Clarity
Do they understand what you do?
Strong15 of 15
15 could name what kind of product this is, unprompted.
Saved report, kept for 60 days — expires in 47 days. Re-opening it is free.
01
Your verdict
Relevance
Can they tell what it solves, and who it's for?
Strong15 of 1515 could quickly tell what problem it solves and who it is for.
Value
Do they actually want it?
Strong14 of 1514 would take a meeting to learn more.
Differentiation
Fix firstIs there a reason to pick you over the alternatives?
Strong13 of 1513 could name a reason to pick you over a similar option.
See what they thought you were
Your page describes: Growth advisory. They said:
- 1×AI-driven market research/growth consultingmatches
- 1×Causal AI growth/pricing consultingmatches
- 1×Causal AI insights / growth strategy consultancymatches
- 1×Causal AI market research / insights advisorymatches
11 couldn't name one; 4 got it right.
Four separate measures, not stages: all 15 personas answered all four questions. Each square is one persona.
Additional signalBrand alignment14 of 15StrongShow finding ▸
Replace loosely defined tiers with fixed scope and price. Not one of the four layers, and it does not affect the scores above or the order to fix them in.
These are 15 simulated buyers. Want 15 real ones?
Test with humans02
Fix these firstFix these first
Three edits, in the order that matters.
The first is on your weakest layer, the second on the next, the third on the layer the most buyers had a problem with. Each says what to change on the page and why, with one simulated answer behind it.
Show mechanism beside every client result, as Interquell does.
Why: "Interquell: up to 5× profit per product through causal pricing" lands because it names the lever. "Sonos: a whole new product category, launched right" and "T-Mobile USA: 4× revenue at record profit" state outcomes with no mechanism. Add the specific driver each engagement uncovered — the demand plateau, the category code, the barrier removed — so the results read as repeatable method rather than vendor luck.
3 of 15 raised this
“the pricing tiers ("From €5k/month," "From €50k") are so vague I can't tell if this is a real engagement or a McKinsey-style anchor-low-then-scope-creep game”
Chief Marketing Officer, Consumer Electronics · 5000+ employeessimulated Moves DifferentiationProof next to the claimAdd baselines and sources to the case study numbers.
Why: "$10B+ Generated Value", "4× revenue", "up to 5× profit per product" arrive without a starting point, timeframe or attribution basis, which invites a senior reader to discount all of them. Give each figure its denominator and period — over what baseline, across how many months, measured how — and attribute it, ideally with a named client contact or published case link next to the claim.
3 of 15 raised this
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see…” Show full quote
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see the base case behind them.”
CEO, Consumer Electronics · 201-500 employeessimulated Moves ValueProof next to the claimExplain the Causal AI method in plain mechanics, not labels.
Why: "Deep Implicit Research + Causal AI" under "How we find the truth" names a method but never shows how it works. Replace the abstraction with three concrete steps a reader can picture: what data goes in (e.g. implicit response tests with n= real category buyers), what the model does with it (quantifies which motives causally drive choice, not correlate with it), and what comes out. The FAQ is too late — the mechanics belong in this section.
6 of 15 raised this
“Consulting shop selling causal-AI market research for pricing and brand decisions. Fancy insights firm.”
Chief Executive Officer, Luxury Goods · 1001-5000 employeessimulated Moves ClarityPlain language
Keep these · 2
These landed. Keep the wording when you edit around it.
- Keep · Differentiation
The Interquell demand-plateau example works because it shows a mechanism, not just an…
“T-Mobile "4x revenue at record profits" is specific and checkable”
Chief Executive Officer, Luxury Goods · 1001-5000 employeessimulated - Keep · Value
The free Double Jeopardy Test is the offer respondents named as their entry point
“The Double Jeopardy Test is the specific thing that would tip me toward them over a generic strategy shop — "we run the decision past three leading AIs...…” Show full quote
“The Double Jeopardy Test is the specific thing that would tip me toward them over a generic strategy shop — "we run the decision past three leading AIs... then pressure-test it against our proprietary knowledge graph" is a concrete, low-risk way to see their methodology on my own decision before I commit real budget, and it's free.”
CEO, Automotive · 201-500 employeessimulated
03
All recommendations
Differentiation
Strong13 of 15Moves DifferentiationLead with the use case
Name the product category SUPRA competes in.
Why: The header "Root-Cause Growth Advisory" is an invented label, and nothing else on the page places the offer — research supplier, strategy consultancy, or decision-intelligence software. Add one line near the H1 that says what kind of provider this is and how it differs from the alternative the buyer is weighing, e.g. quantified causal demand research replacing conventional brand tracking and consultant judgement.
