We Changed Our Pricing 4 Times in 6 Months. Here's What We Learned.
We built a product, launched it, and immediately got pricing wrong. Then we got it wrong again. And again. Here's the framework we wish we'd started with.
Three weeks after launch, I sat in a meeting with a potential partner and watched their face go blank when I explained our pricing. Not confused. Blank. The kind of blank that means “I have no idea how this maps to my business, and I’m too polite to say so.”
We’d spent months building tiered pricing that made perfect sense from our side. Four tiers, clean feature gates, volume discounts. It was elegant. It was logical. And it was completely disconnected from how our customers actually think about value.
That meeting was the first of four pricing rewrites in six months. Each one taught us something we couldn’t have learned from a spreadsheet alone.
The mistake everyone makes (including us)
There are really only three ways to justify a price: cost-based (mark up what it costs you to deliver), competition-based (anchor to what the market already pays), or value-based (charge a fraction of the value or savings you create). Most founders default to the first one. We did too.
The problem with cost-plus pricing is that your customer doesn’t care what it costs you to deliver. They care what it’s worth to them. And the gap between those two numbers is where all the interesting pricing decisions live.
When we first priced the product, we started with our infrastructure cost per identity check, added a margin, and arrived at a per-check price. Technically correct. Strategically useless. Because a per-check price means nothing to a wealth management firm trying to figure out whether your platform will save them money on client onboarding.
Version 1: Per-check pricing (the logical mistake)
Our first model was simple: charge per identity verification. Max 10 cents per check, with volume discounts stepping down to 8 cents above 100,000 monthly checks. Four tiers — Free, Standard, Premium, Enterprise — gated by features and volume.
On paper, this was clean. In practice, nobody could calculate what it would actually cost them. A wealth manager with 80 active client connections running periodic data refreshes would need to estimate their monthly check volume, factor in the tier they’d land on, account for overages, and somehow arrive at a budget number. Too much mental math, too much uncertainty.
The feedback wasn’t “your price is too high.” It was silence. People couldn’t engage with the model at all.
Version 2: Per-user pricing (the overcorrection)
So we swung the other way. Flat monthly fee per user. Simple to understand, easy to budget for. But it created a different problem: it penalized our best customers. A firm with 350 wealth managers would pay 350x regardless of how much value they were extracting. Heavy users and light users paid the same. The firms that would benefit most were the ones getting the worst deal.
We also couldn’t differentiate between a small advisory practice with 25 wealth managers and a large institution with 350. The value per user was completely different across these segments, but our pricing pretended it was the same.
Version 3: Value-based, but we calculated the value wrong
This is where things got interesting. We decided to flip the model: instead of pricing based on what it costs us, price based on what it saves them. Calculate the actual cost of onboarding and maintaining a client today (hourly wage × time per event × external costs), calculate the same cost with our product, and the difference is the value we create.
The framework was right. The execution was wrong. We were calculating total value across the entire firm and then trying to capture a percentage. But the buyer wasn’t thinking in “total firm savings.” They were thinking “what does this cost me per client?”
We’d built a top-down model when the buyer needed a bottom-up story.
Version 4: Bottom-up value pricing (what actually works)
The breakthrough came when we rebuilt the model from the smallest unit up:
Step 1: Value per single client. What does it cost to onboard and maintain one client today? What does it cost with our product? The difference is the value per client. For a typical wealth manager, current onboarding cost was roughly €45 per client (blended hourly wage × time × external verification costs). With our product, that dropped to around €12. Value created: €33 per client.
Step 2: Value per user. Multiply by average clients per user. A wealth manager at a small firm handles about 50 clients. At a large institution, closer to 200. So value per user ranges from €1,650 to €6,600 annually, depending on segment.
Step 3: Value capture percentage. We don’t capture all the value. We capture a share that feels fair relative to what the customer keeps. We landed on different capture rates by segment: higher for enterprise (they get more value per user), lower for small firms (keep the barrier low).
Step 4: Sense check. Does the resulting monthly fee per user feel reasonable? Can a buyer look at it and immediately understand the ROI without a spreadsheet? If the answer to both is yes, the pricing works.
This model let us walk into a meeting and say: “Your onboarding cost per client drops from €45 to €12. You have 100 wealth managers averaging 100 clients each. Here’s exactly what that saves you, here’s what we cost, and here’s your net ROI.” One slide. No confusion. No blank faces.
Triangulate: cost is the floor, competition is the anchor, value is the ceiling
Looking back, the deeper lesson isn’t that value-based pricing is the right answer. It’s that no single method gives you a defensible price on its own.
We now triangulate three lenses every time we revisit pricing:
Cost-based answers: what’s the floor? Sum what it costs to serve one customer at scale (infrastructure, support, amortized dev, payback on acquisition cost). Add the margin you need. That’s your sanity check, not your target. If your price is below this number, you’re choosing to subsidize, and you should know exactly why.
