this is where our story begins. Join us and take control of your most powerful growth lever - Pricing.  It would be my honor to help you! Send me a DM or head to our website: www.pricingio.com

You can also order my debut book, Street Pricing: A Pricing Playlist for Hip Leaders in B2B SaaS (link in bio)

Go capture that value!

Marcos

For this benchmark report, PricingSaaS has examined over 400 B2B SaaS companies across 10 different categories to uncover AI monetization strategies, usage based pricing metrics and created a recap of changes in Q1 of 2024.

We hope you find it helpful and insightful.

2024 B2B SaaS Pricing Q1 Benchmarks & Models

Pricing I/O is a training and coaching boutique helping high-growth B2B SaaS companies accelerate ARR growth and market share. We unlock growth by taking a simple, powerful, and easy to understand approach to monetization – we call this approach the 5Q Pricing Framework.

Pricing I/O: Your B2B SaaS Pricing Experts

25 years of pricing. 500+ SaaS companies.
One conversation where I held nothing back.

Rohit asked me the questions most people are afraid to ask:
→ What's the single biggest pricing mistake you see repeated?
→ How do you know if it's a pricing problem or something else?
→ Should AI features be bundled or priced separately?
→ What made you change your mind on pricing cadence?

I shared the 100x growth story I don't tell often.

Admitted where I got it wrong.

And broke down how to actually think about pricing AI, not the theory, the real decisions.

If you've got 35 minutes, this one's worth it.

Watch the full episode of The AI Pricing Podcast ↓
https://skd.so/OCIaV6

Should you charge for AI separately or bake it into the product?
I get this question constantly. 

And the honest answer is: it depends on what your AI actually does.

I've seen companies destroy expansion revenue by giving AI away for free when they should have charged. 

I've also seen companies kill adoption by charging separately for AI that should have been invisible.

The mistake is thinking there's one right answer. There isn't.

After working through this with dozens of companies, from $10M ARR startups to PE-backed portfolio companies, I keep coming back to three distinct approaches.

The first works when AI enhances the existing experience. 
Makes things faster, smarter, better, but the job-to-be-done is the same. 

Think autocomplete, smart suggestions. 
In this case, don't charge separately. 
Bake it in and raise prices across all plans.

The second works when AI unlocks adjacent use cases. 
Same user, but now they can do something they couldn't before. 
This is your premium tier or add-on play.

The third works when AI creates entirely new users or workflows. 
Different audience, different product. 

This needs its own identity, maybe bundled, maybe standalone.

The question isn't "should we charge for AI?" It's "where does AI create value, and for whom?"

Which of these three describes your AI?

Most SaaS companies treat usage limits as technical guardrails.
Big mistake.

They’re your upgrade engine.

Data retention windows. 
Source limits. 
Processing hours. 

These aren’t just product constraints, they’re monetization strategy.

The key: Set limits where customers naturally hit them as they get MORE value. Not where they get frustrated.

When customers hit limits, they’re succeeding. That’s when they upgrade.

Here’s what that looks like:
→ Starter: 3 sources, 30-day retention
→ Pro: 10 sources, 90-day retention
→ Enterprise: Unlimited, 1 year+

That structure creates a $47K ARR expansion path per customer.
These should feel like growth milestones, not arbitrary restrictions.

What usage limit is driving the most upgrades in your model?

Your packaging model isn't broken because it's "wrong."
It's broken because you outgrew it.

Here are 5 signals I see when companies need to evolve their packaging:

1. Sales is discounting on every deal to "make it fit."

When your tiers don't match how customers buy, reps start hacking. Custom bundles. Creative discounting. Anything to close.

That's not a sales problem. It's a packaging problem.

2. Customers cluster in one tier while others sit empty.
If 80% of customers are in your middle tier and the other two barely move, your packaging isn't giving them a reason to choose.

3. You're building features no one's paying for.
Product ships something great. It gets buried in "Enterprise." No one upgrades for it.

That's a signal the feature deserves its own packaging conversation.

4. Expansion revenue is flat even though usage is up.
Customers are using more. Getting more value. But NRR isn't moving.

Your model isn't capturing the growth happening inside accounts

5. The pricing conversation dominates every sales call.
When customers spend more time asking "what's included where?" than talking about their problems, packaging is creating friction, not reducing it.

None of these mean you picked the wrong model.
They mean your business evolved and your packaging didn't keep up.

