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

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?

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?

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.

Most companies make pricing an after thought.

Most companies also are never able to use pricing as the superpower it actually is.  

I have had the privilege of overseeing revenue management for over $6 billion in revenue across a diverse range of industries during the past decade. Throughout this experience, I've gained a deep understanding of the critical role that pricing plays in business success. 

I'm passionate about sharing my expertise and insights to help organizations harness the power of pricing strategies to improve profitability and overall performance.

Karan Sood

Set and forget is not a pricing strategy ! 

Price--> Design--> Build 

We know that's what everyone says, but thats an oversimplification of what the entire process should look like. 

The assumption your pricing was correct in the pre-design phase and doesn't need change is dangerous, dangerous, dangerous !! 

I have seen too many physical and software products change drastically between initial design to final delivery.  Product owners will typically assume that pricing still holds. You have to change that philosophy. 

 In the real world we need a lot more iteration in price: 

Step 1: 
Initial Price: This stage you quantify the value and set an initial target price. This is a combination of internal/external research, some value quantification and pricing knowledge. 


Step 2: 
Design: With that price info, the product team designs a product that hits product and profitability targets. This is also where you need to keep track of the product margins. Often product will go design a better product at the expense of higher cost, and margins suffer before launch. 


Step 3:
Reprice: Now that we know the new design constraints that impact the profitability, this stage gives  you the opportunity to reprice the product based on the design. If substantial value has been added, price should go up. Do not fall into the 'lets over deliver on value and keep price same' trap. 

Step 4: 
Build: Now with that new price info and product roadmap the product goes through the build stage. 


Step 5: 
Pre launch reprice : Now significant time may have passed since last price review. The market for the product, the economy etc may have changed. This stage can assist in making last changes before product goes out. Good time to also establish guardrails for price performance, discount strategy, or sales strategy.  


Step 6: 
Launch: Goes without saying the product is out in the real world. Great way to capture feedback. Also a stage where performance is measured against the price guardrails. 


Step 7: 
Reprice 3: Based on sales feedback, you start charting next steps. Selling too slow, you may need discount or reprice. Selling too fast, it may be overdelivering on price vs value. Pricing metric may need change. Fx may have changed. This is the price adjustment stage, should be annual or semi annual. 


You can incorporate these steps into new product introduction framework or annual or semi annual pricing strategy process, either ways it will help establish good pricing principles in the org. 

I know of many products that once designed were never repriced years into its life.. Surely things must have changed all those years... 

Think of Pricing as a lifecycle !!

--------------------------
 We are in #Pricingtribe.

Building the #1 Community for pricing, promotions, deal desk and revenue management.

When price increase + price promotion fall on the same day.

Been there. Same team guys. Same team ! 

hashtag

#PricingTribe

10 tips from pricing professionals for pricing professionals. 

We start all our office hours with new  members providing one pricing tip for the rest of  the pricing community. It's my favourite ritual ! 

Here are this week's 10 best: 


- Don't overmodel: Perfect Now Vs. Imperfect that can't ship. 


- Research your WTP by geo, it's not standard across the board.

 
- Know your breakeven: It will dissuade bad discounting behaviour. 


- Incidental pricing: Find pockets of pricing growth in places customer barely notice. Low frequency purchases are margin gold mines. 


- Pricing's impact is in adoption- build cadence with sales, customers, product so the change actually sticks.


- Create deal thresholds + structured deal reviews so sales knowledge becomes reusable pricing intelligence.


- Before the analysis, map what decision-makers are rewarded for-or your brilliant work won’t get adopted.


- Price improves when you can clearly explain (and validate) what’s truly different about your offer.


- Pick one shared KPI that leadership and sales buy into- misaligned incentives create pricing chaos.


- If you can't share actual margin with sales, develop a system that translates to good better best nargin with green, amber and red score. 


- Find the PricingTribe where we share these insights. 


✉️ Send it to a pricing professional
♻️ Repost it to your network
💾 Save it for the future

#Pricing

The human part of pricing isn't going away.

Key takeaways from our 'pricing using AI' roundtable with Steven Forth, Bill Wilson and Kemal H. Sahin. 


