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?

Your top 20% of customers are probably subsidizing your bottom 30%.
And you don't even know it.

See the #2 cause ↓

When we audit customer bases, we find this constantly: the customers who get the most value and never churn are often paying less than the customers who churn after 12 months.

Why?

Because most companies optimize pricing for customer acquisition volume, not for customer value fit.

You built pricing to attract as many customers as possible. 
So you attracted a lot of price-sensitive customers who were never going to be good long-term fits.

Meanwhile, your best customers, the ones who would happily pay 2-3x more because they're getting massive value, are grandfathered on old pricing.

The framework shows how to identify this pattern in your own customer base and fix it.

When we help clients migrate their high-value, under-monetized customers to pricing that reflects the value they're getting, we see 30%+ expansion revenue.

From customers who were already happy. 
They just needed a reason to pay more.

Are you optimizing your pricing for volume or value fit?

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

Years of calls, DMs, and pricing debates.
Finally in the same room.

Dan Balcauski, • Mark Stiving, Ph.D., and I have known each other for years through the pricing world. 

We've shared ideas, challenged each other's thinking, and watched the space evolve together.
But somehow, we'd never all been in the same place at the same time.

Until the Usage Economy Summit last week.

Pricing work can feel isolated. 
You're often the only person at your company who thinks about monetization strategy all day. 
The pricing community changes that.

These are the people who get it. Who've been in the trenches. Who know that pricing isn't just a spreadsheet exercise.

Good to finally make this photo happen.

This is Peter. He looks nice, but he challenges me all the time. 
And honestly? It makes our work better.

Here's the kind of thing we debate constantly:

We're reviewing a client case. High churn. Customers leaving after their first year. The executive team suspects it's a product problem.

The data tells a different story:
→ Legacy customers on old pricing? Staying longer. Making the most money. Seeing the most value.
→ New customers on "optimized" pricing? Churning at exactly 12 months. Citing ROI mismatch.

My take: "This is a pricing problem. The model doesn't align with value realization."

Peter's the first to push back on takes like this:

"Sometimes it really IS a product problem, Marcos. Sometimes the product just doesn't deliver enough value."

And he's right. Sometimes it is.

But here's how you know the difference:

If your legacy customers love the product and your new customers churn, it's not the product. It's the pricing.

The product didn't change. 
The pricing did.

The value is still there. 
Your pricing model just stopped aligning with how customers realize it.

This is what I love about our team at Pricing I/O.
We try to challenge ourselves:
→ Why that value metric?
→ What happens to expansion revenue?
→ Did you pressure-test this with sales?
→ I disagree with this segmentation, here's why.

It's not personal. It's rigorous.

Our best client work comes from these debates.

Because when smart people disagree about pricing strategy, that's where the real insights live.

The best pricing strategies aren't created in isolation.

They're forged when you put smart people in a room and force them to defend their thinking.

When you ask hard questions. 
Challenge assumptions. 
Stay willing to be wrong.

That's how you avoid the "drop decks and disappear" trap most consultants fall into.

If we can't defend a strategy to our own team, how can a client defend it to their board?

Across 400+ companies, this pattern repeats:
Pricing that worked at launch stops working as you evolve.

The winners don't treat pricing as a one-time project.
They build the muscle to test, learn, and adapt.

Do you have a process for pressure-testing big decisions?
Or are you making them in isolation?

Seat-based pricing is dying faster than most CEOs realize.

12 months ago: 50% of B2B SaaS used flat or seat-based models 

Today: Down to 27% 
Projected 2027: <10% 

The shift? 41% of companies are now using hybrid pricing models.

At SaaS Metrics Palooza, I walked through why this is happening, and the framework we use to build hybrid models that actually work.

Here's the reality:
AI changed who does the work.

It's not just humans anymore. It's systems completing tasks, generating summaries, resolving tickets, approving requests, all autonomously.

So how do you charge for that? By the person? The product? The outcome?

Answer: It depends on who's doing more of the work.

The BAM Framework - Base, Allowance, Meter 

These 3 layers create 5 different hybrid pricing models:

1/ Access Tiers (Base only) - Different AI complexity per tier, fair usage policy 

2/ Flat + Unit (Base + Meter) - Platform fee + outcome-based hybrid pricing 

3/ Flat + Limit + Unit (All 3 layers) - Most popular hybrid, includes volume + overages 

4/ Credit-Based (Base + Allowance) - PLG favorite hybrid, but don't fall into cost-plus trap 

5/ Pay-As-You-Go (Meter only) - Pure consumption, AI infrastructure 

The pattern from 400+ transformations: 
Companies using Flat + Limit + Unit (Model 3) are seeing the most traction. Why?

It gives customers predictability (base fee + included volume) while capturing expansion value (usage after allowance).

But, and this is critical, you need safety mechanisms.

→ Predict usage (dashboards, estimators) 
→ Prevent surprises (match reset timing to contracts) 
→ Protect customers (caps, true-up options, don't penalize usage) 

The companies winning with hybrid pricing aren't just picking a trendy model. They're designing the model that fits how their AI actually creates value.