Here's the thing about packaging: it's not a one-time decision.

Companies that treat it like infrastructure instead of a living system end up stuck, either too rigid to capture value or too complex to sell efficiently.

The best packaging matches your stage. 
And as you grow, it should grow too.

I'm a co-founder & CEO of Schematic -- an entitlements and monetization platform built on top of Stripe Billing. 

Our thesis is that AI transforms B2B monetization. 

SaaS monetization was static & seat-based. 

AI monetization is hybrid pricing & hybrid selling across multi-product offerings. 

Developers shouldn't have to reinvent the wheel when it comes to implementing & maintaining pricing & packaging. Product & growth folks should be able to control and iterate on monetization without code changes. They should be able to operate with speed and easily align their product roadmaps with continuous pricing & packaging releases. 

The future of monetization looks far more like telecoms in the 90’s than SaaS in the 2010's.

Enough about that.

As a kid, I wanted to play professional soccer, and I pursued that into my early 20’s, playing collegiately & then semi-professionally. 

My professional journey off the field began with a community visioning campaign to help continue Chattanooga TN’s revitalization, then a short, but formative stint with an edtech startup, which got me interested in startups, and then a year at a fund of hedge funds, before founding my first company in 2012, RootsRated.

Founding RootsRated kicked off what has now been a 15-year journey into building startups. RootsRated began as a go-to site for outdoor recreation and adventure travel. We later pivoted to SaaS, launched Matcha, a content marketing platform, and eventually, were acquired by Springbot, an email marketing service. 

After Matcha, I joined Automox, a leading ITOps platform, where I wore multiple hats—Director of Growth, Chief of Staff, and VP of Ops. Among other things, I led pricing at Automox, which led to the founding of Schematic. 

I grew up in Chattanooga, spent the last ~7 years in Atlanta which is one of the great cities, and recently moved to Colorado with my wife, two kids, and two dogs. Attended the University of Richmond, captained the soccer team, and studied International Relations & French (though my French has since atrophied). 

Outside of work, I enjoy trail running and becoming a cycling addict. Occasionally share my thoughts on history and technology on Substack.

Monetizing SaaS:
- Youtube: https://www.youtube.com/@schematichq
- Spotify: https://open.spotify.com/show/5yjegk5duBz3LtvjwOo8ai
- Apple: https://podcasts.apple.com/us/podcast/monetizing-saas/id1757006729

Fynn Glover

the first physical copies of "You're Leaving Money on the Table - How to Create Leverage with Pricing" just arrived. 

first book i've written. really cool to see it in print.

thanks to the many folks who helped bring this together!

Podcast dedicated to stories from operators about monetization, pricing, and packaging in the world of B2B SaaS

Monetizing SaaS

Co-founder & CEO of Schematic | helping SaaS & AI startups monetize smarter and faster

I'm a co-founder & CEO of Schematic. It's far too complex for startups to monetize features and manage subscriptions. Schematic is the fastest way for the next generation of startup and AI developers to implement and manage pricing. Feature flags, access control, plan & subscription management, metering, and drop-in billing components -- all in one. 

As a kid, I wanted to play professional soccer, and I pursued that into my early 20’s, playing collegiately & then semi-professionally. 

My professional journey off the field began with a community visioning campaign to help continue Chattanooga TN’s revitalization, then a short, but formative stint with an edtech startup, which got me interested in startups, and then a year at a fund of hedge funds, before founding my first company in 2012, RootsRated.

Founding RootsRated kicked off a decade-long journey into building startups. RootsRated began as a go-to site for outdoor recreation and adventure travel. We later pivoted to SaaS, launched Matcha, a content marketing platform, and eventually, were acquired by Springbot, an email marketing service. After Matcha, I joined Automox, a leading ITOps platform, where I wore multiple hats—Director of Growth, Chief of Staff, and VP of Ops. Among other things, I led pricing at Automox, which led to the founding of Schematic. 

I grew up in Chattanooga, spent the last 6 years in Atlanta which is one of the great cities, and recently moved to Colorado with my wife, two kids, and two dogs. Attended the University of Richmond, captained the men’s soccer team, and studied International Relations & French (though my French has since atrophied). 

Outside of work, I enjoy trail running and cycling, and occasionally share my thoughts on history and technology on Substack.

