# Message test — https://ditchcarbon.com/ After reading your page, 11 of 15 personas could name a reason to pick you over a similar option. - **Page tested:** https://ditchcarbon.com/ - **Audience tested against:** Sustainability and procurement leaders - **Personas:** 15 simulated - **Report:** https://grader.wynter.com/r/ditchcarbon-scope-3-emissions-management-platf-wEc1Yls > These answers are generated by AI, scored on Wynter's B2B Message > Layers framework using behaviorally-diverse simulated personas. The > methodology is real and the critique is directional. What a simulated > persona cannot have is a live budget, a renewal coming up, or a boss > asking about this quarter. --- ## 01 · The scores Every persona answered all four questions. These are four independent proportions of the same panel, not stages of a funnel. | Layer | Question | Cleared the bar | Strength | Of those who passed | | --- | --- | --- | --- | --- | | 1. Clarity | Do they understand what you do? | 15/15 | 78% | all with reservations | | 2. Relevance | Can they tell what it solves, and who it's for? | 15/15 | 87% | 6 without hesitation, 9 with reservations | | 3. Value | Do they actually want it? | 13/15 | 70% | all with reservations | | 4. Differentiation | Is there a reason to pick you over the alternatives? | 11/15 | 63% | all with reservations | **Brand alignment** (a side metric, not one of the four layers) — 13/15, 70% strength (all with reservations). Does the page read like the company you actually are? **Fix first: Differentiation.** Earliest failing layer, walking the sequence in order — not simply the lowest score. --- ## 02 · What to change, layer by layer Ordered worst-first. Specific edits, not a restatement of the score. ### Differentiation **Add a line under the 2M dataset headline stating match rate and data recency.** "Built on emissions profiles from 2 million companies worldwide" says how big the dataset is, not how well it performs. Buyers comparing vendors want the percentage of a typical supplier list that matches and how recent the underlying disclosures are. *effort medium · impact high · tested against Specifics beat superlatives* **Add a short section explaining how supplier matching works and what counts as reported data.** The page claims audit-ready primary data but never says how suppliers are matched or where the figures come from. Spell out the matching inputs, what qualifies as reported emissions, and what is returned when a supplier has not disclosed. *effort medium · impact high · tested against Answer the live objection* **Replace "proprietary dataset" in the IDENTIFY block with a specific reason to choose DitchCarbon.** "Proprietary dataset of company emissions profiles" is a claim any emissions vendor makes. Name the thing rivals cannot say, such as coverage of your supplier list without surveys, or refresh frequency. *effort medium · impact medium · tested against Give a reason to choose you* ### Value **Move the Grant Thornton cycle-time result above the fold, beside the hero claim.** The hero promises "no manual work" with nothing to check it against. The before-and-after on survey cycles shrinking to three or four weeks is the most checkable number on the page and should sit next to the promise it proves. *effort low · impact high · tested against Proof next to the claim* **Add industry and company size to each customer proof line, such as Hikma's.** "Reduced manual aggregation, with emissions forecasting established over six months" floats free of any context a manufacturing or pharma buyer can map onto. Say the sector, supplier count and company size beside each result. *effort low · impact medium · tested against Proof next to the claim* ### Clarity **Replace "Built on trusted inputs" with a heading naming the actual sources.** "Trusted inputs" tells a reader nothing and could head a section on any product. Use the sources themselves: procurement data, supplier disclosures and public climate records. *effort low · impact medium · tested against Concrete over abstract* ### Relevance **Add a line under the hero naming the buyer by role and situation.** Readers currently work out who the page is for from logos and job titles. Write a line naming the Scope 3 lead or procurement team with a fragmented supplier base who is still running supplier surveys. *effort low · impact medium · tested against Name the audience* ### Brand alignment (side metric) **State in the hero subhead whether DitchCarbon is an API, a dashboard or a service.