3 of 15 raised this
“the pricing tiers ("From €5k/month," "From €50k") are so vague I can't tell if this is a real engagement or a McKinsey-style anchor-low-then-scope-creep game”
Value
Strong14 of 15Moves ValueAnswer the live objection
Offer a bounded first step on one real decision.
Why: The page presents an advisory relationship with no visible small entry point, so the reader has no low-risk way in. Add a named scoped engagement — one pricing or brand decision, fixed price, fixed timeline, defined deliverable — and offer a reference call with an existing client insights lead. This is the step buyers say they would actually take before any larger commitment.
3 of 15 raised this
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see…” Show full quote
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see the base case behind them.”
Moves ValueOne clear next action
Promote the Double Jeopardy Test as the primary CTA.
Why: The free test is the strongest asset here but competes at the top with "Download the Growth Whitepaper" and later with "Discuss your case" and "How Demand Architecture works". Make "Take the Double Jeopardy Test" the single hero action, demote the whitepaper to a text link, and state on the test block what the reader gets back and that it runs on their own decision and data.
3 of 15 raised this
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see…” Show full quote
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see the base case behind them.”
Clarity
Strong15 of 15Moves ClarityConcrete over abstract
State the deliverable: what the client receives and when.
Why: Nothing on the page says what is actually handed over. After "Decision-grade evidence you can take to the board", add a concrete line naming the artefacts and timeframe — e.g. a quantified demand-driver map per segment, ranked price and claim levers, and a board-ready decision recommendation, delivered in X weeks. Readers currently cannot tell whether they are buying a study, software, or a consulting engagement.
6 of 15 raised this
“Consulting shop selling causal-AI market research for pricing and brand decisions. Fancy insights firm.”
Moves ClarityConcrete over abstract
Define "implicit measurement" where it first appears.
Why: "We measure the subconscious motives, barriers and value drivers behind real choices" reads as marketing gloss because the measurement itself is invisible. Say in plain words how subconscious drivers are captured — reaction-time based choice tasks, real purchase behaviour, whatever the actual instrument is — so the claim "Evidence, not opinion" has something under it.
6 of 15 raised this
“Consulting shop selling causal-AI market research for pricing and brand decisions. Fancy insights firm.”
Relevance
Strong15 of 15Moves RelevanceName the audience
Add an automotive decision example to the industry blocks.
Why: The page invokes premium auto buyers and shows the Audi logo, but every worked example belongs to pet food, FMCG or telco. Give automotive the same treatment the Pet Food block gets: name the decision at stake — trim and options pricing, EV positioning, dealer versus DTC — and the demand driver the work uncovered, so an auto reader sees their own case rather than inferring it.
2 of 15 raised this
“What would rule them out, or at least stall me, is the industry mix: pet food, telecom, insurance, FMCG — zero automotive logos or case studies.”
Brand alignment
Strong14 of 15Moves Brand alignmentAnswer the live objection
Replace loosely defined tiers with fixed scope and price.
Why: The tiered engagement framing reads as an open-ended, scope-creeping consulting relationship, which undercuts the evidence-driven, decision-grade positioning the rest of the copy claims. State for each tier what is in scope, what is delivered, and either the price or the price mechanism, so the commercial model matches the promise of "Evidence, not opinion."
04
Buyer evidence
Biggest risks
A deliberately adversarial read of the same answers. Each claim was checked back against what the personas said and dropped if nothing supported it.
- high
The page sells a method nobody can describe back, so it cannot be evaluated, let alone bought.
Six respondents said the proprietary method is named without mechanics, model, data or logic, and called it abstract jargon; two could not identify the deliverable. Nine said the problem and buyer land fast but the mechanism behind Causal AI is left to inference or buried in the FAQ. The page's clearest asset — audience framing — is attached to an unexplainable product.
- high
The case studies are doing the page's persuasion work, and half of them are doing it backwards.
Three respondents believed the Interquell demand-plateau and T-Mobile figures because a mechanism was shown, while four discounted the same case study format for arriving without baselines, sourcing or causal models — one calling unsourced numbers actively damaging with a senior buyer. The identical asset produces belief and doubt depending on whether mechanism appears, which means the page's outcome-only figures are subtracting credibility, not adding it.
- high
The page cannot close anyone. Its own best-case outcome is a free test.
Four respondents described an identical purchase path — entry tier, one bounded decision, a reference call — and no respondent described committing on the strength of the page alone. Three named the free Double Jeopardy Test as their entry point, one as a precondition. The strongest asset on the page is the one that generates no revenue.
- high
The one thing the page proves is that mechanism sells and the page mostly withholds it.
