# Message test — https://www.getfocus.eu/ After reading your page, only 9 of 15 personas could name a reason to pick you over a similar option. - **Page tested:** https://www.getfocus.eu/ - **Audience tested against:** Heads of R&D and CTOs that are responsible for technology bets at large corporate organizations. - **Personas:** 15 simulated - **Report:** https://grader.wynter.com/r/decision-grade-technology-intelligence-getfocu-CpOugC8 > 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? | 13/15 | 78% | all with reservations | | 2. Relevance | Can they tell what it solves, and who it's for? | 15/15 | 94% | 11 without hesitation, 4 with reservations | | 3. Value | Do they actually want it? | 14/15 | 74% | all with reservations | | 4. Differentiation | Is there a reason to pick you over the alternatives? | 9/15 | 57% | all with reservations | **Brand alignment** (a side metric, not one of the four layers) — 11/15, 63% 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. ### What they thought you sell 1 of the personas who named a category got it wrong: - 1× “Technology scouting / patent analytics platform” --- ## 02 · What to change, layer by layer Ordered worst-first. Specific edits, not a restatement of the score. ### Differentiation **Move the 2003 lithium-ion backtest above the logo wall.** The one piece of evidence readers found checkable — the 2003 lithium-ion versus hydrogen forecast — is not in the copy at all until far down, while the top of the page carries only claims like "Defensible technology bets" and "Signals before market consensus". Promote the backtest into the hero area, directly under the radar, with the date the call was made, what TIR said at the time, and what happened. That chart is the differentiator; it should sit where the claim is made, not after it. *effort medium · impact high · tested against Proof next to the claim* **Replace "Defensible technology bets" with a stated advantage over analyst workflows.** "Defensible technology bets" and "Signals before market consensus" are claims any roadmapping or trend vendor could print unchanged, and readers said the product felt like existing roadmapping software with better data. Say instead what an analyst team cannot do: score every route in a domain, including ones nobody assigned, and refresh the ranking monthly rather than at study delivery. Anchor it to the existing line "Your first decision-grade radar in weeks — not the months a one-off study… *effort medium · impact high · tested against Give a reason to choose you* **Define TIR next to its first appearance on the radar.** The radar axis reads only "TIR · Improvement Rate (%/yr)" and the detail panel shows "107.6%" with no statement of what is being measured or how it is derived. Readers could not judge whether the metric is novel or comparable to anything they already use. Add a one-sentence definition beside the axis label — what inputs the rate is computed from (patent citation networks over time), the unit, and what a high value means for a technology's trajectory. Do the same for "Patents 301": say what… *effort low · impact high · tested against Plain language* ### Clarity **Spell out TRL and the radar quadrant labels in plain words.** The radar leans on undefined shorthand — "TRL · Technology Readiness Level (1–9)", quadrants like "IMMATURE · HIGH TIR · MONITOR CLOSELY" — and stacked jargon around citation networks. Readers followed the fund/monitor/phase-out/ignore framework but could not tell what put a technology in a quadrant. Add a short legend under the radar saying in one line each what makes a route immature versus mature and high versus low TIR, so the picture is readable without decoding acronyms. *effort low · impact medium · tested against Plain language* ### Brand alignment (side metric) **Add a non-automotive radar example beside the EV battery one.** Every concrete artefact on the page is automotive EV — the domain selector says "Automotive EV Battery", the routes are cathodes and electrolytes, the sample question is "Which battery chemistry wins for low-cost EVs?". Readers in materials, chemicals and industrial equipment could not see themselves in it and read the breadth of the logo wall as unfocused. Show a second worked example from chemicals or materials, with its own question and route list, so the method reads as domain-portable… *effort high · impact medium · tested against Name the audience* **Attach one named outcome to a logo near "Trusted by global innovators".** "BUILT ON 30 YEARS OF MIT RESEARCH / Built on MIT research. Trusted by global innovators." asks the reader to take institutional credibility on faith while the logos sit unexplained beneath it. Put one line of substance next to a named customer — the domain they radar'd and the decision it drove — so the wall carries evidence rather than volume. The Moët Hennessy quote already shows this works; it names a role and a real dilemma. *effort medium · impact medium · tested against Proof next to the claim* **Group the logo wall by sector instead of one scattered list.