Monetizing SaaS:
- Youtube: https://www.youtube.com/@schematichq
- Spotify: https://open.spotify.com/show/5yjegk5duBz3LtvjwOo8ai
- Apple: https://podcasts.apple.com/us/podcast/monetizing-saas/id1757006729

Youssef Salah

What would happen to your business if you allocated just 10% more of your time to turning pricing & packaging into something your company is exceptional at?

Pricing is 50% of the revenue equation. 

Price x quantity = revenue. 

And yet, most companies spend 95% of their time focused on only the "quantity" side.

We obsess over how many times we can sell the product, while the "Price" half of the equation remains a static intuition.

Pricing is a living, breathing thing, just like your product. 

It's a muscle you have to develop, train, and strengthen continuously to unlock its leverage.

If you’re better at sales, product, or engineering than you are at pricing... ask yourself why.

Pricing is half the battle. 

Make 2026 the year that you treat it like the mission-critical discipline it is.

And leave a lot less money on the table.

Price is a number. Pricing is an architecture.

Most founders blame their billing tool when they can't launch new pricing fast enough.

They're looking at the symptom, not the cause.

The real problem? A broken pricing architecture.

I learned this the hard way at my last company. We had:

Stripe for self-serve

NetSuite for enterprise

Salesforce for our pricebook

Amplitude for usage analytics

Hard-coded entitlements scattered across the code base. 

A homegrown metering system nobody trusted

Six disconnected systems. Thousands of lines of billing code. One tier launch took six months. An add-on initiative was abandoned entirely.

As Jalal Iftikhar from Notion puts it: "The real issue is the inability to slice and dice offerings, test and segment, iterate, and learn. Usage-based billing systems are designed to consume events and inform invoices. They're not designed to enable the commercial tinkering that drives growth."

The architectural imperative is clear.

Your pricing system needs key pillars. 

Unified Product Catalog – One schema for every plan, feature, and price across all systems

Decoupled Entitlements – Business logic separated from product code

Real-Time Metering – Transparent usage tracking that calms CFO anxiety

Company Profiles - Easily manage customer lifecycle across access, usage, upgrades, exceptions, etc. 

GTM Control Plane – Non-engineers can iterate on monetization

The result? Companies like Plotly ship & monetize AI products two quarters faster.

Kurt Smith from Fexa said something I think about all the time: 

"Think about all the creative pricing conversations that have simply stopped happening, because people have accepted that their systems make testing impossible."

In the AI era, pricing agility = revenue agility.

The winners will treat pricing like product. They'll architect for continuous iteration, not annual overhauls.

Your architecture determines your strategy. Invest accordingly.

Great pricing isn’t a number. 

It’s an exchange rate between: 1) what customers get; and 2) what they’re willing to pay. 

The mistake I see most teams make is misunderstanding how their product delivers value worth paying for. 

A good way to figure this out is to splice and dice your product and run two simple matrices with real customers:

1) Usage Value: How often is each capability actually used?

2) Perceived Value in Buying: Which capabilities are must-haves vs nice-to-haves vs irrelevant?

Plot them on a 2x2 and four things emerge immediately:

1. Leaders (high usage, high value): These anchor your paid tiers. Put limits here.

2. Fillers (high usage, low value): Table stakes. Required, but not necessarily monetizable.

3. Detractors (low usage, low value): Noise. Cut them or bury them.

4. Add-ons (low usage, high value): Loved by a subset. Perfect for enterprise or expansion.

This 2x2 is your packaging strategy.

Your leaders drive conversion. 

Your limits & add-ons drive expansion.

Pricing & packaging drives growth when it’s designed to move with customer behavior. 

If you want the template I use for this with customers, comment template, and I'll send over.

Our friends at PricingSaaS tracked 498 companies throughout 2025 and just released their findings. The numbers tell an interesting story:

- Packaging changes up 21% YoY
- Credit-based models up 126% YoY
- AI features shifting from add-ons to core plans

The report includes 50+ real examples with before/after screenshots from companies like Atlassian, Figma, Anthropic, and Canva.

We contributed our perspective alongside some of the most thoughtful thinkers in SaaS monetization.

If you're planning any pricing or packaging changes in 2026, this is worth 15 minutes of your time.

Incredible work from Rob Litterst and John Kotowski!