Based on Tremont's research:
Hybrid models are capturing 3-4x more expansion revenue than traditional seat-based pricing.

The question isn't "should we go hybrid?"
It's "which hybrid model fuels OUR growth?"

Which model fits your product? Person doing the work or product doing the work?

Seat_Based_Pricing

At Vista Equity Partners, I learned something that changed how I think about pricing forever.

It wasn't about finding the "perfect price point."

It was about understanding how pricing connects to valuation multiples.

Here's what that looked like in practice:

We'd acquire a portfolio company and immediately audit their pricing. Not to squeeze more revenue out of customers, but to understand if their pricing model supported the growth thesis.

The companies with tight discount controls, clear value-based packaging, and pricing aligned to customer outcomes? They consistently outperformed on valuation multiples.

The ones with ad-hoc discounting, feature-based tiers, and "we charge what competitors charge" mentality? They left millions on the table.

One pattern I saw repeatedly: the pricing model that works for a Series B company scaling the business is completely different from a $100M ARR company optimizing for profitability pre-IPO.

There's no one-size-fits-all.

That's why I started Pricing I/O. To bring that PE-level rigor to growth-stage SaaS companies, without the $1 million McKinsey price tag and 9 months of PowerPoint slides.

We deliver results in weeks, not quarters.
We work in the trenches, not from ivory towers.
We teach teams to own pricing, not create dependency.

Because pricing isn't a one-time project. 
It's a strategic function that evolves with your business.

What's one pricing lesson you wish you'd learned earlier?

li_at

JSESSIONID

63% of AI monetization barriers are pricing-related.
And here's the #1 question I get from CEOs: "Where does AI actually belong in our pricing?"

Most companies are guessing. Chargebee's research shows 29% are just building AI into the core without charging extra.

That's a mistake.

At SaaS Metrics Palooza, I broke down the framework we use with PE-backed companies to decide where AI belongs.

It's not about the technology. It's about the experience.

Three different AI experiences = three different packaging strategies:

1/ Underscore the Core - When AI reinforces what you already do
Slack started with AI as a $10/user add-on. A few months later? Built into Business+ with a 25% price increase.

Why? They realized AI was becoming core to the Slack experience—making search better, recaps faster, answers easier. Not a "nice to have" feature.

2/ Upgrade the More - When AI extends adjacent use cases
ClickUp Brain charges $28/user (their base plan is $7). That's 4x their standard pricing.

Sounds expensive until you realize it's replacing 3-4 other AI productivity tools at $25-30 each. For customers, $28 is a consolidation play and a bargain.

3/ Unlock the New - When AI creates entirely new workflows
Intercom's Fin resolves support tickets autonomously at $0.99 per resolution. 
New TAM, new use case, standalone product.

Those who package based on experience (not just "it's AI so charge more") capture 2-3x more value and see 40% less pricing pushback.

The mistake? Treating all AI features the same.

Your AI that makes existing workflows 10% faster ≠ Your AI that unlocks entirely new capabilities.

Where does your AI actually belong?

McKinsey published a 4000-word guide on AI pricing. 
They're right about the problem. Wrong about the solution.

After analyzing 150 AI vendors, they found that despite $4.4trillion in potential economic value from AI, less than 1% of software spend is actually going to AI products today.

Why? Three consistent blockers: only 30% of companies publish quantifiable ROI, CFOs can't forecast what they'll spend on AI quarter to quarter and pilots fail to scale without proper change management investment.

I agree with all of this. We're seeing the exact same patterns across our 400+ client benchmark.

But here's where McKinsey loses me.

Their solution: "Test with customers and iterate quickly." That's not a strategy. That's expensive guessing.

Here's what I told a $75M ARR CEO who was about to "test" three different AI pricing models:
"You can't test your way to the right pricing without first understanding which experience you're selling."

→ Are you underscoring your core product? 
(AI makes existing workflows faster/better) 

→ Upgrading adjacent use cases? 
(AI extends what you do into new territory) 

→ Or unlocking entirely new capabilities? 
(AI creates workflows that didn't exist before)

That decision shapes everything, your packaging structure, pricing metric, go-to-market motion, whether you embed or sell standalone.

McKinsey's "iterate quickly" approach skips this question entirely.
So companies end up testing random combinations. 

"What if we bundle it?" 
"Let's try consumption-based." 
"Should we do per-seat or per-action?"

Each test costs 3-6 months and thousands in opportunity cost. This is the difference between consultants who drop decks and consultants who work in the trenches.

A 200-page McKinsey deck will tell you that 41% of companies are moving to hybrid models and you should "test and iterate." Great. Now what?

Working in the trenches with your team means asking: What experience is your AI actually creating for customers? Then designing the pricing model that monetizes that experience.

Not copying what Salesforce or Snowflake is doing. Not testing five models and hoping one works.

Companies that got AI pricing right didn't test their way there. They designed the experience first, then built pricing around it.

→ Slack realized AI was becoming core to the messaging experience, built it into Business+ with a 25% price increase. 
→ ClickUp saw AI extending productivity workflows, charged $28/user as an add-on to consolidate other tools. 
→ Intercom built AI that automated support entirely, 99¢ per resolution, standalone product.

