TL;DR: Pricing isn’t a democracy - don’t crowdsource the decision.

TL;DR: Deal desks handle 'Failure Work'. Work that would not exist if your pricing actually worked.

TL;DR: Most customers, most of the time, care just about your product. Sell to them.

TL;DR: Customers only hate paying via credits when the systems are designed badly.

Most founders avoid asking customers about pricing, assuming they'll lie - but that's only true if you ask about the dollar amount. Ask about packaging, structure, and fairness instead, and you'll find your customers are surprisingly honest allies in building a pricing model that actually sells.

$100–200M ARR SaaS companies often hit the same wall: growth slows because pricing becomes operational drag, not leverage. The root of the slowdown is usually a mix of commercial debt from contract variance, missing enterprise-grade packaging, and multi-product pricing complexity that hurts NRR and cross-selling.

Usage-based pricing sounds simple. In reality, it’s a minefield unless you get four things right: Map, Measure, Monetise, Manage. Map how customers create value, measure it transparently, choose the right pricing modality, and manage complexity ruthlessly. Miss one step, and the whole model collapses.

Turning costs into revenue is the fastest way to make pricing “sell itself.” A client doing near nine figures ARR switched from charging stores $1/order to letting shoppers pay $3—store keeps $1, they keep $2. Result: 100% ARR lift and far easier sales. Here’s the playbook: internal vs. external pass-through.

The best approach I have to raise prices significantly to new customers (e.g. +50%) is to bundle the price increase together with a significant value increase.

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Sometimes the largest obstacle for a company to significantly increase prices is in the heads of the founders or executives.

​They simply don't believe that their product is worth it.

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Churn can be too low.
If higher prices creates higher churn, then you have a choice: money now or money later?

So there is some intuitive relationship between prices and churn.

Let me unpack this.

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Following last weeks newsletter I got this question from a reader:

"How would you approach a two-sided business model where one side is generating ecommerce orders that need fulfilment (through the Network), and the other side is made up of connected distributors who do the fulfilment (drop shipping orders)?

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Here are the three main questions I ask myself when thinking about pricing for any AI product:

1) Does the solution generate a single, repeatable outcome?​
​(or many different outcomes?)

2) Is the path to value clear to the customer?

(or does the solution require explorative usage to reveal the true value?)

3) Is there significant cost involved in powering the AI solution?

(or does the deployment cost about as much as regular SaaS?)

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I was emailing back and forth with a product leader inside a Fortune 100 company when she mentioned that 'SKU Spaghetti' was an issue.​

I loved this term (I used to call it 'SKU creep', but 'SKU Spaghetti' is just a better term. You know who you are - thank you!).

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Lots of my customers ask about charging different prices in different countries. And it makes sense: US wants to pay more than Europe, who wants to pay more than China. So the same price - 100 - might be too cheap in one country and unsellable in another...

‍Metric Granularity is the technical term (that I invented, full disclosure) of the size of the unit you charge via your pricing metric. So if you charge $100/user/mth - then the metric is #user while the granularity is '1', if you charge per single, individual user...

My first principle of pricing: Price the customer, not the product...

Let me tell you a story: We just completed a mystery shopping exercise for a $40M ARR US B2B SaaS company.
​They were convinced their competitors were undercutting them on price.
​Most of their sales people said so.

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Most customers I work with try to apply some form of 'linear' pricing to an 'exponential' world.​
Let me explain: Whatever pricing model you have it probably runs on some kind of metric or measurement - e.g. Users, API calls, CPU cores, Employees, AUM, Store Locations etc..

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Credit systems work like this:
1) Buy credits upfront
2) Spend credits to use the product.
3) Unused credits roll over to the next period.

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The price you charge for your product is also the money you have to pay for everything:
1) Customer Acquisition (CAC)
2) Building a better product
3) Overhead
4) Profits​

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At the enterprise level or at any larger ACV most pricing negotiations have several elements, such as:
1) Price paid
2) Length of contract
3) Terms of renewal
Most SaaS vendors focus on '1' and sacrifice '2' and '3'.
So they would prefer:

There is a misguided intuition that since pricing affects everyone, then everyone should also be involved in making pricing decisions. This is wrong...