- Generative AI cannot be used to set and forget price points. LLM's are not price automation engines. That's a job for traditional reinforcement learning based revenue management engines.  


- Use LLM's in pricing for summarizing and extracting insights from large volumes of messy qualitative information (calls, notes, competitive intel, product/market feedback). 


- Use AI to produce structured thinking artifacts fast (drafts of value models, segmentation hypotheses, messaging, objection handling, etc.). Value modeling used to be scarce, slow, costly, and rarely updated. Now, done well, AI can produce value models quickly enough to make them dynamic and iterative


- Synthetic data is emerging as a major shift in pricing research. Used as synthetic personas/agents that can be interviewed at scale (e.g., JTBD-style interviews), generating qualitative data cheaply and repeatedly.


- The “human” part of pricing isn’t going away. Strong consensus that pricing is still heavily about change management and stakeholder alignment (product + marketing/positioning + sales+finance+facilities (lol))


- Best practice for making LLM outputs more usable: rubrics. A key practical tactic by define evaluation criteria (rubrics/frameworks) to score outputs and reduce randomness. This will help build consistency, coherence, and trust into AI-assisted workflows.


Next week we have a show and tell where a PricingTribe member will show a bundle recommendation engine built using AI. 

Super exciting conversations #PricingTribe.

Pricing Strategy tactic for global expansion. 


Every company at some point will look at expanding globally. A big mistake most do is use their pricing from home country and convert to local currency, put a new currency sign, add VAT and call it a day. 


While it's not wrong, it's not right either. Sometimes it can go terribly wrong. Learnt it the hard way (damn VAT).


Take Netflix for example. While most of the content is same or atleast the volume is similar but Netflix India is 1/4th the price of its US counter part. 

This is no accident. 

Remember what netflix needs globally ? 

The goal is penetration and secure mass users. 

The cost to get in for them is usually fixed, so anything beyond the coverage of fixed cost is gravy to an extent. And the way to maximize that is with localized pricing. 


Local pricing means a few different things: 

1) Benchmarking base metric: Calculate GDP/capita or disposable income of the local country to a base/home country US/CA/EU/JP etc. 


2) Multiply Base price by country ratio to get local pricing in base currency.  


3) Convert to local FX (Use 6 mon avg). 


4) Convert the local FX pricing to charm/anchor prices where necessary. 


5) Create fencing around price: Customers in US should not be able to access India pricing. Else you have an issue. 


6) Do look at VAT laws. US is always EX VAT, India Including VAT.


There are many other ways to do this including local WTP research. You can do that on top of it to validate your derived pricing. 


What other factors would you consider ?


-------------------------
Follow Karan for all things pricing, discounting and careers in pricing. 

Our PricingTribe Community is in full swing ! On point discussions. This month focus is on building pricing tools with AI. Absolutely loving what people have created. Look in your inbox for your invite or apply.

How a CEO should defend pricing in public.
A lesson from Larry Culp (CEO GE Aerospace)



GE Aerospace has been in the news because parts and service pricing is going up and airlines are complaining. Now remember parts and service terms are key part of airlines and aero deals.



Key component+expertise
+ multi year contract =Pricing Power ! 



Now costs are going up tariffs, investments are increasing, supply turmoil at the same time, there too much demand for their services, and airlines want to keep old aircrafts etc. So a lot is happening that makes things favorable for GE and its pricing.




So customers are doing, what they will always do 'complain about price'. Even when there is no cheaper alternative available or preferred. 



Now GE and other plane parts suppliers have long followed unique pricing practices, including pricing to outcome. So they have to defend their pricing power.



So what does their CEO do when he sees pricing pushback, he pushes back harder. 



How ? 



CEO of GE Aerospace reminds everyone of the value 101 lesson: that the price  you pay today reflects the investment the customer make today for the value they will receive over the next decade. 



This is also a lesson in value based selling that GE’s is communicating: 


- we decrease risk (customer safety)
- we decrease customer opex (Save ongoing cost)
- we decrease customer CAPEX (keep old aircrafts)
- we increase customer revenue (less downtime)



He further added we "will conduct its regular summer review of aftermarket pricing, while relying on productivity gains, redesign and resourcing to limit pass-through".