Three different experiences. Three different pricing strategies. All intentional from Day 1.

McKinsey is right that this is the biggest shift in software since SaaS. But "test and iterate" isn't how you capture the opportunity.

Context without expertise is aimless. Expertise without context is pointless. You need both.

The discount death spiral: one deal at 30% off, another at 35%, your average hits 25%. 

Across 400+ SaaS companies, we see this pattern destroy margins and valuation multiples. 

Here's how PE-backed companies fix it with a 3-tier approval process. 

Full breakdown here 👆

McKinsey found that successful AI pilots require $3 in change management for every $1 in model development.

Most companies spend $0 on change management.
Then wonder why pilots don't scale to production.

After analyzing 150 AI vendors, McKinsey identified "sustained adoption" as the #3 blocker to AI monetization (behind value communication and price predictability).

Here's what's happening:

Companies invest heavily in building AI capabilities. Model development, infrastructure, data pipelines, millions of dollars.

Then they launch to customers and assume adoption will just happen.
It doesn't.

Without forward-deployed engineering, employee training, performance monitoring, and process integration, teams don't change their workflows. The AI sits unused. No ROI gets proven. Contracts don't renew.

The $3-for-$1 rule is McKinsey's finding from companies that successfully scaled AI pilots. For every dollar spent building the model, they spent three dollars on change management.

But here's what most pricing discussions miss:
Adoption friction isn't just an operations problem. It's a pricing problem.

This is the "L" in the REAL framework I shared at SaaS Metrics Palooza—Lift. How much effort does the customer need to invest to get value?

The more friction, the less pricing power you have.

→ High friction (3-6 months to value) means customers are skeptical. They want pilots. They negotiate hard. They're not willing to pay premium prices for something they're not sure will work.

→ Low friction (2-3 weeks to value) means customers see results fast. They're confident. They're willing to pay 2-3x more because the risk is lower.

Last month, I worked with a company that cut their AI onboarding from 12 weeks to 3 weeks through better change management, pre-built integrations, forward-deployed engineers, structured training.

Their close rates went up 40%. But they forgot to reprice.

They were still charging based on the old 12-week implementation timeline. Leaving money on the table.

Many companies forget to revisit pricing after they've reduced adoption friction. If you cut implementation time by 75%, you should be capturing more value, not the same amount.

Based on our 400+ client benchmark, companies that systematically reduce adoption friction and reprice accordingly capture 2-3x more revenue per customer than those who just focus on the product.

The pattern: 
Invest in change management → Measure time-to-value improvement → Reprice to reflect lower friction.

Adoption friction directly impacts pricing power.
Lower the friction, raise the price.

Are you investing $3 in change management for every $1 in AI development? 
Or are you building capabilities no one will adopt?

AIPilots

Your economics typically won't be as great out of the gate when it comes to AI, but the path to make it better over time is gonna be the key.

I shared this at SaaS Metrics Palooza because too many SaaS leaders are panicking about day-one AI pricing economics instead of building the right improvement path.

Here's the specific framework I shared:

Secondary limits that actually work:
→ Cap data sources (5 basic, 15 pro, unlimited enterprise)
→ Retention windows (30/90/365 days by tier)
→ Processing limits (hours per month, API calls)
→ Response time SLAs (24hr/4hr/1hr support)

The credit bonus math:
Instead of $1,200 ARR at $80/month (20% discount)
Do $1,200 ARR at $100/month + 20% usage credits

Same customer investment, but you protect pricing integrity and create margin expansion as they grow into those bonus credits.

Use this 3-step process as your 30-day action plan ↓

What secondary limit will you implement first?

Pricing

LLM costs have dropped 80% annually for two straight years.

Most AI companies responded by lowering prices or making features "unlimited."

McKinsey's research on 150 vendors shows that's the wrong move. 
Companies that maintained or raised prices despite falling costs saw 2-3x higher revenue growth than those who passed savings to customers.

Yet most are doing the opposite.

Jasper AI went from $10 per 5,000 words to unlimited generation included free. Sounds customer-friendly. But here's what that misses:
Your AI isn't getting cheaper. It's getting more valuable.

Two years ago, AI did single-step tasks, generate an email, summarize a doc, answer a question.

Today, AI agents execute multi-step workflows autonomously. Research across databases, draft outreach, update CRM, schedule follow-ups.

Your costs dropped 80%. 
Your complexity increased 10x.

Customers don't pay for compute. They pay for outcomes.

Adobe got this right. 
Started with embedded AI and simple features. 
Moved to standalone SKUs at higher prices as they added video generation, translation, and complex workflows.

Their costs went down. Their prices went up.

Q1 2025: $125M in AI revenue, expecting to double by year-end.

Only 16% of SaaS companies commercialized AI as standalone products. But those 16% report 2-3x higher customer traction and revenue.

The pattern across companies getting this right: costs fall, prices stay flat or rise with added capabilities. 

Use margin gains to add complexity, better integrations, multi-step workflows, higher quality.

Price based on value delivered, not costs incurred.