Where mechanism appeared — the Interquell demand plateau — three respondents said it outweighed generic vendor pitches and was testable against their own SKUs. Where it did not, six called the method jargon and four discounted the numbers. The evidence for the fix is already on the page and unevenly applied.
- medium
Framing the category around premium automotive buyers and then showing no automotive work reads as a bluff.
Three respondents flagged the absence of automotive examples in the case studies despite the category framing, with one doubting bench depth for a sustained automotive engagement. Logos did not close the gap. The page invites the exact comparison it fails.
- medium
Without a stated category, the pricing tiers become the only thing buyers can interpret — and they interpret them as risk.
Two respondents could not place the offering in a product category despite clear problem framing and logos; another read the loosely defined tiers as an open-ended, scope-creeping engagement. When the page will not say what it is, buyers price the ambiguity themselves and against the seller.
Differentiation
Product-category positioning stays vague, and the pricing tiers read as scope creep
3 of 15
“the pricing tiers ("From €5k/month," "From €50k") are so vague I can't tell if this is a real engagement or a McKinsey-style anchor-low-then-scope-creep game”
Chief Marketing Officer, Consumer Electronics · 5000+ employeessimulated See all 3 comments
“I'd need my category named specifically — CPG, retail, whatever — with a number attached, not just logos like P&G and Unilever sitting in a scroll bar”
Chief Executive Officer, Consumer Packaged Goods · 1001-5000 employeessimulated “the FAQ positioning against McKinsey/Simon-Kucher and Kantar/Ipsos is clearly aimed at someone who already knows those names and is comparison-shopping”
Chief Executive Officer, Automotive · 1001-5000 employeessimulated The Interquell demand-plateau example works because it shows a mechanism, not just an…
4 of 15 · what worked
“T-Mobile "4x revenue at record profits" is specific and checkable”
Chief Executive Officer, Luxury Goods · 1001-5000 employeessimulated See all 3 comments
“The Interquell pricing line — "products sit on a demand plateau that carries a far higher optimal price," leading to "up to 5x profits per product" — is…” Show full quote
“The Interquell pricing line — "products sit on a demand plateau that carries a far higher optimal price," leading to "up to 5x profits per product" — is the one thing here that's specific enough to act on”
Chief Executive Officer, Consumer Packaged Goods · 1001-5000 employeessimulated “The specific thing that would pull me toward them is the Interquell pricing example: "some products sit on a demand plateau that carries a far higher optimal price"…” Show full quote
“The specific thing that would pull me toward them is the Interquell pricing example: "some products sit on a demand plateau that carries a far higher optimal price" leading to "up to 5x profits per product"”
CMO, Telecommunications · 501-1000 employeessimulated
Value
Case study numbers are unsourced and lack baselines, so respondents discount the…
3 of 15
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see…” Show full quote
“the Interquell "up to 5× profit per product" and T-Mobile "4× revenue at record profits" numbers are the kind of thing that would matter if I could see the base case behind them.”
CEO, Consumer Electronics · 201-500 employeessimulated See all 3 comments
“a page that respects my time would footnote "4× revenue" with a timeframe and baseline, not just drop it as a headline”
Chief Executive Officer, Automotive · 1001-5000 employeessimulated “the named case studies — T-Mobile's "4x revenue," Sonos, Interquell's "up to 5x profits" — never show the mechanism, just the outcome”
Chief Executive Officer, Telecommunications · 1001-5000 employeessimulated Nobody would buy the full engagement first; they want a bounded pilot on one real decision
3 of 15
“A reference call with the actual T-Mobile or Sonos insights lead who'd walk me through the before/after numbers and confirm SUPRA's model, not the agency's spin, drove the…” Show full quote
“A reference call with the actual T-Mobile or Sonos insights lead who'd walk me through the before/after numbers and confirm SUPRA's model, not the agency's spin, drove the result - that's the one thing that converts curiosity into a paid pilot”
Chief Marketing Officer, Consumer Electronics · 5000+ employeessimulated See all 3 comments
“I'd want the Double Jeopardy Test or the smaller "Top 5% Growth Diagnostic" (from €50k, 4 weeks) as a bounded pilot on one real pricing or comms decision,…” Show full quote
“I'd want the Double Jeopardy Test or the smaller "Top 5% Growth Diagnostic" (from €50k, 4 weeks) as a bounded pilot on one real pricing or comms decision, not a full engagement”
CMO, Telecommunications · 501-1000 employeessimulated “A pricing or brand call where their read directly contradicted what my internal team and agencies were converging on, and where being right on that call was later…” Show full quote
“A pricing or brand call where their read directly contradicted what my internal team and agencies were converging on, and where being right on that call was later verifiable in the P&L — one real save like that a year justifies the retainer”
Chief Marketing Officer, Luxury Goods · 5000+ employeessimulated The free Double Jeopardy Test is the offer respondents named as their entry point
3 of 15 · what worked
“The Double Jeopardy Test is the specific thing that would tip me toward them over a generic strategy shop — "we run the decision past three leading AIs...…” Show full quote
“The Double Jeopardy Test is the specific thing that would tip me toward them over a generic strategy shop — "we run the decision past three leading AIs... then pressure-test it against our proprietary knowledge graph" is a concrete, low-risk way to see their methodology on my own decision before I commit real budget, and it's free.”