That very statement conveys we will look at efficiency gain but will pass through in price what is fair. 



I think it's the best way a CEO can respond to pricing pressure. There is a reason they have tapped into their pricing power and are having their most profitable year.



February is "Value based Pricing" month in #PricingTribe.



If you liked this send, save or repost it ! 



PIC: GE aviation. That equipment itself speaks high pricing.

No alternative text description for this image

Pricing gets easier when you’re not solving it alone. Proof: This month inside PricingTribe.


Not theory. Not slides for the sake of slides.


We are stacked !!

- Office Hours: Pricing problems, unpacked


- AI Show & Tell with Michael Binney building comprehensive AI products/workflows


- January Roundtable: Using AI in Pricing: What to Automate and What to Keep Human
With Steven Forth and Bill Wilson.


- Member Show & Tell with Krista Gamble: Building bundle recommendation agents.


- Plus, many valuable discussions happening inside the community.


Different formats. Same Focus.

Real pricing decisions, not theory.


If you’ve already received an invite and haven’t joined yet, now is the time. Look for ‘PricingTribe’. Pending invites won’t stay open forever.


The value compounds the moment you show up.

Pricing Public Service Announcement. 

The pricing bible "Strategy and Tactics of Pricing" latest edition is probably the most mis priced product on the market. Ironic I know. 

It would actually make Tom Nagle very unhappy (Someone send him this chart). This level of price variation is kind of criminal.. 

Anyways, you can actually be happy. Because globally because of this mis-pricing and cross border/cross platform price matching the paperback masterpiece is almost 60% off in US/CA/UK.. 

US: $87 (Reg $200)
CA: $114 (Reg $272)
UK: 54 GBP (Reg 155 GBP)

Our book club is reading this in Feb. You should too.. 

Highly recommend getting it while quantities last. Btw, no harm in getting previous editions too if this one runs out.

PSA: Head of Pricing for a Wealthtech company.


You will setup deal desk, pricing, and operationalize the pricing transformation for the org. 

Reporting to: CFO

Must have: Software/SAAS pricing experience + Deal Desk

East cost preferred: Boston/Denver/Berwyn(PA)/Raleigh(NC)

If you have the above, or know someone. Do let me know. 

hashtag

#PricingTribe

I am very bullish about AI's use in pricing. 

From what I see inside PricingTribe, other are too. 

A lot of people are building workflows, competition scrapers, pricing tools, recommendation engines etc.. And this is their first project, which means a lot more is coming and the products will keep improving. 

If the last wave to hit pricing was democratizing data, this maybe democratizing skills. 

AI has done what was likely unachievable for most people until recent past. The bar to automation and achieving process efficiency has never been lower. 

The bar for access to knowledge has never been lower either. 

This creates an opportunity to leapfrog in their careers advance their contributions. 

I feel very strongly that AI native pricing professionals will have a huge advantage in the near future. Over time we will know what AI native will mean.. 

Is current AI perfect ? No.

But an imperfect start early > Perfect start late. 

If there was a goal you had in mind about upskilling yourself as a pricing professional, let adding AI capability be that goal. I don't have to tell you how to do it. It's all out there. 

If it was not on your radar, add it now. 


January is 'Building with AI' in PricingTribe. We have show and tells, webinars and office hours. And I am bullish and excited.

If you build it, they will come !! 🏟️

Very excited about the kind of conversations we are having.

Deep, though leadership, with show and learn !!

You know where to find us !

Your invite is maybe in your inbox. 

Bringing waitlist applicants soon.

There is no industry where bad pricing is as apparent as the restaurant industry. 

No surprised 46% of all restaurants fail by year 5. 

If you don't invest in price, sooner or later it'll catch up to you. 

- Not enough price to value
- Not enough coverage for opex
- Over reliance on tips to fund opex
- Don't educate the customers enough
- too much competition based pricing

I do think they can solve most of it by repricing, and resetting customer expectations. 

Reset menu prices to change customer perception, raise the perceived value.  Pay people living wage, and stop the over reliance on tips. Which in itself is a very North American concept only.  