Based on our 400+ client benchmark, companies that maintain value-based pricing during falling infrastructure costs capture 4-5x more economic value.

Falling LLM costs are a margin opportunity, not a customer discount.

Question for your team: Are we pricing our AI based on the value customers get, or the costs we incur?

Most B2B SaaS companies are about to copy their way into a churn crisis.
This is the conversation I'm having with CEOs and boards 3x per week.

I just watched a $50M ARR company copy a competitor's usage-based pricing model.
Six months later: CAC up 60%, churn jumped from 8% to 14%, sales cycles doubled.

What works at scale can destroy an early-stage company.

Before you change your pricing model, answer these three questions:

1. How do your customers actually consume value?
Not how you think. How they actually behave.

CRM where value scales with team size? Per-seat still works.
Data platform where value comes from queries? Usage-based fits.

2. What's your sales motion?
High-touch enterprise sales can handle complexity.
PLG with self-serve? If prospects can't understand their cost in 30 seconds, you've lost them.

3. What's your growth stage?
Series A proving PMF needs different pricing than $100M ARR pre-IPO.

The shift from license-based to outcome-based pricing is real.
But context without expertise is aimless, and expertise without context is pointless.

Just dropped a video about it ↓

https://lnkd.in/gNGqitFU

I break down the complete framework, why AI is accelerating this shift, how to model impact before launch, and how to test without blowing things up.

You don't hire consultants because you have a strategy.
You hire them because you don't.

A CPO told me recently:
"The team wants to start quickly. They have urgent things they're nervous about because nobody knows what they're doing, bluntly."

Not "we're pursuing a strategic initiative."
Just: nobody knows what they're doing and we're scared.

This is how every consulting project actually starts.
But nobody admits it.

Here's what really happens:

Your company launches an AI product. 
Pricing team guesses at a model. 
Three months in, churn spikes. 
Board asks questions. 
Nobody has answers.

Or: Competitor changes pricing. Sales scrambles. Everyone has opinions. Nobody has data. CFO demands a strategy by next board meeting.

Or: New product launching in 60 days. Pricing still says "TBD" in the deck. CEO keeps asking "what are we charging?" and the room goes quiet.

That's when you call.

Not because you woke up wanting to "optimize monetization strategy."

Because you're 30 days from a board meeting with no idea what to tell investors about your AI pricing.

Consultants sell transformation.
You're buying panic relief.

When you say "we need to move fast", you're not impatient. You're scared and running out of time.

When you say "the team is nervous", you're admitting you don't have confidence in your approach.

When you ask "how quickly can you start?", you're really asking: how soon can you stop us from making an expensive mistake?

The consultants who get it don't lead with "here's our transformation methodology."

They lead with "here's how we'll de-risk this for you in the next 30 days."

If you're evaluating consultants and the process feels like it's taking forever, this is why.

You need someone to de-risk the urgent thing. 
They're selling you a six-month transformation.

The best projects start by de-risking the urgent thing first. Building the transformation second.

When's the last time you were brutally honest with a consultant about why you're really hiring them?

"We're paying for 20 seats but only 5 people use it."

You're charging per seat. 
But your customers don't get value from the number of seats, they get value from tasks automated, data processed, or outcomes achieved.

This is value metric misalignment. And it's killing your renewals.

Real example: 
AI-powered task automation company charging $50/user/month. 
Customer signs up with 20 seats at $1,000/month. 
But only 5 people actively use it.

They're paying $1,000/month but perceiving $250 worth of value.

At renewal: 
"Why are we paying for 20 seats when only 5 people use this?" 
They churn.

The fix isn't lowering the price. It's changing the value metric.

→ If value comes from tasks automated, charge for tasks, like Zapier does. 
→ If value comes from data processed, charge for data volume. 
→ If value comes from outcomes, charge for outcomes.

When your pricing metric aligns with how customers actually consume value, they can justify the cost.

Across 400+ B2B SaaS companies we've worked with at Pricing I/O, this is the #1 cause of pricing-driven churn.

What's your pricing metric? 
Does it match how your customers actually get value?

$60K for 6 months of value? That's too expensive.
This is how customers justify churning, even when your product works.

I see this pattern constantly: products that require data integration, team adoption, or behavior change take 6+ months to deliver full value.

But companies charge full price from day one.

So at renewal, customers do the math: 
"I paid $60K but only got 6 months of real value. That's $10K/month. Too expensive."

And they churn.

Not because the product failed. 
Because the pricing model didn't account for the time it takes to realize value.

The carousel above shows three ways to fix this: ramp pricing, success milestones, or hybrid models.

The goal? 
Make it easy for customers to justify the cost at every stage of their journey

If it takes 6 months to see full value:
Don't charge full price from day one

The value may be real.
But it takes time to materialize.

If your pricing model doesn't account for ramp time, customers will churn before they see the full value.

Your best customers are paying you 40% less than your worst customers.
And that's why you have a churn problem.

I see this pattern constantly at Pricing I/O.

A CEO comes to us: 
"We've invested millions in product development. Hired more CSMs. Improved onboarding. But our churn rate is still 15%."

So we pull their data.