CEO, Automotive · 201-500 employeessimulated See all 2 comments
“I'd take the free Double Jeopardy Test on one live pricing or launch decision before I'd sign anything at €50k+, because the case studies are compelling but I…” Show full quote
“I'd take the free Double Jeopardy Test on one live pricing or launch decision before I'd sign anything at €50k+, because the case studies are compelling but I have no idea yet if my category/data would produce something as clean as their T-Mobile or Sonos examples.”
CMO, Consumer Electronics · 501-1000 employeessimulated
Clarity
Proprietary terminology is asserted rather than explained, and respondents call it…
5 of 15
“Phrases like "we see the causal logic behind every recommendation" and "decision-grade evidence" sound reassuring but never show the actual model or data behind them — that's marketing…” Show full quote
“Phrases like "we see the causal logic behind every recommendation" and "decision-grade evidence" sound reassuring but never show the actual model or data behind them — that's marketing language standing in for method”
CEO, Automotive · 201-500 employeessimulated See all 5 comments
“The phrases themselves are abstract nouns doing all the work — 'Demand Architecture,' 'Deep Implicit Research,' 'Causal AI' — none of which tell me if I'm buying a…” Show full quote
“The phrases themselves are abstract nouns doing all the work — 'Demand Architecture,' 'Deep Implicit Research,' 'Causal AI' — none of which tell me if I'm buying a study, software, or a consultant's time.”
Chief Executive Officer, Consumer Packaged Goods · 1001-5000 employeessimulated “I'd still want to see the actual mechanics of their "knowledge graph" and how implicit measurement is captured before I trust the label, because "Causal AI" is doing…” Show full quote
“I'd still want to see the actual mechanics of their "knowledge graph" and how implicit measurement is captured before I trust the label, because "Causal AI" is doing a lot of unexplained work here.”
CMO, Telecommunications · 501-1000 employeessimulated “they're used as if they're established category terms, but they're proprietary-sounding jargon with no plain definition, so I had to infer from context”
Chief Marketing Officer, Consumer Packaged Goods · 5000+ employeessimulated “The mechanism is still a bit of a black box to me — "causal AI" and "implicit research" get repeated a lot without a clear step-by-step of the…” Show full quote
“The mechanism is still a bit of a black box to me — "causal AI" and "implicit research" get repeated a lot without a clear step-by-step of the actual method”
CMO, Automotive · 501-1000 employeessimulated The problem and buyer are legible fast, but the mechanism behind Causal AI is not
6 of 15
“Consulting shop selling causal-AI market research for pricing and brand decisions. Fancy insights firm.”
Chief Executive Officer, Luxury Goods · 1001-5000 employeessimulated See all 6 comments
“tells you what it does within seconds, and the client logos plus named cases (T-Mobile, Sonos, Allianz) tell you who it's for: CMOs and growth/insights leads at big…” Show full quote
“tells you what it does within seconds, and the client logos plus named cases (T-Mobile, Sonos, Allianz) tell you who it's for: CMOs and growth/insights leads at big consumer brands”
Chief Marketing Officer, Consumer Electronics · 5000+ employeessimulated “the hero line "Consensus feels safe. That's what makes it dangerous" plus "SUPRA finds the root cause of growth and turns it into decisions in brand, innovation, communication,…” Show full quote
“the hero line "Consensus feels safe. That's what makes it dangerous" plus "SUPRA finds the root cause of growth and turns it into decisions in brand, innovation, communication, and pricing" tells me the problem”
CMO, Telecommunications · 501-1000 employeessimulated “"Causal AI" and "Deep Implicit Research" are named but not explained until the FAQ, so my first pass gives me the who and the what but not really…” Show full quote
“"Causal AI" and "Deep Implicit Research" are named but not explained until the FAQ, so my first pass gives me the who and the what but not really the how”
Chief Executive Officer, Telecommunications · 1001-5000 employeessimulated “What's still missing is a crisp one-line definition of "Causal AI" itself; I had to infer what it actually does from the case studies rather than any stated…” Show full quote
“What's still missing is a crisp one-line definition of "Causal AI" itself; I had to infer what it actually does from the case studies rather than any stated methodology”
Chief Marketing Officer, Luxury Goods · 5000+ employeessimulated “The "who" is inferred rather than stated outright, but the client logos (T-Mobile, Sonos, Allianz, P&G) and case studies make it obvious this is aimed at CMOs/leadership teams…” Show full quote
“The "who" is inferred rather than stated outright, but the client logos (T-Mobile, Sonos, Allianz, P&G) and case studies make it obvious this is aimed at CMOs/leadership teams making high-stakes brand, pricing or innovation calls”
CMO, Consumer Electronics · 501-1000 employeessimulated
Relevance
Absence of automotive proof makes the page feel off-target for that buyer
2 of 15
“What would rule them out, or at least stall me, is the industry mix: pet food, telecom, insurance, FMCG — zero automotive logos or case studies.”