Link to the report in comments.

a founder i was speaking with today was discussing their pov on craft. 

made me think about examples of craft that have motivated me...

here are a few that i think about pretty regularly:

1. jim harrison's novellas

2. the way beckham can strike a ball

3. jonas vingegaard's mountain climbing technique, strategy, and guts

4. Linear's approach to product development

5. Andrew Johnston's approach to selling by way of listening & inquiring. Also RevenueCat's.  

6. pixar's ability to light up imagination at any age

7. litespeed's titanium bicycles 

8. nate bargatze's humor

9. redbull's content marketing 

10. toyota's delivery of insane consistency & reliability

chatting with a customer in SF yesterday where we were asking them what's the worst part about using schematic. 

one of the best ways ive found to improve. 

then we started talking about what's happening in monetization for both AI startups and enterprises launching AI products.  

this is all changing so quickly, but here's how i'd synthesize what i think it is we're all seeing & feeling in terms of jobs to be done. 

1. launch initial monetization (often credits)

2. stop the bleeding with basic limits

3. there's a transparency arms race to deliver great billing ui and customer portals

4. telemetry, both in terms of costs and churn/expansion signal

5. need to iterate and experiment with pricing models and with packaging more then ever before

if you're building ai and figuring out monetization, how would you edit this?

Super excited about what Vladik Rikhter and Tim Olshansky are building. And for their partnership. We're psyched to support their monetization.

CEO & Co-Founder Fencer | The Security Suite for Startups

🚀 Tim Olshansky and I are thrilled to unveil Fencer - the best security suite for startups (yes, we’re serious, it’s the best!) 

We’ve spent the last 16 months building Fencer with a great team and a couple dozen beta customers. Now we’re opening up to the rest of the world.

At Zenput, enterprise security requirements entered the picture early. When we had fewer than 30 employees, SOC 2 compliance became a prerequisite for revenue growth, and there was no clear, simple solution to help us get there. 

Startups shouldn’t have to juggle 10 different vendors, use non-developer friendly tools, or spend weeks trying to deploy solutions. Security should be simple and accessible for startups, and that is the big idea behind Fencer. 

As one of our customers said: 

“I like to think of Fencer as our co-pilot to help us manage security. Almost like a colleague that nudges us when we're writing code that might not be secure, telling us when an AWS change might have a vulnerability, and monitoring and ensuring that our systems are working in the background as intended and in a secure way.” Prithvi Narasimhan from Rely Health.

Here’s what we’re bringing to the table:

- Unified vulnerability detection and remediation support covering code, attack, surface, cloud infrastructure, and endpoints.
- An integrated SIEM 
- Connections with GRC tools (shoutout to Vanta & Drata) that streamline audit prep

💰 We’ve raised $5.5M from MHS Capital, Goldcrest Capital and a lot of great operators/founders: Shyam R., John Clarke Mills, Satjot "SJ" Sawhney, Harman Singh Narula, Jeff Kahn, Ari Baranian, Alok Chanani, Jackson Noel, Idan Perez 🐙 , David Karel, Nikki Perry, Josh Breinlinger, Robert Sverbilov, Michael Monu, Ash Fontana, Gene Karshenboym, Albert Bielinko, Ben Wheeler, & Gene A. Glekel amongst others.

If you've recently achieved SOC 2, ISO 27001, or HITRUST certification — or already hold one of these — send me a message, reply in the comments, or check out the site:

Open article: Fencer: Integrated Security Platform for Startups by fencer.dev

Fencer: Integrated Security Platform for Startups

Incredibly thoughtful post from my friend Kayvan Dastgheib-Beheshti. thank you sir!

VP GTM Operations @ Payscale | Top RevOps Mentors 2026, 2025, 2024 | Pavilion RevOps Leader of the Year Finalist

View Kayvan Dastgheib-Beheshti’s profile

This might be a surprise, but your product catalog is the forgotten product.

When Fynn Glover asked me about the biggest monetization bottleneck in SaaS, my answer was immediate:

"The product catalog itself."

Here's what is often forgotten entirely - the product catalog and entitlements are as much a product as your actual product. Together, they govern how you monetize. Yet most companies treat them as an afterthought.

I see this pattern everywhere:

Your CRO looks at CPQ as the source of truth. Your CFO looks at the billing system. Your CTO/CPO looks at your database. Your CS leader looks at the admin panel or your CS tool.

Four teams. Four sources of truth. Zero coherence.