Legacy customers, 5+ years with the company, love the product, paying 40% less than new customers.

New customers? Churning after 12 months. 
Primary reason: "Can't justify the ROI."

Most CEOs think their legacy customers are just more loyal.
But that's not it.

Your legacy customers are paying less, but they understand exactly what they’re getting for the money.

Your new customers? 
They're paying more, but they can't connect what they pay to what they get.

When we run pricing surveys with churned customers, here's what they tell us:
"We weren't using enough of the product to make it worth it."
"We couldn't justify the cost."
"The ROI wasn't there."

These aren't product complaints. These are pricing complaints.

Your product didn't fail them. Your pricing model did.

If your legacy customers love the product and your new customers churn, it's not the product. It's the pricing.

The product didn't change. 
The pricing did.

Across 400+ B2B SaaS companies, I see this constantly: 
High churn isn't always a product problem. It's often a pricing problem.

Are your best customers paying you the least?

Building a SaaS product is the easy part.
The hard part? 

Knowing what to charge for.
Not how much. What.

I've worked with 400+ companies on pricing transformations, and the most common mistake isn't bad pricing, it's never defining the value metric in the first place.

They default to per-user because competitors do it. 
Or per-seat because the billing system made it easy. 
Or per-transaction because... honestly, no one remembers why.

None of those are strategies. They're inherited defaults.

Here's the question that actually matters: 
What is the thing that, when your customer gets more of it, they're clearly getting more value?

It's not always obvious.

For a fintech client, it wasn't users. It was connected bank accounts, that's what correlated with value delivered.
For others, it might be projects managed, workflows automated, or outcomes achieved.

The right value metric does three things: it scales with customer success, customers understand it intuitively, and it's predictable enough to forecast.

"Per user" used to check all those boxes. But AI is breaking that model.

When automation reduces headcount, when one person can do the work of five, charging per user starts to punish the efficiency you're selling.

I'm seeing companies rethink this now, before their customers start asking why they're being penalized for getting better at their jobs.

What's your value metric? 
And when's the last time you questioned whether it's still the right one?

A client who's known me for years just evaluated five other consultants before hiring me.
That should terrify you.

This week, a billion-dollar SaaS company closed with us on a pricing transformation. 
Their Chief Product Officer and I go way back, we worked together at Vista Equity Partners. 
He knows my work. Trusts me. We literally survived the trenches together.

But when his company needed to hire a pricing consultant, he still looked at six different options.
During our debrief, I asked what made the difference.
He said: "When I did the reference calls, I asked each vendor's clients a specific question: Would you use this consultant for any type of pricing problem, or just this specific one?"
For the other five consultants, clients said: "Actually, they're great at this thing, but not so much at that. For that other problem, I'd probably use a different vendor."
For us: "I'd use them for anything. And have, multiple times."
Here's the uncomfortable truth nobody's talking about:
Your relationship doesn't protect you anymore.
Your client can love you. Trust you. Have worked with you before. And they'll still compare you with five others.
Why?
Because they've been burned by consultants who solved one problem and disappeared. Who dropped 200-page decks and never showed up again. Who created dependency instead of capability.
So now they do real diligence. Doesn't matter who you are.
What decides the deal isn't your pitch. It's what your clients say about you when you're not in the room.
"Would you hire this consultant again? For a completely different problem? Or just this one?"
If the answer is "just this one," you're a disposable solution. An expensive band-aid.
If the answer is "for anything," you're a partner.
What's the difference?
Disposable consultants solve problems. Partners build capability.
Disposable consultants deliver a model. Partners teach the team to execute it independently.
Disposable consultants create dependency. Partners make themselves less necessary over time.
The executive said something else that stuck with me:
"We wanted to make sure we didn't bias our process by our relationship. So we did the diligence even though we already knew you from the Vista days."
Your relationship gets you on the shortlist.
What your former clients say about you is what closes the deal.
In 2025, everyone's making those reference calls. Everyone's comparing. And the question they're asking is:
"Do you make me better after you leave?"
If the answer isn't "yes," you're losing deals you thought were already yours.
When's the last time you asked your clients: "Would you hire me again for a completely different problem?"
If you're not sure of the answer, you already know.

"We're not using it enough to justify the cost."
When SaaS customers say this at renewal, it's not a usage problem. It's a pricing problem.

After analyzing hundreds of B2B SaaS churn calls, I've identified 3 customer churn red flags:

Red Flag #1: "We're not using it enough"
→ Your pricing metric doesn't align with usage patterns

Red Flag #2: "We can't justify the ROI"
→ Your pricing model doesn't account for value realization timeline

Red Flag #3: "It's too expensive for what we're getting"
→ Wrong customer segmentation driving churn

If you're hearing these in renewal calls, fix your SaaS pricing model, not your product.

Watch more insights here:
https://lnkd.in/g-7XkY9X

LLM costs dropped 80% for 2 years straight. Should you lower AI prices?

McKinsey analyzed 150 vendors: Companies that maintained/raised prices saw 2-3x higher revenue growth.

Why? Your AI isn't getting cheaper, it's getting MORE valuable.

