Pressure-test your positioningin a weekend. Not three months.
The Synthetic Customer Research Panel is a structured prompt system plus a Claude/GPT artifact that lets founders stress-test messaging, pricing tiers, landing copy, and feature priorities against 12 AI-simulated ICP personas before spending on real research.
Includes a bias-check protocol and a real-world calibration worksheet, because synthetic research is directional, not predictive. We built the limitation into the product so it’s used responsibly.
Most founders spend three months on positioning. They ship the wrong thing anyway.
Rewriting the headline on Tuesday. Second-guessing the pricing tiers on Thursday. Tearing up the feature list on Sunday. Burning through agency-quality weekends — with zero signal back about which version actually lands.
Real customer research costs time and money you don't have at the messaging-iteration phase. So most founders ship on instinct, then spend the next six months wondering why conversion flatlined.
The Synthetic Customer Research Panel compresses the iteration phase from months to a weekend — without pretending to be ground truth.
- 01Week 1: Rewrite hero headline four times
- 02Week 2: Reorder pricing tiers based on a tweet
- 03Week 3: Add a feature because a friend asked for it
- 04Week 4: Get the same feedback from a different friend
- 05Months 2–3: Ship anyway. Hope.
- 06Month 6: Read the analytics. Wince.
A pressure test before the real research. Not a replacement for it.
- A structured prompt system for Claude and ChatGPT.
- 12 ICP persona archetypes engineered for sharp pushback, not agreement.
- A bias-check protocol that flags AI sycophancy and over-confidence.
- A calibration worksheet that turns directional signal into real research questions.
- A weekend workflow you can repeat for every product, pivot, and pricing change.
- A replacement for real customer interviews.
- Predictive — synthetic personas don't buy products with real money.
- A statistical sample. N=12 simulations is not a survey.
- Magic. The output is only as sharp as the inputs you feed it.
- Compatible with founders who want their existing assumptions validated.
Use it responsibly. Synthetic research is directional, not predictive. The bias-check protocol and calibration worksheet exist because the failure mode of this category is treating AI confidence as customer truth. The kit is designed to make that mistake hard.
Four deliverables. Built to work together.
The Structured Prompt System
A Claude/GPT artifact that orchestrates persona-by-persona pressure testing of your messaging, pricing, copy, and feature priorities. Runs unlimited times. Repeatable output.
12 Pre-Built Persona Archetypes
Calibrated ICP archetypes covering bootstrapped SaaS, agency, creator, operator, SMB, enterprise, technical, and skeptic profiles. Each one engineered to push back, not agree.
The Bias-Check Protocol
A checklist that flags AI sycophancy, hallucinated specifics, and over-confidence in synthetic output. Run it after every session. It is the integrity layer.
The Real-World Calibration Worksheet
A Notion + Google Sheets worksheet that translates directional AI signal into sharper questions for the real customer interviews you'll do next. The bridge to ground truth.
Sample output. One persona. The kind of pushback you can't get from your group chat.
“You promise ‘10x faster onboarding.’ I’ve heard ‘10x’ from every vendor this quarter. The number isn’t the problem — proof is. Where’s the case study? Where’s the methodology? I bounced at the hero.”
“$299 Starter / $899 Pro / Talk to Sales. The ‘Talk to Sales’ tier signals you don’t know how to price me yet. I’m in the awkward middle. Show me the Pro feature limit I’ll hit and the math for the upgrade.”
“Concrete time-to-value benchmark. Two customer logos from my segment. Cancel-anytime in writing on the pricing page. The vendor before you had all three. I’m comparing.”
The kit produces a card like this for each of the 12 archetypes you point at your product. The bias-check protocol runs immediately after. The calibration worksheet converts what survives into real research questions you take into real interviews.
How operators actually run it. Friday night to Sunday afternoon.
Load the artifact. Drop in your assets.
Open the structured prompt system in Claude or ChatGPT. Paste your current homepage copy, pricing page, and feature list. Pick the 4–6 persona archetypes that most resemble your real ICP.
Run each persona. Capture the pushback.
Step through each persona prompt. Capture pushback on headline, value prop, pricing tiers, feature priority, and onboarding promise. The system surfaces objection clusters across personas.
Run the bias-check protocol.
Score the output against the checklist: sycophancy flags, hallucinated specifics, over-confident claims, single-source pattern errors. Strike anything that fails. What's left is the directional signal.
Complete the calibration worksheet.
Translate every surviving insight into either (a) a copy change you can ship Monday or (b) a question to ask in your next real customer interview. The output is a 1-pager you act on.
Each one engineered to push back, not agree.
The Cash-Conscious Bootstrapper
$0–$100K MRR. Tracks every dollar. Allergic to enterprise-speak and stock photo founders.