** The flat run of TUDelft, Rabobank, US NAVY, NASA, BASF, Canon, LVMH, Reckitt reads as unrelated pilots rather than domain depth, and it made the company look like an early-stage vendor chasing anything. Break it into labelled clusters — chemicals and materials, defence and aerospace, industrial — so a reader in one of those sectors sees a peer group rather than a scatter. Keep fewer names per cluster if that buys coherence. *effort low · impact medium · tested against Proof next to the claim* --- ## 03 · What is working ### The hero line and problem statement name the audience in the first screen, and readers… Five respondents said the target reader and the problem were identified within the first one or two lines, with no guesswork required. Several added that the copy spoke directly to CTO and R&D leader pain, including the isolation of fund/kill decisions. This was the most consistently praised element of the page. > helps CTOs/R&D leaders pick which tech routes to fund or kill > > — Senior R&D Leader, Automotive, 1001-5000 > "You're judged on the future, but your entire day is the present" and "97% of your time goes to today's fires" are lines that land because they nail the actual pressure of an R&D leadership job > > — Director of R&D, Manufacturing, 5000+ > That's explicitly my job description, no inference needed. The "You ask one question, we run the whole engine" section reinforces it with an actual example question > > — VP of R&D, Industrial Equipment, 1001-5000 > "You're judged on the future, but your entire day is the present" and "It's a very high-stakes solitary game" nail the R&D-leader loneliness I actually feel, so whoever wrote this has talked to real CTOs, not just marketers guessing at pain points. > > — VP of R&D, Manufacturing, 1001-5000 > Pretty quick, actually - the subhead "You're judged on the future, but your entire day is the present" plus "We help CTOs and R&D leaders decide which competing technical routes to: fund, monitor closely, phase out or ignore" tells you the problem and audience in the first two lines. > > — Head of R&D, Industrial Equipment, 5000+ > It was clear fast — the subhead "You're judged on the future, but your entire day is the present" plus the line "We help CTOs, and R&D leaders decide which competing technical routes to: fund, monitor closely, phase out or ignore" told me the problem and audience within the first screen. > > — CTO, Chemical and Materials, 1001-5000 > the hero line "You're judged on the future, but your entire day is the present" plus the immediate follow-up "GetFocus is a technology decision-intelligence system for high-stakes R&D technology bets > > — Director of R&D, Automotive, 5000+ ### The fund/monitor/phase-out/ignore framework was the value respondents could articulate Two respondents said the page solves a real gap between patent-data dumps and actionable funding thresholds, and named the fund/monitor/phase-out/ignore decision framework as useful. One qualified this immediately by noting the TIR numbers behind the framework are unvalidated. The framework itself, separate from the metric, was understood and welcomed. > I'd have an actual trigger point ("thresholds you set") to move from watching to funding, which is exactly the gap I have today with patent tools that just dump data on me. > > — VP of R&D, Manufacturing, 1001-5000 > the fund/monitor/phase-out/ignore buckets are a genuinely useful framing if the underlying TIR numbers hold up. But that's a big "if": the only real proof offered is the 2003 lithium-ion backtest > > — CTO, Industrial Equipment, 1001-5000 ### The 2003 lithium-ion vs hydrogen backtest is the one proof point respondents believed… Four respondents named the 2003 lithium-ion versus hydrogen chart as the credible, checkable demonstration of the forecasting mechanism and the page's real differentiator against generic competitor claims. One noted it still needs independent verification. It is the only piece of evidence on the page that respondents singled out as working. > The 2003 lithium-ion vs hydrogen backtest chart is the one specific thing — shows mechanism, not just a claim. Rules-in territory only if that backtest is independently verifiable > > — Senior R&D Leader, Automotive, 1001-5000 > the patent improvement signal for lithium-ion batteries was already pulling away from internal combustion in the early 2000s" is a concrete, checkable historical claim, not just a promise > > — Director of R&D, Manufacturing, 5000+ > The thing that would actually move me toward this one is the 2003 lithium-ion-vs-hydrogen backtest — "the patent improvement signal for lithium-ion batteries was already pulling away from internal combustion in the early 2000s" is a specific, checkable historical claim > > — CTO, Chemical and Materials, 1001-5000 --- ## 04 · What the personas said ### TIR is used throughout but never defined, so respondents could not judge or compare it Four respondents said the TIR metric appears repeatedly without an auditable formula or citation-weighting methodology, leaving it incomparable to anything else. Related jargon (TRL, citation networks) and the patent-count panel were also flagged as undefined, including what counts as a relevant patent. Respondents said this ambiguity blocked them from assessing whether the metric is novel. > it's used constantly (107.6%, +0.6 vs 2025, YoY +6.8%) as if it's a settled metric, but I never got a formula, just "analyze the citation network to calculate the rate at which the technology is improving on cost and performance" — that's a description of intent, not a definition I could audit or replicate. > > — Director of R&D, Manufacturing, 5000+ > TIR 'improvement rate %/yr' has no stated formula — is it cost decline, energy density, cycle life, some blended index? And 'citation network' analysis is asserted without saying what counts as a relevant patent family or how they weight citations, so I can't tell if two companies' TIR numbers would even be comparable. > > — CTO, Chemical and Materials, 1001-5000 > I'd still want proof