18 months ago: Single tasks
Today: Multi-step autonomous workflows

Adobe's playbook: Costs ⬇️ → Prices ⬆️ → $125M Q1 revenue

What to tell your CFO: Customers pay for outcomes, not compute.

Source: McKinsey 2025 report

Tropic

Vice President of Procurement

Head of Procurement & Strategy

Advisor

GRIN

Qualtrics

Global Head of Procurement, Real Estate & Facilities 

I established the department and built a team that delivers impactful results to the bottomline.  By helping the company maintain profitability while growing 40-50% per year, my team played a significant role helping achieve the high valuation placed on the company which led to being acquired for $8B.  I've built processes that reduce fraud, save the company millions of dollars (which it re-invests for additional growth), increase contract flexibility, decrease risk.  The results have been large and the impact even larger.

Head of Procurement

Brigham Young University

Operations / Global Supply Chain Management

Adjunct Professor

Honeywell

Managed a global program across categories such as building services, personal protective equipment, printers, scanners, security, gas detection, calibration, lab chemicals, roofing services, sensing and controls, and other indirect products and services encompassing approximately 200M of spend. Worked as an expatriate for 6 months in Bucharest, Romania facilitating growth in the region, performing training to the procurement team, and driving immediate synergies with recently acquired companies.  Developed processes ensure 98%+ compliance for spend categories are met - thereby increasing productivity and limiting leakage.  Led a team that tracked monthly spend and reported to senior leadership.

Senior Procurement Manager

Developed and leveraged a deeper understanding of high dollar and critical suppliers and their markets to achieve improved results in negotiations through prioritization, strategy validation, and analysis of spend, markets, risks, benchmarks, etc.  Outcomes: stronger supply chain, better balanced and productive relationships with suppliers, achievement of direct material productivity goals, secure and sustainable competitive advanced, and mitigating risk.

Category Manager

Collaborated with  suppliers to align schedules including identification of any gaps and risk mitigation actions to achieve continuity of supply. Placed purchased orders (POs).  Worked as project lead for bearing buyers to facilitate subcontract material.

Global Buyer

Acted as the coordination and communication link with all
areas of operations relevant to purchased parts for the Geo-Eye satellite program.
Tracked shortages to expedite deliveries, receipts and production implementation to ensure program schedule.

Planner/Scheduler

Working in the repair and overhaul SCAS division.  Developed models to help predict ever-changing forecasts to ensure customer due dates were met while maintaining efficient inventory levels.

Production Control Planner

I am committed to building the reputation and value of procurement in the Tech sector.  I launched a respected procurement organization at Qualtrics by leveraging my global procurement experience from different industries.  I hire great leaders and collaborate with business partners to source and deliver innovative solutions that creatively solve business problems, mitigate risk, improve supplier performance, and make significant contributions to the financial health and performance of the company.

Michael Shields

Multiple times in my career I haven’t had a formal savings goal.  

Perhaps that sounds strange coming from a procurement guy. 

But it’s true. 

I’ve had bosses who cared more about: 

1. CSAT - if I were hiring a first time procurement leader, one of the strongest traits I’d look for would be the ability to build relationships internally.  Help stakeholders understand the value procurement actually brings.  This partnership leads to higher adoption, less rogue spend and more optimized spend. 

2. proof that we were getting a good deal - Approvers get bombarded with spend requests.  Clearly providing data to help them know what should be approved (and quickly) vs where to push back.  The requested budget far exceeds the actual budget.  Arming them with data is powerful. 

3. Finding suppliers who can help us generate more ROI.  Spending money isn’t a bad thing.  So you need to spend money in order to make money.  If I can help source suppliers that help us hit our goals, the supply base becomes a competitive advantage. 

Don’t get me wrong.  For each company I’ve ever worked for, I’ve had a tremendous impact on the bottom line.  Certainly enough to justify my expense multiples over. 

But for me, savings are a result rather than a focus.  They come organically through other activities.

Vice President of Procurement @ Tropic | Spend Management Enthusiast | Speaker | Advisor | Professor. On a mission to change the perception of Procurement. In tech and beyond.

Last week, I posted about not having a savings goal and another procurement leader reached out to talk about it. Apparently his savings goal is 15% next year. 

Me: “Based on what?”

Him: “Based on…. the fact that this year we’ll likely surpass the goal we set (15% vs 13% goal). 

Me: “That’s kind of dumb… possibly irresponsible.”

Here’s why: 
🔸 savings goals without linking to spend growth, inflation, or strategic initiatives is uneducated and risky. 
🔸 risk is introduced when savings are measured on price variance alone without TCO/risk weighting.
🔸 suggests that savings are greater than value. 
🔸 Over-rotation can occur when savings goal isn’t based on data.  

I have seen first hand how savings can get harder to achieve YoY (unless the company is scaling quickly).  That’s when creativity kicks in (and not the good kind of creativity). Suddenly questionable business choices are occurring… ones that favor short term gains over long term value. 

What if instead the goal was a combination of: 

price optimization (leveraging data to quickly achieve what is sustainable for both parties)

value creation (measuring increased ROI, time savings, etc) 

and improved supplier performance (better and stronger results)?