Competitive answers: what does the market already accept? Benchmark adjacent products. This anchors your pricing to what customers already pay elsewhere, which is where their reference point lives whether you like it or not. The risk is picking the wrong peer set; pick three peer groups, not one.
Value-based answers: what’s the most we could charge? Quantify time saved, risk avoided, costs eliminated. Apply a willingness-to-pay rate (10–15% is a common starting point for new products). This gives you the ceiling, the most defensible long-term story for sales, and the ROI math the buyer will use internally.
The right price is somewhere in the overlap. When we first priced the product, we used only one lens (cost) and ended up with a number that was technically defensible and commercially inert.
Pick the right structure (and don’t be afraid of a hybrid)
Once you have a price, you have to decide how to charge for it. Per seat? Per unit of usage? Flat platform fee?
The honest answer is that almost everyone interesting ends up with a hybrid. We’ve recently been working with an AI platform serving customer support teams that landed on a two-part tariff: a flat monthly platform fee that gets you access and unlimited users, then per-unit consumption rates for the modules you actually use (per word translated, per QA review). Volume tiers bring the per-unit rate down as customers scale. A 10% multi-module discount nudges expansion. Annual commitments get a further discount in exchange for predictability.
It works because each piece does a different job. The platform fee establishes a stable relationship and covers fixed costs. The consumption fee aligns what the customer pays with what they get. The volume tiers reward growth. The annual discount pulls cash forward and reduces churn risk.
If you want to push this further, three-part tariffs (platform fee + bundled usage + per-unit overage) tend to capture even more value. Behavioral research suggests customers on a three-part tariff increase their usage by around 15% versus less than 1% for those on a pure two-part tariff. The bundled allowance changes how they think about consumption.
This matters more than ever for AI products. When the buyer’s mental model is “I’m replacing seats with agents,” your pricing structure has to make that math obvious. A pure per-seat model under-prices the actual leverage. A pure consumption model gives the buyer pricing anxiety. Most teams we see end up somewhere in between, with a platform fee that establishes the relationship and consumption-based pricing that aligns with the value delivered per ticket, per interaction, or per outcome.
What we actually learned
Start from the customer’s smallest unit of value. Don’t model total firm savings. Model the saving per client, per transaction, per ticket, per whatever your customer naturally thinks in. Then build up. People can intuitively validate small numbers (”€33 saving per client sounds about right”) in ways they can’t validate large ones (”€2.4M in total savings” triggers skepticism, not confidence).
Segment early, even if your segments are rough. A 25-person firm and a 350-person firm aren’t just different sizes, they’re different businesses with different economics. We defined three segments (Small, Medium, Large) with different assumptions for clients per user, usage patterns, and value capture rates. The segments were imperfect, but having them at all meant we could tailor conversations instead of forcing one story onto everyone.
Build the model so the buyer can play with it. The single most effective sales tool we created wasn’t a pitch deck, it was a spreadsheet where the prospect could plug in their own numbers (number of users, clients per user, current cost per event) and see their specific ROI. When the buyer builds the business case themselves, they own it. That’s worth more than any pricing page.
Your pricing is a communication tool, not just a revenue mechanism. The reason Version 1 failed wasn’t that the numbers were wrong. It was that the model couldn’t be understood in a meeting. Pricing needs to be explainable in one sentence. Ours is now: “You pay a percentage of the value we create per client, and you keep the rest.”
Treat pricing as a moving target, not a launch decision. Demand curves shift as your brand strengthens, reference customers accumulate, and ROI evidence builds. We now revisit pricing quarterly and re-index annually (CPI plus a small premium). The teams that get pricing right aren’t the ones who pick a perfect number on day one. They’re the ones who build a feedback loop and use it.
Common pricing mistakes worth avoiding
A few patterns we keep seeing in other founders’ pricing, often the same ones we made:
Building a model that’s clever behind the scenes but opaque on the surface. Complexity is fine internally. The buyer should still be able to explain what they’re paying for in one sentence.
Waiting too long to move to annual prepay. Annual contracts smooth churn, generate cash, and force the renewal conversation once a year instead of twelve times. Push for it earlier than feels comfortable.
Treating pricing as static. If you haven’t touched your pricing in two years, your pricing is wrong. Markets move, you move, your pricing has to move too.
Forgetting to embed concessions in the proposal. Mid-market procurement teams will negotiate. If you don’t leave room, you’ll either lose the deal or lose margin you didn’t plan to lose.
Asking the wrong price discovery questions. Don’t ask “what would you pay?” Ask “what are you currently paying for the alternative?” Relative beats absolute every time.