the "improvement rate" metric predicts winners better than an analyst with Orbit or PatSnap before I believed it's a new category > > — Chief Technology Officer, Aerospace and Defense, 5000+ > what would rule it out is the patent-count panel on the live radar itself: "301 Patents, YoY +6.8%" sits there with zero methodology note on what counts as a relevant patent or how citation-network weighting works > > — CTO, Chemical and Materials, 1001-5000 > none of which is defined in plain terms on the page, so I'm left guessing whether TIR is a proprietary metric or just a repackaged patent-growth curve > > — Chief Technology Officer, Aerospace and Defense, 5000+ ### The examples are all automotive EV, and respondents in materials, chemicals and defense… Two respondents asked for a materials or chemicals example instead of the automotive EV battery case, and two asked for a defense-sector proof point instead of civilian examples. One added that the page ignores defense procurement realities such as data sovereignty, classification and long-cycle sourcing. The single-vertical example set narrowed who found the page relevant. > I'd need a materials or chemicals-sector example on the page itself, not just automotive EV battery and MIT-research pedigree — something like a specialty-polymer or catalyst technology radar with a named account, since right now everything concrete points at automotive and I'm chemicals. > > — CTO, Chemical and Materials, 1001-5000 > the polish (custom radar UI, "30 years of MIT research") reads more like an investor deck than a sales page built for a defense-sector CTO's actual procurement concerns like data sovereignty, classification, or long-cycle sourcing, none of which are mentioned anywhere > > — Chief Technology Officer, Aerospace and Defense, 5000+ > Right now every proof point is consumer or civilian (EVs, luxury goods), so "for me" would mean seeing our kind of long-cycle, classified-adjacent R&D bet handled, not just gestured at with a NASA/Navy logo > > — Chief Technology Officer, Aerospace and Defense, 5000+ ### One backtest is not enough evidence, and respondents wanted a live run on their own data… Four respondents said the EV-hydrogen backtest is the only proof offered and asked for multiple historical validations, methodology transparency, or a live forward bet on an unresolved technology. Four more said they would need the radar or methodology demonstrated on their own chemistry or a technology they already know before taking a meeting or considering purchase. Respondents treated a generic backtest as less… > I'd take the meeting specifically to press on how TIR is calculated, what the false-positive rate is across other historical backtests (not just the one cherry-picked EV example), and how it would have called a case where the market went the wrong way > > — Director of R&D, Manufacturing, 5000+ > Have them run their citation-network methodology live on a chemistry my own team already has strong convictions about, and get a call that matches or sharpens what we believe instead of contradicting it with no explanation — that's the proof point that turns this from a pitch into a purchase order. > > — VP of R&D, Manufacturing, 1001-5000 > If a competitor on my shortlist showed me two or three backtested cases plus let me run my own unresolved bet through their model, that beats "trust our one MIT-pedigreed example" every time. > > — Head of R&D, Industrial Equipment, 5000+ > I'd want to see the radar validated live on a technology I already know well — something where I can judge if their TRL/TIR calls match what my own engineers already believe > > — Director of R&D, Automotive, 5000+ > the fund/monitor/phase-out/ignore buckets are a genuinely useful framing if the underlying TIR numbers hold up. But that's a big "if": the only real proof offered is the 2003 lithium-ion backtest > > — CTO, Industrial Equipment, 1001-5000 ### The customer logos read as scattered pilots rather than domain credibility Four respondents said the named customers lack relevance to their domain, particularly industrial equipment, and that the logo list suggests pilot chasing across unrelated sectors with no beachhead. Two framed this as an early-stage vendor with an unfocused sales motion, and one said the company is stronger at narrative than at instrumenting proof for skeptics. The proof-by-customer strategy actively reduced… > none are industrial equipment peers doing competing-route evaluation like I do, so I have no proof this works in my domain versus the patent tools I already pay for > > — VP of R&D, Industrial Equipment, 1001-5000 > a sharp backtest story sitting next to an unsourced "301 Patents, +6.8% YoY" panel reads like a young company that's better at narrative than at instrumenting proof for someone as skeptical as me. > > — CTO, Chemical and Materials, 1001-5000 > the mix of "US NAVY, NASA, LVMH, Rabobank, Diam" reads like an early-stage company grabbing every pilot client it can across totally unrelated sectors, not a firm with a focused sales motion yet > > — Chief Technology Officer, Aerospace and Defense, 5000+ > That logo scattergun actually undercuts the pitch — feels like a scrappy team collecting logos rather than a vendor with depth in my industry. > > — Director of R&D, Aerospace and Defense, 5000+ ### Respondents understood the product as a patent-analytics scouting dashboard, but placed… Four respondents correctly described the product as patent-citation-based tech scouting that scores emerging tech maturity to drive fund/watch/kill decisions, and