I'd argue the top line would benefit as much as the bottom line. Suppliers would help their customers achieve a competitive advantage. 

For example, the company spends more but it’s with a better performing supplier that is delivering higher ROI.

That’s actually great. 

Don’t get me wrong, I am not anti-savings. Done right, they will still come and can be tracked. But not at the expense of ROI, quality and supplier performance.

Here’s my favorite agenda item at a conference.

(Frankly I hope to see more of it). 

Round tables where each table has a unique topic. Attendees can sign up for a table that interests them. Ideally 8-10 people at each table. 

The format: 
quick intros. 
Each person has ~12 minutes. 
2 minutes to explain a current situation. 
10 minutes for others at the table to provide ideas, advice, recommendations. 

In 1.5 hours, you break down 7 real life problems about a relevant topic. Each person gets the benefit of the group discussion and receives consulting for their problem. 

One person is the moderator (keep on track, ensure no one over powers, etc). 

It’s powerful. It’s impactful. 

You start off as strangers and by the end have strengthened your network in a powerful way. 

In my opinion, it beats a panel any day of the week.

I was left to interpret the pricing change.  

Here’s the email I got. “Hey, wanted to shoot over the renewal contract before I go on vacation next week. Take a look and let’s grab some time when I get back the week of the 5th.”  

I looked it over. It looked different. 

The pricing was 17% higher. One of the SKUs looked new. Another seemed to have disappeared. 

Without context, I filled in the blanks the best I could…

Guess what I did the week he was on vacation?

I talked to his competitors.  

No way we could absorb 17% increase.  

This is a bit of an extreme example I’ll admit. But I see it in other ways:

Pricing saved until the last 5 minutes of a call. No time to understand impact or reinforce value. 
SKU changes presented but not well explained. 
Uplifts proposed but value didn’t increase (perception or reality). 

I’m not saying every pricing change needs a full whiteboard session. But interpretation is a dangerous thing. You might end up in a situation straight out of that Key & Peele sketch where they are texting each other. Same words. Completely different tone interpreted. One guy thinks they’re making plans to have fun. The other shows up to the meeting point with a baseball bat.  

I’m convinced that the best sellers are those that frame in a way that re-inforces value and helps the buyer logically understand the pricing and the value. It naturally incentives the buyer to move quick. 

Take-away: 

If you leave buyers to build the story themselves, don’t be surprised when the ending isn’t the one you wanted.

In today’s edition of good-intentions but bad results: 

You think you are insulting a competitor. 
But you might actually be insulting my judgement (since I’m seriously considering them). 

You think you are incentivizing me to close by EOQ. 
But you might really be threatening the guy you are wanting to “partner” with (your word, not mine). 

You think you are making your product sound amazing with a fluffy stat. 
You are really breaking trust and losing credibility by exaggerating.  

You think you are going to make your customer happy by quickly agreeing to a big discount. 
You are really making them wonder why that discount wasn’t offered up front. What else are you hiding??

There is a way to talk about the competition. There is a way to uncover urgency. There is a way to share ROI. And there is definitely a way to meet the financial hurdles of a prospect. 

But the execution is really important. 

Why do I share?  

Because these results slow things down. Unintended consequences cost both the buyer and the seller. 

And I’m a believer there is a better way!

I wore a collared shirt and jacket in an effort to fit in with the finance crowd at the FATE conference in NYC. 

The goal was to have me talk to finance leaders about the value of procurement + finance. 

Three thoughts: 

1. Booth duty is a grind. Shout out to sellers who do this on the regular. 
2. Decent conversations make the grind worth it (I think).
3. I regret my wardrobe choice (not true to who I am…)

Next time I think I’m going to wear a custom t- shirt. I’m debating between a few options. 

A. “Stop Saying No to Good Spend.”
B. “In CFO We Trust. In Procurement We Verify.”
C. Procurement: The Growth Lever You’re Ignoring.”
D. Slash Waste. Not Headcount.”
E. I Audit Feelings With Data.”

The highlight was meeting a CFO who had decent visibility to his spend but it came at a big cost of time and effort. 

His company is scaling and his home grown solution isn’t. 

His big fear? He’s saying “no” to good spend. He doesn’t see his job as cutting costs or saying no. He knows that GOOD spend can help his company grow. Which spend will push the business forward and achieve core goals. 

That’s why an alliance between finance and procurement is so powerful. Finance defines the strategy; procurement operationalizes it so every buying decision aligns with that strategy.

It was fun to show him how Tropic plays a critical part through process (routed to the right people with the right context) and data (ensuring the price is fair, the terms are market, and the spend is actually justified). 

So which t-shirt is best? Or is there a better idea all together?

No alternative text description for this image

Matt posted this photo from a Sales dinner last week. But he also failed to really tell the stories behind the photo. 

