Make your SaaS product or API the better choice, without relying on price cuts. I combine customer research, pricing and AI-agent tests to find what buyers value and what you can deliver profitably.
Sell API endpoints or metered services to AI agents? We build and test offers that make your product a more attractive choice, while finding ways to increase margins at the same time.
That means a clearer promise, better pricing and packaging, and stronger proof. Give agents a reason to choose you without undercutting competitors on cost.
How customer research, pricing and agent tests help your product win against alternatives without defaulting to discounts.
Explore the experiment sprint ↗In our early tests, agents always chose competing options. After we changed the offer, they chose the new version in every recorded choice in the later test.
It still won when its listed price was 50% higher than the generic option in the comparison.
See how the results changed ↗Controlled research across different test stages, not a live sales result. See the sample sizes and comparison limits.
Find why agents choose competing products, then test changes to your promise, pricing and packaging. Give buyers a stronger reason to choose you, while checking what it costs to deliver.
4 weeks after agreed scope and required access.
50% upfront, 50% at handoff.
Starting price for the stated scope; production rollout and extra usage are scoped separately. An accepted diagnostic or equivalent evidence is needed before testing.
The Agent Choice Diagnostic maps buying friction, economics and the strongest hypotheses.
Data APIs, extraction and enrichment services, developer infrastructure and AI tooling. When usage drives revenue and delivery cost, the pricing unit is part of the product—not just a line on a rate card.
You have a discoverable product, credible alternatives and a clear job. Learn which offer details deserve a test before the launch.
See what we test ↗Connect the buying promise to setup, first value and repeat use. Separate offer friction from a product that is difficult to activate.
Explore the product journey ↗Bring your product, the job you want to win and the alternatives buyers consider. We’ll turn the problem into a testable question.
Interviews, sales conversations, pain-point mining and product data reveal the outcome, constraints and alternatives that matter. Sentiment analysis helps organise market language; it does not prove agent preference.
Your team knows which job to compete for—and which promises are worth testing.
Design the outcome, capabilities, evidence and commercial terms as one offer. Compare the cost of finishing the same job, not just the headline unit price.
Give buyers a clearer reason to choose without hiding the cost of delivering it.
Explore pricing & packaging ↗Purpose-built environments and repeatable procedures compare offer variants under defined buying contexts. Selection, successful execution and economics are separate measures.
Focus on the changes that help you win buyers, with delivery cost and margin checked alongside selection.
See the experimental approach ↗Distinguish offer, access, pricing and product friction.
Focus the roadmap instead of changing everything at once.Connect the promise and price to a completed job.
Give growth, product and sales the same commercial story.Examine cost, retries and risk alongside preference.
Avoid winning demand that becomes expensive to serve.Review customer evidence, the job, alternatives, current offer and economics. Agree the baseline and what a useful result looks like.
Construct three variants. Document pricing, outcomes, proof and constraints. Set the criteria and controlled test procedure.
Compare offers in bounded buying scenarios. Check robustness and endpoint execution. Keep failures and exclusions in the record.
Analyse results and explain uncertainty. Deliver recommendations and the next live-validation or implementation steps.
The outcome, buying constraints, alternatives and reasons an offer might win.
Know which problem your team is solving—and for whom.
Outcome framing, packaging, pricing mechanics and evidence, built around one priority job.
Choose pricing and packaging with evidence, before risking your launch budget.
Test design, baseline, run evidence, execution checks and an honest account of uncertainty.
Give stakeholders reasoning they can inspect, not just a slide to trust.
Completed-job costs, margin implications, recommended changes and the next validation steps.
Give product, growth and sales a clear plan to win more profitable business.
Jobs-to-be-Done, desired outcomes, objections and competitive claims were checked against the research—not inferred from a feature wishlist.
Research coverage, not a conversion or revenue result.
Read the research approach ↗The new offer won every recorded choice in the later test, including when its listed price was 50% higher than the generic option in the comparison.
Early and later tests differed. This measures agent choice, not sales or profit.
Read the offer experiment ↗From event tracking to customer segmentation, the work connects product usage to useful decisions. A clustering review checked feature design, outliers and test-account contamination before accepting the model’s results.
Read the methodology review ↗Find a better reason for agents to choose you. We’ll examine your product, pricing and competitors before recommending what to change.
Jake McMahon
Founder · ProductQuant Labs
I’m Jake McMahon. I connect what customers want, what your product can deliver and what they’ll pay for—then test the offer with agents before you commit to it.
You get customer research, pricing strategy and experimental analysis in one engagement. My work spans AI product commercialisation at Queue, SaaS growth consulting and the purpose-built sandboxes behind these offer tests. The advantage: research becomes a commercial decision, not another report handed off to someone else.
You work directly with me, from the research question to the readout. One engagement is in delivery at a time.
More about my work ↗Not always. The sprint needs a clear job, channel, baseline and enough evidence to design meaningful variants. If you have equivalent evidence, we can assess it. Otherwise the diagnostic establishes the starting point.
We distinguish current behavior from a future-channel hypothesis. The diagnostic can assess readiness and human buying friction. We will not present simulated demand as real customer demand.
No. You receive the agreed research, tests and recommendation. Marketplace share, realised revenue and customer conversion require live validation.
Production rollout, a wider redesign, extensive instrumentation, new interview programmes and extra API usage are separately scoped. One engagement is in delivery at a time.
Help buyers find you through Google, AI answers and agent marketplaces. Build discovery around the customer problems your product solves.
Give the right buyers a reason to consider you before they choose someone else.
Explore SEO, AEO & GEO ↗Help people and AI agents get a useful result sooner. Improve setup, first use and the path to paid, repeat and expanded use.
Make your product easier to adopt, harder to abandon and worth using more.
Explore activation & expansion ↗Share your product and the buying problem you want to solve. We’ll discuss what to test.