That's the trap in usage-based, consumption, and AI-native pricing: your cost moves per customer and you can't just raise the number to fix it. I've priced these from the inside — 13 products, $450M+ in ARR. I'll build yours to survive a real buyer.
I watched a founder cut 50 points off his price the second a buyer pushed back — not because the number was wrong, but because there was nothing underneath it. No packaging logic, no story, nothing to hold the line with. So it folded.
The number is never the real problem — the missing architecture underneath it is. I don't hand you a PDF. I build it with you, and make it hold when a real buyer shows up.
5% of users drive 90% of the cost. The buyer can't see it. You can't pass it through without losing the deal.
I launched pricing for exactly this: an AI product with no competitive anchor, an average cost per user around $25 but a median of $0.25, self-serve usage nothing like contracted. I aligned the CEO, CFO, and CTO on how much burn to tolerate and for how long, shipped a seat-based model with iteration built in, and got in the deals to close them.
You won't find a logo wall here. Pricing models are the most confidential thing a company owns — every one I build stays under NDA, and that includes yours. What I can show you is the work I own outright, and what I can do is put the same thinking on your live deal in thirty minutes.
"Farhan is one of those rare people who makes complex pricing problems feel simple. He came in, listened closely, and built a custom framework that actually fit how we operate — not some off-the-shelf model. Fast turnaround, zero hand-holding required, and every deliverable was immediately usable."
"Removed pricing decisions from my mental overhead. I can focus on sales, relationships, and infrastructure now — and the pricing model scales to 50 locations without rethinking it."
Each engagement ends with a model your finance team can own, your sales team can use, and your leadership can stand behind in a board meeting or a live deal.
For reference: a pricing hire in a major market runs $180K–$250K all-in and takes four months to land. A brand-name firm bills $50K–$200K and leaves you a deck. Every engagement below ends with a model your team owns and operates — and I'm in the deals while it's being proven.
Either way, one focused session. We structure your proposal, build the ROI case, and get the number to a place you can hold. The model didn't know your cost curve, your churn, or which two accounts carry your quarter. Plausible dies in the room.
In 60 days you walk away owning a pricing model you can defend in a live deal — whether or not we ever work together again.
I run the customer interviews. You get a model backed by real willingness-to-pay data — segment by segment, with floor, ceiling, and optimal price points.
For companies pricing a product whose cost moves — usage-based, consumption, or AI-native. Research, model, assets, and I'm in the deals with you.
Three clients at a time. That's the whole capacity — it's how I stay in your live deals instead of handing you a deck. If the calendar's full I'll tell you on the first call.
10–15 structured conversations with your customers and your pipeline. Mapped against your real cost to serve. You get a recommendation with the willingness-to-pay data underneath it.
Pricing page, enterprise negotiation, concessions playbook — and me in the room when a buyer pushes. A model nobody can hold the line on isn't a model.
Tear down your current pricing, packaging, and conversion funnel. Find the leaks — where you're leaving money, where the friction is, where the story breaks.
Run willingness-to-pay studies, competitive analysis, and customer segmentation. Real data from real buyers, not vibes.
Design the packaging, tier logic, price points, and conversion mechanics. Model scenarios. Stress-test against competitive pressure and cost structure.
Ship it. Pricing page copy, sales enablement, internal governance, billing specs. I stay through enforcement so it actually lands.
I spent years owning pricing inside Grafana Labs — running it, not advising on it. The best pricing isn't the cleverest model. It's the one you can walk into a room and stand behind.
Four years pricing at Grafana Labs — from sub-$100M to $500M+ ARR, 14 products, 7,500 customers. I've structured the deals, run the research, and built the governance. Now I do it for companies that can't afford to figure it out the slow way. I don't do positioning, launches, or brand — pricing is the whole practice.
Frameworks, teardowns, and lessons from the field.
5–10% of users drive 90% of AI costs. Here's how to design a lever only they'll feel — without touching the other 95%.
Pricing problems disguise themselves as marketing problems. Here's how to spot them — and what to do at each stage.
How you charge outlasts what you charge. Here's the exact WTP research framework for ideal conditions and the 30-day scramble.
A 10% discount is rarely 10%. Here's the real math — across the deal, the renewal, and the life of the account.
Don't bump the whole base. Concentrate the raise on the accounts pulling 10× the value — $6M in two quarters, off a base everyone was scared to touch.
Cost used to track customer size. In AI it tracks behavior — a twelve-person startup can outspend a 4,000-seat enterprise, and you can't tell which from the contract.
30-minute call. No pitch. Just an honest look at your pricing and what's holding it back.
Ask the model trained on real pricing engagements — my frameworks, office hours, and client work. Free, no booking.