explicitly ruled out project management. However, several said it feels like existing roadmapping software with better data, and asked for proof that TIR outperforms current analyst workflows. Two said they would need a head-to-head comparison against… > Patent-analytics tool that scores emerging tech maturity/improvement rate to guide R&D fund/watch/kill calls. > > — Senior R&D Leader, Automotive, 1001-5000 > I'd want to know how it differs from the patent tools we already run before I take a meeting purely on the pitch > > — VP of R&D, Industrial Equipment, 1001-5000 > Basically a patent-analytics-driven tech scouting tool dressed up as a "decision-intelligence system." The EV/hydrogen backtest is the one bit of proof that makes it feel real - everything else is buzzwords over what's fundamentally roadmapping software with better data underneath. > > — Head of R&D, Industrial Equipment, 5000+ > it's a patent-analytics-driven strategic tech-scouting dashboard for R&D leaders, not a project management tool > > — Director of R&D, Automotive, 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 metric is unusable as a differentiator because it is never defined, which collapses the argument that TIR beats an analyst's spreadsheet.** *(high)* Three respondents flagged TIR as appearing repeatedly with no auditable formula, no citation-weighting methodology and undefined adjacent jargon (TRL, citation networks, relevant patents), and said this blocked them from judging novelty. Four more described the product as roadmapping software with better data and asked for proof TIR outperforms current analyst workflows, with two demanding a head-to-head. The undefined metric and the 'nothing new' read are the same failure: the page asks… - **Proof rests on a single case, and readers will not buy on it — the one credible asset is also the only asset.** *(high)* Four respondents named the 2003 lithium-ion vs hydrogen backtest as the only piece of evidence that worked and the page's real differentiator. In the same breath, six respondents said one backtest is insufficient and asked for multiple historical validations, methodology transparency, a live forward bet, or a run on their own chemistry before taking a meeting. One respondent asked for independent verification even of the chart they praised. The page's entire evidentiary weight sits on an asset… - **The logo wall damages credibility rather than building it, converting social proof into evidence of an unfocused early-stage vendor.** *(high)* Five respondents said the named customers lacked relevance to their domain, that the list reads as pilot chasing across unrelated sectors with no beachhead, and two explicitly framed the company as early-stage with an unfocused sales motion. One said the company is stronger at narrative than at instrumenting proof. This element scores worse than having no logos at all. - **Nothing on the page moves a reader to a meeting; the stated next step is for the vendor to re-prove the product on the reader's own data.** *(high)* Four respondents said they would need the radar or methodology demonstrated on their own chemistry or a technology they already know before taking a meeting or considering purchase, and four asked for further historical validations or a live forward bet. Combined with an undefined metric and irrelevant customer logos, the page's conversion path is a custom pilot the page does not offer. - **The page is built for one vertical and silently disqualifies everyone else, wasting the strong first-screen targeting.** *(medium)* Five respondents praised the hero line and problem statement for naming the reader and pain within one or two lines with no guesswork. But every example on the page is automotive EV: two respondents asked for a materials or chemicals case, two asked for a defense proof point, and one said the page ignores defense procurement realities including data sovereignty, classification and long-cycle sourcing. The page earns attention in the first screen and then hands the reader examples that exclude… - **The only value respondents could articulate is a four-box decision framework, and they themselves flagged its inputs as unvalidated — so the articulated value is hollow.** *(medium)* Two respondents named the fund/monitor/phase-out/ignore framework as the useful contribution, and one immediately qualified it by noting the TIR numbers behind it are unvalidated. Three others said TIR has no auditable formula. A decision framework fed by an undefined score is a taxonomy, not a product claim. --- ## 06 · Who answered | # | Role | Industry | Company size | | --- | --- | --- | --- | | 1 | VP of R&D | Industrial Equipment | 1001-5000 | | 2 | Director of R&D | Manufacturing | 5000+ | | 3 | Senior R&D Leader | Automotive | 1001-5000 | | 4 | Chief Technology Officer | Aerospace and Defense | 5000+ | | 5 | CTO | Chemical and Materials | 1001-5000 | | 6 | Head of R&D | Industrial Equipment | 5000+ | | 7 | VP of R&D | Manufacturing | 1001-5000 | | 8 | Director of R&D | Automotive | 5000+ | | 9 | Senior R&D Leader | Aerospace and Defense | 1001-5000 | | 10 | Chief Technology Officer | Chemical and Materials | 5000+ | | 11 | CTO | Industrial Equipment | 1001-5000 | | 12 | Head of R&D | Manufacturing | 5000+ | | 13 | VP of R&D | Automotive | 1001-5000 | | 14 | Director of R&D | Aerospace and Defense | 5000+ | | 15 | Senior R&D Leader | Chemical and Materials | 1001-5000 | --- ## 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 2026-08-25, then deleted along with the personas and their answers.