The result? Every pricing change becomes a cross-functional nightmare. Engineering files tickets or redeploys. Finance reconciles discrepancies, and points to historical revenue recognition. Sales & RevOps operate with outdated information or rigid legacy structures. Product lacks visibility into the financial impact of their roadmap. It's extremely manual to manage customer lifecycle. 

The structural flaw is simple: businesses under-appreciate that the product catalog needs to be a singular source of truth that orchestrates changes across the entire quote to cash stack. 

As Fynn writes in his new book, You're Leaving Money on the Table, the solution is starting with a unified product catalog that serves as the canonical source for packaging, pricing, provisioning, and analytics. 

One schema. One truth. Everywhere.

When you get the architecture right, speed follows. In 2026, pricing agility IS revenue agility.

Highly recommend that RevOps leaders work cross-functionally to end siloed product catalogs and start treating your product catalog like the revenue-critical infrastructure it is.

Startup Advisor • Growth Leader • Superhuman • Advisor @ Clay, Replit, Wispr Flow, Superpower & others

This is what $1bn looks like.

$1,000 in cash on the table.
$999,999,999,000 in insights from the book.

You're Leaving Money on the Table
How to Create Leverage with Pricing
by Fynn Glover

A field guide to pricing that every founder should read.
Because your startup won't be a unicorn if you get pricing wrong.

If you'd like a copy:

1. Like this post
2. Comment "book" and I'll send it over

4 good times to use WTP & rule of thumb is to hold these conversations on consistent basis to continuously learn. 

1. Pre-product & want to test viability of your solution

2. Working to close design partners/early customers and need to determine price they are willing to pay

3. 6-12 months into a contract with a healthy customer to better understand your value to them

4. Ahead of a meaningful P&P change post PMF

SaaS margins dropped from 90% to 50% with AI.
It’s time to reconsider pricing.
But that's easier said than done.

Most founders panic when it's time to talk pricing with customers.
They overthink it. They undersell.

They lose deals not by asking too much, but by failing to understand what customers actually value.

Fynn Glover has conducted countless willingness-to-pay interviews over the last 2.5 years. He's also trained hundreds of founders on this skill.

His take is simple: willingness-to-pay conversations are critical for finding Product-Market Fit. He calls these talks “pricing therapy.”

Here's his repeatable flow:

1/ 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 & 𝐅𝐫𝐚𝐦𝐢𝐧𝐠
Explain your product's promise. Get the buyer in the right mental model.

2/ 𝐏𝐞𝐫𝐜𝐞𝐢𝐯𝐞𝐝 𝐕𝐚𝐥𝐮𝐞
Ask what problems they think it solves, and which features feel indispensable.

3/ 𝐑𝐞𝐥𝐚𝐭𝐢𝐯𝐞 𝐕𝐚𝐥𝐮𝐞
Compare your value to the tools they already pay for to gauge worth.

4/ 𝐏𝐫𝐢𝐜𝐞 𝐌𝐞𝐭𝐫𝐢𝐜
Explore which metric best maps to their perceived value (seats, usage, etc.).

5/ 𝐏𝐚𝐜𝐤𝐚𝐠𝐢𝐧𝐠 𝐒𝐜𝐡𝐞𝐦𝐚
Show draft tiers and ask what resonates and what feels off.

6/ 𝐌𝐚𝐱𝐢𝐦𝐮𝐦 𝐖𝐓𝐏
Ask for the max they'd pay, either open-ended or scenario-based.

7/ 𝐈𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐞 𝐃𝐫𝐢𝐯𝐞𝐫𝐬
Uncover the real factors: budget, comparables, frequency, stakeholder buy-in.

8/ 𝐅𝐞𝐞𝐝𝐛𝐚𝐜𝐤 & 𝐄𝐦𝐨𝐭𝐢𝐨𝐧
End by asking how the conversation felt. Listen for discomfort, not just answers.

Make sure your interview is conversational, not static. 

Conducting PMF conversations should never stop.
They should occur when you're pre-product, after you've won initial customers, and on an ongoing basis as you extend and deepen your fit.

Pricing isn't just a number you stick on the product.
It's a conversation about value, confidence, and how well you've done your homework.

🎓 New article packed with actionable pricing frameworks: https://lnkd.in/dW_hDJYi
1. The “wirecutter” guide to modern pricing models with examples
2. How to conduct willingness to pay research - aka “pricing therapy” interview with 8 questions to ask
3. Anatomy of a great pricing page

How do you talk pricing with your customers?

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