Your turn
We’ve attached two resources below that you can use today:
The Pricing Strategy Prompt — a structured prompt you can feed to any AI assistant along with your product details. It walks through the same value-based pricing framework we used: identifying your customer’s unit of value, modeling current vs. new cost, segmenting, and setting capture rates. It’s the thinking tool that got us from Version 1 to Version 4.
The Pricing Model Template — a simplified version of the spreadsheet we use in sales meetings. Plug in your own segments, cost assumptions, and value capture rates. It calculates per-client value, per-user value, and total revenue potential automatically. Designed to be handed to a prospect so they can model their own ROI.
What pricing model are you using, and how did you land on it? We’re curious whether other founders went through the same iteration cycle or found a shortcut we missed. Drop a comment or reply, we read everything.
Resource 1: Pricing Strategy Prompt
Copy this into Claude, ChatGPT, or any AI assistant along with a description of your product and customer.
I need help building a value-based pricing model for my product. Here’s the context:
[Describe your product: what it does, who uses it, what problem it solves]
Walk me through these steps:
1. UNIT OF VALUE: What is the smallest unit of value my customer experiences? (e.g., per transaction, per client served, per hour saved, per ticket resolved). Help me identify the right unit based on how my customer naturally thinks about their work.
2. CURRENT COST: Help me estimate what it costs my customer to handle one unit today WITHOUT my product. Break it down into: labor cost (hourly wage × time), external/tool costs, and opportunity cost if relevant. Ask me clarifying questions to get realistic numbers.
3. NEW COST: Now estimate the cost per unit WITH my product. What time is saved? What external costs are eliminated? What’s the new per-unit cost?
4. VALUE CREATED: Calculate the value per unit (current cost minus new cost). Then help me think about how many units a typical customer handles per month/year.
5. CUSTOMER SEGMENTS: Help me define 2-3 customer segments (e.g., small/medium/large) based on volume, team size, or usage patterns. For each segment, estimate: units per user, number of users, total value created.
6. VALUE CAPTURE: What percentage of the value created should I capture as my price? Consider: competitive alternatives, customer willingness to pay, my cost to serve, and what leaves enough value on the table that the ROI is obvious.
7. TRIANGULATION CHECK: Compare the price you’ve derived against (a) the cost floor (what it costs me to serve one customer at scale, plus margin) and (b) the competitive anchor (what similar products charge). Does the value-based price sit comfortably above the floor and within reach of the anchor? If not, what needs to change?
8. SENSE CHECK: For each segment, calculate the implied monthly price per user. Does it feel reasonable? Can I explain it in one sentence? Would a buyer immediately understand the ROI?
9. PRICING STRUCTURE: Based on the above, recommend a pricing structure (per-user, per-unit, tiered, two-part tariff, or hybrid) and explain why it fits my market.
Present the final model as a simple table showing: segment, value per unit, units per user, value per user, capture rate, and price per user.
Resource 2: Pricing Model Template
Below is the structure of our pricing model. Build this in a spreadsheet (or copy it into an AI and ask it to generate the formulas for you).
=== INPUTS (change these for each prospect) ===
Segment: [Small / Medium / Large]
Number of users: [e.g., 25 / 100 / 350]
Clients per user: [e.g., 50 / 100 / 200]
Hourly wage (blended): [e.g., €55]
--- Current process (without your product) ---
Time per event (hours): [e.g., 0.75]
External cost per event: [e.g., €5]
--- New process (with your product) ---
Time per event (hours): [e.g., 0.15]
External cost per event: [e.g., €2]
--- Your pricing ---
Value capture rate: [e.g., 20-30%]
=== CALCULATIONS ===
Current cost per client:
= (Hourly wage × Time per event) + External cost
= (€55 × 0.75) + €5 = €46.25
New cost per client:
= (Hourly wage × New time) + New external cost
= (€55 × 0.15) + €2 = €10.25
Value created per client:
= Current cost - New cost
= €46.25 - €10.25 = €36.00
Value per user (annual):
= Value per client × Clients per user × Events per year
= €36 × 100 × 1 = €3,600
Your price per user (annual):
= Value per user × Capture rate
= €3,600 × 25% = €900
Customer keeps per user:
= Value per user - Your price
= €3,600 - €900 = €2,700
ROI for customer:
= Customer keeps / Your price
= €2,700 / €900 = 3.0x
=== TOTAL REVENUE POTENTIAL ===
Revenue per segment:
= Price per user × Number of users
= €900 × 100 = €90,000/year
Your cost to serve: [your platform cost per user]
Gross margin per user: [price minus cost to serve]
Pro tip: build this as a live spreadsheet and hand it to your prospect during the sales meeting. Let them change the inputs. When they build the business case themselves, they sell it internally for you.
Image credit: Matheus Bertelli via Pexels