CEO, Automotive · 201-500 employeessimulated See all 3 comments
“I'd need a line that names my actual situation — a mid-size automotive OEM or supplier under margin pressure trying to move beyond incremental optimization — rather than…” Show full quote
“I'd need a line that names my actual situation — a mid-size automotive OEM or supplier under margin pressure trying to move beyond incremental optimization — rather than just consumer brand logos like Sonos or L'Oréal; right now the industry list skips automotive entirely”
CMO, Automotive · 501-1000 employeessimulated “a page this personality-driven around one founder makes me wonder about bench depth on a live automotive engagement.”
CEO, Automotive · 201-500 employeessimulated
05
How this works
Who we simulated (15 personas)
15 AI-simulated personas matched to your target market. Each answered independently, without seeing your goal, the scoring criteria, or each other’s answers. Attribution is role, industry and company size only.
Chief Executive OfficerConsumer Packaged Goods · 1001-5000 employeesUS
Chief Marketing OfficerConsumer Electronics · 5000+ employeesEU
CEOAutomotive · 201-500 employeesUS
CMOTelecommunications · 501-1000 employeesEU
Chief Executive OfficerLuxury Goods · 1001-5000 employeesUS
Chief Marketing OfficerConsumer Packaged Goods · 5000+ employeesEU
CEOConsumer Electronics · 201-500 employeesUS
CMOAutomotive · 501-1000 employeesEU
Chief Executive OfficerTelecommunications · 1001-5000 employeesUS
Chief Marketing OfficerLuxury Goods · 5000+ employeesEU
CEOConsumer Packaged Goods · 201-500 employeesUS
CMOConsumer Electronics · 501-1000 employeesEU
Chief Executive OfficerAutomotive · 1001-5000 employeesUS
Chief Marketing OfficerTelecommunications · 5000+ employeesEU
CEOLuxury Goods · 201-500 employeesUS
Methodology
Every answer on this page was written by an AI model role-playing a buyer profile, scored on Wynter’s B2B Message Layers framework. The personas were sampled in code across role, industry, company size and behavioral traits; the model wrote only the answers. Scores arrive through fixed verdict categories and the counts are computed in our own code, so no number here was written by a model.
Score details: the count and the strength
The count is how many personas cleared the bar on each question. A yes can be unhesitating or come with reservations; the scorecard counts both as a yes, and this is the only place the difference is shown. Per layer:
- Clarity: 15 of 15, all with reservations
- Relevance: 15 of 15, 3 without hesitation, 12 with reservations
- Value: 14 of 15, all with reservations
- Differentiation: 13 of 15, all with reservations
These answers are AI-simulated and directional. Validate anything you’re betting on with real buyers, your ICPs.
Your next 3 moves
- 1.Show mechanism beside every client result, as Interquell does.
- 2.Add baselines and sources to the case study numbers.
- 3.Explain the Causal AI method in plain mechanics, not labels.
See what real buyers say.
A detailed, section-by-section message test report from verified B2B professionals who are actually in-market for what you sell.
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RetentionThis report is kept for 60 days, until 24 Oct 2026, then deleted along with the personas, their answers and everything derived from them. The link stays live for that whole period so it can be shared or revisited, and stops working afterwards.
The email address it was requested from is kept beyond that, because it subscribes you to the newsletter — that was the price of the report. You can unsubscribe in one click from any issue, which stops the email without affecting a report still inside its 60 days. The public report page never shows the requester’s address.
The email address it was requested from is kept beyond that, because it subscribes you to the newsletter — that was the price of the report. You can unsubscribe in one click from any issue, which stops the email without affecting a report still inside its 60 days. The public report page never shows the requester’s address.