** "Get audit-ready primary emissions data at scale" leaves the delivery format unidentified. Say plainly what buyers receive: a platform login, an API feed into their existing carbon accounting tool, or both. *effort low · impact medium · tested against Show the product early* --- ## 03 · What is working ### The 2M+ company emissions database and supplier-matching premise is understood on first… Seven respondents correctly restated the offering: matching suppliers against a database of roughly two million companies' reported emissions to replace manual Scope 3 surveys. Several named the dataset size unprompted. > They match your suppliers against a database of ~2 million companies' actual reported emissions data, so instead of surveying suppliers manually you get Scope 3 visibility fast > > — Director of Procurement, Manufacturing, 501-1000 > a Scope 3 supply-chain emissions data platform — basically a data-matching and estimation tool, not a measurement tool in the metering sense > > — Sustainability Manager, Pharmaceuticals, 1001-5000 > matches suppliers to emissions profiles so you skip manual surveys > > — Director of Sustainability, Healthcare, 501-1000 > They match your suppliers against a database of 2 million+ company emissions profiles so you get primary, already-reported Scope 3 data instead of surveying suppliers yourself > > — VP of Sustainability, Retail and Consumer Goods, 1001-5000 ### The hero line and three-step structure land the problem above the fold Four respondents said the problem and the pain it addresses are communicated immediately, crediting the hero line and the three-step structure. > The hero line — "Don't just measure emissions. Reduce them. Get audit-ready primary emissions data at scale, no manual work" — tells me the problem in one breath > > — Director of Procurement, Manufacturing, 501-1000 > The "Trusted by leading Scope 3 teams worldwide" line and logos (Haleon, GSK, Philip Morris - companies that look like mine) made it obvious who this is for without me having to infer much. > > — Senior Procurement Manager, Pharmaceuticals, 501-1000 ### Named-customer cycle-time outcomes are the proof points that justify a meeting Four respondents cited the Grant Thornton before-after timeline and reduction of survey cycles to three or four weeks as checkable, specific evidence worth acting on. > I'd cut weeks out of our annual Scope 3 supplier data collection — going from chasing surveys to getting matched, already-reported data for "days, not months" > > — Director of Procurement, Manufacturing, 501-1000 > the Haleon and Grant Thornton quotes ("reported our 2024 emissions within three to four weeks") are the kind of proof point that makes me sit up, because that's a real cycle-time claim, not just a dashboard promise. That's worth a meeting, but not worth a budget line yet > > — Senior Sustainability Manager, Financial Services, 5000+ > Grant Thornton's quote about reporting "within three to four weeks" because "everything we needed was already in the public domain" is the specific line that matters to me > > — Director of Procurement, Financial Services, 1001-5000 > the Grant Thornton quote about reporting 2024 emissions "within three to four weeks" because "everything we needed was already in the public domain" is the specific number that matters to me > > — Sustainability Manager, Healthcare, 5000+ --- ## 04 · What the personas said ### Matching methodology is unexplained, especially for suppliers that do not disclose Four respondents could not tell how matching works, what counts as 'reported' data, or what happens to non-disclosing suppliers, and said this undermines the audit-readiness claim. > if I'm honest the fuzziness is in the word 'matches': it never says what match rate looks like for a mid-size manufacturer, or whether 'reported' means CDP disclosures, sustainability reports, or something thinner like estimated factors dressed up as reported > > — Director of Procurement, Manufacturing, 501-1000 > Whether it's "audit-ready" the way they claim depends on how that matching actually works and what counts as a verified disclosure versus a modeled estimate, which the page doesn't spell out clearly enough for me > > — Sustainability Manager, Pharmaceuticals, 1001-5000 > the page never says whether that's name-matching, spend-category matching, or something probabilistic with a confidence threshold > > — Procurement Manager, Manufacturing, 5000+ ### Vague verbs leave the delivery format unidentified One respondent could not determine whether the product is an API, a dashboard, or a managed service. Another flagged marketing-deck language standing in for substantiation. > It's the vague verbs doing the work - "match," "analyse," "turn insights into action" - none of which tell me if this is an API feed, a dashboard, or a service team doing outreach to my suppliers on my behalf. > > — Senior Sustainability Manager, Financial Services, 5000+ > "transparent methodology" and "confidence scoring" are named but never shown, which reads like a company still building out its substantiation to match its ambition > > — Sustainability Manager, Pharmaceuticals, 1001-5000 ### No proof point speaks to specific industries respondents cared about Respondents in manufacturing and pharma contexts found no sector-specific evidence, including for mid-size companies with fragmented supply bases. > A manufacturing-specific proof point - a logo or case study from a company our size with a messy, fragmented tier-1/tier-2 supply base, not just pharma and tech giants - would make me think 'this is for me' > > — Director of Procurement, Manufacturing, 501-1000 > I'd need a pharma-specific proof point - a named pharma customer quote with a number attached, not just Haleon's logo sitting in a row of unrelated industries > > — Senior Procurement Manager, Pharmaceuticals, 501-1000 ### Without a competitor comparison, the dataset claim does not hold as an advantage Four respondents said they would check Watershed, Persefoni, or other rivals before shortlisting, and