The Time-Starved Agency Owner
Productizing services to escape billable hours. Buys for leverage, not learning.
The Pro Creator
10K–50K followers, turning audience into revenue. Built different. Bored by 'business' tone.
The Operator Buyer
COO or Head of Ops at a $5–$50M company. Budget owner. Reads the case study before the headline.
The Local SMB Owner
Plumber, dentist, contractor, salon. Calls beat clicks. Hates dashboards. Trusts referrals.
The Technical Skeptic
Engineer or CTO. Reads the changelog before the homepage. Bounces at marketing fluff.
The Stretched In-House Marketer
Wears eight hats. $5–$25K monthly discretionary budget. Buys what saves Thursdays.
The Enterprise Evaluator
Committee-driven procurement. Security, compliance, and integration questions first.
The First-Time Founder
Pre-revenue. Learning the language. Confidence-checks every decision against three sources.
The Career Switcher
Corporate to founder. Bringing enterprise instincts to a scrappy stage. Still decoding.
The Reluctant AI Adopter
Burned by hype cycles. Needs proof, not promises. Reads 'AI-powered' as a yellow flag.
The Stack-Maximizer
30+ tools in the stack. Integration depth is the only feature that moves them.
Each archetype is a prompt scaffold — not a static description. The system primes the model to maintain that persona’s worldview, vocabulary, and skepticism pattern throughout the session. Personas can be cloned and tuned for niche-specific ICPs (industry vertical, geography, stage).
Most synthetic research tools sell certainty. This one sells honest signal.
The failure mode of this entire category is treating AI confidence as customer truth. A persona that sounds plausible feels like data. It isn’t.
The Synthetic Customer Research Panel is built around that failure mode, not in spite of it. The bias-check protocol forces you to strike anything the model can’t ground. The calibration worksheet forces you to translate signal into questions, not answers. Together, they make the responsible use of synthetic research the path of least resistance.
That’s the moat. Not the personas. Not the prompts. The integrity layer.
Built for skeptics
Every output ships with a confidence signal and a 'triangulate before acting' footer.
Forces real research next
The calibration worksheet ends in a list of questions for real interviews — not conclusions.
Honest about limits
Synthetic personas don't buy products. The kit never pretends otherwise. Anywhere.
Research the customer, then put what you learn to work.
Once you know how your buyers think, the Brand Voice Engine turns those insights into copy that sounds like you, the Sales Battlecard Builder arms your team for the objections and competitors the research surfaced, and the AI Offer & Landing Conversion Kit rebuilds the page around the language your customers actually used.
The honest answers — including the ones you’re skeptical to ask.
Yes, and that's exactly why we built the bias-check protocol and calibration worksheet into the kit. Synthetic research is directional, not predictive. RedHub AI built this kit to surface positioning gaps and stress-test messaging so you can spend real research budget on the right questions — not replace real research with confident-sounding AI fiction.
Anyone can prompt 'act as a SaaS founder.' This is a structured system: 12 calibrated archetypes built with consistent depth, a prompt scaffold that forces specific pushback patterns instead of agreement, a bias-check protocol that flags AI sycophancy, and a calibration worksheet that translates directional signal into real research questions. The output is repeatable; ad-hoc prompting isn't.
No — and any product that promises that is selling fiction. The Synthetic Customer Research Panel compresses the pre-research phase: pressure-testing positioning, finding obvious holes, and generating sharper questions for real interviews. Think of it as the dry run before the production, not the production itself.
Yes. You'll need access to Claude (Pro or Max) or ChatGPT (Plus or Pro) — the kit is the artifact, prompts, and protocols you run inside those tools. We don't bundle the LLM; you bring your own. Most users run the full kit inside a single Claude Project for persistent context.
Founders inside roughly $0–$5M ARR refining positioning, messaging, or pricing. Especially: bootstrapped SaaS, productized services, creator businesses going pro, and operator-led SMBs. If you've burned weekends rewriting your homepage with no signal back, this is built for you.
Yes. The kit is licensed for single-operator use across unlimited projects — your own products, your agency clients, your portfolio companies. Team licensing is available on request through the RedHub AI support inbox.
Instant access to the structured Claude/GPT artifact (prompt system plus persona library), a downloadable PDF playbook, the bias-check protocol checklist, and the real-world calibration worksheet in both Notion and Google Sheets formats. All assets are delivered from the RedHub AI member hub.
30-day no-questions refund. If the bias-check protocol doesn't change how you read AI outputs — and how you write the questions for your real customer interviews — you shouldn't have paid. Email support and you get the $69 back.
Stop guessing.
Start pressure-testing.
The Synthetic Customer Research Panel is the weekend that saves you the next quarter. $69, once, and you’ll run it on every product you ever ship.
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