Let me pick up where he left off…

A: Michelle from G2. If all sales pros were like her, the reputation of the group would be very elevated. It was fun to realize that in my role, I’ve worked with members of her team in the past. Treat people well.  It's a small place. 
B. Tanner from Sendoso - A few years ago, he and I went a few rounds to structure a deal when he was doing sales at Spiff and I was procurement at Qualtrics. We ended up signing on the last day of the quarter. But not before he hooked us up with a big discount. Great guy. Sub-average golfer. Lives in Utah like me. 
C. Todd - Sales historian and cool author. We connected on Zoom a couple weeks ago and finally got to meet in real life. He even gave me a copy of one of his books. Highly recommend. Also Matt promised everyone at the dinner advanced copies of his new book but then couldn’t live up to his word. Lame. I’m still going to buy the book anyway of course.  
D. Unknown person in the mirror. The outsider looking in. I actually have no idea who this person is but clearly they were wanting to keep their distance from Matt. 
E. Jen - Not at tall as people say. But even kinder, more genuine, and more supportive that you hear. She’s the real deal and just might be the best thing that ever happened to sales. If you are still looking for a way to boost the ROI of your upcoming SKO, drop her a line. You won’t regret it. 
F. Joshua from AskElephant. I actually enjoyed hearing about his company. It was the first time I heard about them but then they came up on another call the very next day. And he’s ALSO from Utah. 3 Utah dudes from 3 companies at a dinner in Chicago. Silicon Slopes is alive and well. 
G. Emily - loved getting to know her. Great at sales enablement but also loves Stand up comedy. We have a follow up meeting in a couple weeks.  Pretty excited about that. 
H. Matt’s empty chair: The conversation seemed to flow much better when he was up taking pictures. I even got to know his boss Jeff a bit (to the chair’s right). Jeff went to Italy once.  
I: Procurement Guy right Here: True story. We might have been a chair short at the table. But everyone was willing to scooch a bit. Matt tried to cut me out of the picture but he failed (again). 
J: Heather and Ashley from Jellyvision - somehow I got lucky enough to sit next to them. No regrets. They are amazing and if they ever come to Utah, we’ll probably hang out. They are basically family now. 

There are more people that I could have tagged but the photo was getting messy with lines and letters as it was.  

All in all, it was actually a really cool dinner hosted by the folks at Sales Assembly. This evening was proof that things are ALWAYS better when procurement and revenue get in the same room and talk openly.

What is the catalyst for a sourcing event?

What if instead of:

It’s over a certain threshold (ie; $100K) or 
It’s required every few years (3 seems to be the norm)

The catalyst was specific supplier insights or business need: 
🔹 A new supplier might be able to do it better (Data shows up increased adoption / growth) 
🔹 A new supplier can do it cheaper (leveraging benchmarking data)
🔹 Stakeholder CSAT is low (looking at internal pulse surveys). 

An often under-stated fact: churn is expensive. Many focus on the negative impact to revenue organizations but it’s actually horrible for buying entities as well.  

And yet, extended sourcing events that just award the business back to the incumbent are also expensive and taxing of resources.  

Here’s a recommended new process:

Mid-point of contract, the system kicks off a step that: 
🔹 Collects stakeholder feedback (pulse survey)
🔹 Looks at utilization (supplier can provide)
🔹 Evaluates the competitive landscape (what’s changed). 

This insight is used to evaluate status and TAKE action. 

(Meaning if there are red flags, let’s collaboratively work with the supplier to fix them). 

Process repeats 4-6 months prior to contract end. 

If status is green, sourcing not required. 
If status is yellow, let’s start looking at an alternative. 
If status is red, then it’s probably time to prepare to switch.  

Again, BOTH seller and buyer benefit here.  

Supplier performance likely improves. 
Churn rate likely decreases. 
Sourcing efforts are focused on where they are actually needed. 

All enabled by technology. 

I can attest this works in certain situations. 

Would love to have others weigh in on whether there are blindspots I’m not seeing.

If you are a seller, you might think your buyer is being difficult (“ugh, procurement…”). 

If you are a buyer, you might think your seller is being greedy (“ugh, they are just trying to maximize their commission”). 

This market is kind of crazy.  The pressure on margins is insane. 

Revenue pressure is strong.  But budgets are being cut.  And as a result, negotiations are getting pretty tense…. and drawn out. 

Here’s where things are actually getting done:

Companies that actually deliver more value AND can articulate that value are the ones that will see consistent success.  

(Both of these MUST be true). 

Their close rates won’t just be higher, they’ll actually gain a market advantage.  

They are the ones closing deals quicker while their competitors are dealing with longer, more drawn out negotiations… and costly churn.  

Value isn’t just the great equalizer. It’s the only thing that accelerates deals when economic headwinds are slowing them down.

So while it might feel like buyers and sellers have opposing goals, the irony is that both sides are running toward the same place and don’t realize it.

Sellers might indeed feel pressure to raise prices but in order to do this, they need to deliver more value.   Buyers might think they need reduce cost but what they really need is higher ROI.  
 That’s a great unifying insight.

Sound too good to be true?

Tropic’s co-founder is pretty strict when it comes to budgets.  

But I watched him approve a deal that was signficantly more (in excess of 20%). 
 Because the technology had changed dramtically.  And the rep did a great job of showing how the ROI increased much more than 20%.

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Marcos Rivera

Michael Shields

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The Battle

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