that the dataset size loses weight absent a side-by-side on match rate and data recency. > what would tip it is a side-by-side on actual match rate and data recency for our sector - whoever shows me real coverage on our supplier list first wins the meeting > > — Director of Procurement, Manufacturing, 501-1000 > "Compare 17 Scope 3 software platforms" sitting right there as a page link tells me they know I'm shortlisting against competitors, so I'd actually click that before taking their word for anything > > — Sustainability Manager, Pharmaceuticals, 1001-5000 > DitchCarbon wins if it can show a side-by-side data coverage number against them, not just an absolute 2 million figure, because scale alone means nothing without knowing if the other guy has 3 million or better accuracy on my actual vendor list. > > — Senior Sustainability Manager, Financial Services, 5000+ > "Compare 17 Scope 3 platforms" link would make me check rivals first > > — Director of Sustainability, Healthcare, 501-1000 ### Audience is inferred from logos and job titles rather than stated Three respondents worked out who the page is for from customer logos and quoted titles, not from any explicit statement of the target buyer. > The intended reader is implied rather than stated outright — I had to infer "Scope 3 / procurement / sustainability teams at large companies" from the logos > > — Procurement Manager, Manufacturing, 5000+ > The "who" is never stated in plain words like "for procurement teams" - I had to infer it from the IDENTIFY/ANALYSE/ACT framing and the named titles in the quotes > > — Director of Procurement, Financial Services, 1001-5000 --- ## 05 · The hardest read An adversarial pass over the findings. Every claim below was checked against the panel's own answers; unsupported ones were dropped. - **The page's central claim collapses the moment a buyer asks how it works.** *(high)* Three respondents could not tell how matching works, what counts as 'reported' data, or what happens to non-disclosing suppliers, and said this undermines the audit-readiness claim — the one claim a Scope 3 buyer must trust. - **Comprehension of the premise is being mistaken for belief in it.** *(high)* Four restated the 2M+ database premise and several named the dataset size unprompted, yet four others said that size carries no weight without a side-by-side on match rate and recency against Watershed or Persefoni. - **The page sends buyers to competitors' sites to finish the evaluation it started.** *(high)* Four respondents said they would check Watershed, Persefoni, or other rivals before shortlisting. The page supplies the category framing and lets a competitor supply the decision criteria. - **The only evidence that earns a meeting is a single customer story, and it does not generalise.** *(high)* Four respondents cited the Grant Thornton cycle-time timeline as the checkable proof worth acting on, while two in manufacturing and pharma found nothing sector-specific, including for mid-size firms with fragmented supply bases. - **Buyers cannot tell what they would actually be buying.** *(medium)* One respondent could not determine whether the product is an API, a dashboard, or a managed service; another flagged marketing-deck language standing in for substantiation. Procurement cannot scope an unidentified delivery format. - **The page makes qualification the reader's job.** *(medium)* Two respondents reverse-engineered the target buyer from customer logos and quoted job titles because no explicit statement of audience exists, which compounds the absence of sector-specific evidence for manufacturing and pharma readers. --- ## 06 · Who answered | # | Role | Industry | Company size | | --- | --- | --- | --- | | 1 | Director of Procurement | Manufacturing | 501-1000 | | 2 | Sustainability Manager | Pharmaceuticals | 1001-5000 | | 3 | Senior Sustainability Manager | Financial Services | 5000+ | | 4 | Director of Sustainability | Healthcare | 501-1000 | | 5 | VP of Sustainability | Retail and Consumer Goods | 1001-5000 | | 6 | Procurement Manager | Manufacturing | 5000+ | | 7 | Senior Procurement Manager | Pharmaceuticals | 501-1000 | | 8 | Director of Procurement | Financial Services | 1001-5000 | | 9 | Sustainability Manager | Healthcare | 5000+ | | 10 | Senior Sustainability Manager | Retail and Consumer Goods | 501-1000 | | 11 | Director of Sustainability | Manufacturing | 1001-5000 | | 12 | VP of Sustainability | Pharmaceuticals | 5000+ | | 13 | Procurement Manager | Financial Services | 501-1000 | | 14 | Senior Procurement Manager | Healthcare | 1001-5000 | | 15 | Director of Procurement | Retail and Consumer Goods | 5000+ | --- ## 07 · Before you act on this The methodology is real, and the critique is directional. What a simulated persona cannot have is a live budget, a renewal coming up, or a boss asking about this quarter. **Validate anything you're betting on with real ICPs who are actually in-market.** Being wrong is more expensive than you think. Finding out is cheaper than you'd guess. Wynter runs message testing with verified B2B professionals — trusted by HubSpot, RingCentral, Shopify, Cognism, Paddle, Veeam, Rippling and Miro. This report is kept for 60 days from 2026-10-05, then deleted along with the personas and their answers.