#PricingTribe what do you think ? Do we have a problem in menu pricing ?

Monthly PricingTribe Roundup


First off I am really happy with everything that happened inside the community over the last month and we aren’t even done yet.

We still have Krista Gamble going over her show and tell session showcasing her 'Bundle recommendation agent' she built using AI. 


The place is shaping exactly into what it is: 

- Pressure-test real work
- Learn new pricing strategies
- Get peer feedback, and vendor reco's
- Attend practitioner-led events
- And learn without having to build all of this on your own


So I am very BULLISH and EXCITED about what this place has already become and will become in the future.


Back to what happening inside the community.

This month we had a few events:

- You can watch the recording of Pricing Roundup with Steven Forth and Bill Wilson and Kemal H. Sahin on using AI in pricing. It was a fascinating discussion on AI automation in pricing. Recording can be accessed. 


- Michael Binney Led a fantastic show and tell on Building using AI. You can again watch the recording. He went over a very sophisticated pricing recommendation engine built using AI vibecoding. Highly recommend watching. 

- We had our PricingTribe office hours that was filled with pricing wisdom. Recording available.


WHAT’S HAPPENING IN FEBRUARY

- So we are switching our theme for the next 2 months to focus on Value Based Pricing Strategy which includes selling, pricing and articulating value. 


- So some of the events will be themed around the concept of ‘value’ and what it means to us, how to best capture it in pricing and how its changing now. Live value quantification exercise. 


- A sub theme we will focus on is designing and running an efficient deal desk.  

BOOK CLUB

- We are going to be reading “Strategy and Tactics of Pricing” by Tom Nagle. No one will be required to read the full book, we will divide and read chapters and share learnings in real world context.


What other things are coming soon by March:

- Pricing Pods: These are curated sub groups inside PricingTribe that will have few people inside each pod on the same journey for 12 weeks. For example “Transitioning to consumption pricing”, “Deal desk design and best practices”.

- Member 1-1: I will soon open up the opportunity for members to schedule events themselves with other people or 1-1 with each other. I feel like lot of people want to provide more 1-1 tips from each other. 


It's amazing what's happening inside the tribe. If you applied, an invite maybe in your inbox.

#PricingTribe show and tell.

Today Michael Binney did a show and tell of an amazing pricing intelligence tool for B2B that he vibe coded himself. It brought in several different personna’s and angles into the pricing quote and provided a well triangulated price for the quote.

The art of possible with AI in building tools and workflows for pricing is pretty wide. 

If you haven’t started, no better time to start now.

Pricing and Commercial Lead | Pricing Tribe

Had a fantastic session with the #PricingTribe and Karan Sood this morning.

We explored the intersection of AI "Vibe Coding" and pricing strategy. Specifically, how natural language programming is lowering the barrier to entry for building custom tools. 
It was inspiring to demonstrate how quickly we can now move from a raw idea to a functional prototype.

A big thank you to the community for the open-minded discussion. The seeds of creativity have definitely been planted for the next generation of pricing tools. 🌱

#Pricing #AI #VibeCoding #TechInnovation #Community

Question for Pricing Professionals: What’s changing or going to change in your pricing job that isn’t being discussed enough?

Every team is on a different baseline and every team has different responsibilities. But any information helps ! Chris is doing some good work as always for the #PricingTribe.

The Pricing Recruiter! Recruit for Pricing, LPM, Revenue Management, Deal Desk and More! Founder of SV Pricing Recruiting the top Pricing Recruiting Firm in the US!

We talk a lot about the future of pricing. AI, automation, new skills, new tools.
Before jumping ahead, I want an honest baseline of where pricing actually stands today.

I’m running the State of Pricing survey to understand:
 • How pricing decisions are really made
 • What tools pricing teams actually rely on
 • Where AI fits (or doesn’t) today
 • What’s holding pricing teams back
 • How pricing teams and careers are evolving

There are no right or wrong answers.  Just the reality of the pricing profession.

If you work in pricing, I’d really value your perspective.

👉 TAKE THE SURVEY (8–10 minutes)
https://lnkd.in/giaUApDq

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The Battle

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