Consumer Neuroscience
Consumer neuroscience, run as research — not as a sales prop.
A nine-signal stack spanning neural-response prediction, facial expression coding, eye tracking, NLP sentiment, cultural-trope analysis, social monitoring, semantic-to-behavior prediction, power-law attention modeling, and generative-media feedback. Built to survive a methods review.
Eight weeks. Written readout. Defensible.
See the platform. Bring your skeptic.
Seeing this as an operator? The Measurement Instrument covers the same nine signals from a decision and attribution angle — and includes the pilot cohort application.
Neuromarketing has a credibility problem. We're trying to fix it from inside.
For twenty years, “neuromarketing” has been sold as a single hero signal — an EEG cap, an fMRI scan, a galvanic skin response graph — wrapped in academic-sounding language and priced like an enterprise SaaS contract. The signal was often real. The interpretation rarely survived contact with a methods review.
We do not believe any one signal predicts behavior. We believe the convergence of many signals does. That is the entire thesis of this practice, and it is the reason the page below describes nine measurement layers instead of one hero technology. For the operator-facing instrument, see the operator-level signal instrument.
Nine signals. One convergent answer.
No single layer is allowed to speak for the audience. Each one is a check on the others.
NeuroLens
Neural-response prediction
Measures: Predicted EEG-class neural response to video, second-by-second, without a headset on the viewer.
Earns it: Catches attention loss and emotional flatline at the frame where it happens, not the survey after.
Facial Expression Recognition
FER
Measures: Micro-expression intensity across six basic affects, frame by frame, on opt-in viewer webcam streams.
Earns it: Shows the gap between what a viewer says they felt and what their face actually did.
Eye Tracking
Gaze & attention
Measures: Gaze fixation, dwell time, saccade pattern, and attentional drop-off across creative or page layout.
Earns it: Separates "saw it" from "looked at it" from "looked away." Stated recall lies. Eyes don't.
NLP Sentiment Analysis
Language signal
Measures: Affect, stance, intensity, and rhetorical structure across reviews, transcripts, social copy, and ad copy.
Earns it: Scales to corpora a human team can't read, and finds shifts before they show up in survey data.
Sentiment Databases + Cultural Tropes
Baseline valence
Measures: Baseline valence and trope-loading for words, phrases, symbols, and references against a curated cultural corpus.
Earns it: Catches the connotation a copywriter missed and the trope a strategist over-relied on.
Social Monitoring
Real-time signal
Measures: Share-of-voice, sentiment drift, audience composition, and reaction velocity across public social and review surfaces.
Earns it: The leading indicator. NPS and brand-tracker move weeks after social does.
Semantic → Behavior Prediction
Intent scoring
Measures: The relationship between the language on a page or in an ad and the downstream behavior of the people who read it — purchase, scroll, share, abandon.
Earns it: Predicts intent from copy with materially more signal than time-on-page or scroll depth.
Power-Law Attention Modeling
Distribution analysis
Measures: The distribution of attention across content — which frames, paragraphs, or seconds will carry the disproportionate share of the audience's focus.
Earns it: Attention is not uniform and not normal. Modeling it correctly is the difference between testing the average frame and testing the frame that matters.
Generative-Media Sentiment Feedback
Pre-screening
Measures: Predicted audience response to generative-media creative variants, evaluated through the other eight signals before a human ever sees them.
Earns it: Lets a producer screen fifty variants down to five defensible ones in a morning, instead of putting five into a focus group and hoping.
A finding is reported when at least two of the nine signals converge. When they disagree, the disagreement is the finding.
The convergence principle.
Every measurement signal has a known failure mode. Each one, alone, is a confident generator of plausible-sounding mistakes.
The honest move is to triangulate. When the brain prediction, the facial coding, and the eye-tracking attention curve all dip at the same second of a spot, that is a finding. When the NLP sentiment score on a landing page agrees with the semantic-to-behavior model and the social monitoring trendline, that is a forecast. When they disagree, we report the disagreement and tell you which signal is historically more reliable in that context. We do not hide it behind a composite score.
Neural response
over-indexes on arousal, under-indexes on valence
Facial coding
misreads neutral faces as engaged
Eye tracking
can't tell you why the gaze landed
NLP sentiment
scores irony as positive
Social monitoring
conflates volume with sentiment
Selective. Eight weeks. Written readout.
Walk the platform. Bring questions.
Four buyers, four reasons this page exists.
These are angled toward methodology defense, not operator pain.
Brand & Marketing Leaders
“My CFO will approve a measurement spend if I can show him it isn't EEG-cap snake oil. I need a methods page I can forward without flinching.”
Agency Strategists
“My clients ask if neuromarketing is real. I need a partner whose methodology I can hand to their procurement team without rewriting half of it first.”
Content & Media Producers
“I've sat through three neuromarketing pitches that promised to read minds. I want one that admits what the instruments can't do and shows me the convergence math.”
Research & Market-Intelligence Buyers
“I review vendor methodologies for a living. Show me the lineage, the failure modes, and the disagreement-handling protocol — or don't waste the meeting.”
When the signals disagreed.
Brand-anonymous. A different kind of proof from the measurement page — this one is about what happens when the stack contradicts itself.
Situation
A direct-to-consumer skincare brand was reviewing a launch spot that had cleared internal qualitative testing with strong “likeability” scores. The team felt the campaign was safe.
What we measured
NeuroLens neural-response prediction returned a high engagement curve across the full 30 seconds. Facial Expression Recognition, on the same viewer panel, returned a sustained low-grade disgust signal — small in amplitude but consistent. Eye tracking showed normal dwell. NLP sentiment on the script copy returned “positive.” Social monitoring on the brand's existing audience showed an above-baseline sensitivity to ingredient-related claims in the prior 60 days.
The Finding
We did not report a verdict. We reported a disagreement: the neural signal liked the spot, the facial signal did not, and the social baseline suggested the facial signal was the one to weight. The client paused, re-shot two scenes that exaggerated a specific ingredient visual, and re-tested. The disgust signal resolved. The spot shipped. We do not claim the alternative would have underperformed — we cannot run the counterfactual. We claim that the team made the decision with the disagreement on the table. That is the product.
How we work, and where it comes from.
Lineage.
Our methodology draws from peer-reviewed work in consumer neuroscience (the Plassmann / Ramsoy line), affective computing (the Picard / Rosalind-Picard MIT Media Lab lineage), and computational social science (the Lazer / Pentland / Salganik lineage). Citations available on request — we will send the actual PDFs, not a vendor-deck summary.
Request citationsConvergence over composite.
We do not collapse the nine signals into a single proprietary score. A composite score hides which signal disagreed. We report the per-signal reading and the convergence (or lack of it) explicitly.
Ethics and consent.
FER and biometric protocols run under participant consent flows reviewed against IRB-equivalent standards. No covert webcam use. No data resale. No model training on participant data without an explicit secondary consent.
Failure-mode disclosure.
Every readout includes a "what this instrument can't tell you" section. EEG-class prediction does not measure conscious preference. FER does not measure mood. Eye tracking does not measure intent. We say so in writing.
The Pilot Cohort.
Six teams. One measurement engagement each. Eight weeks. The full nine-signal stack applied to a decision you are actually about to make — a campaign, a positioning, a piece of content, a launch.
You receive a written readout your team can defend in front of a CMO, a CFO, or a procurement reviewer. The methodology section is included by default. The failure modes are disclosed. The disagreements between signals are reported, not buried.
We are selecting for fit. The right cohort member has a real decision on the calendar, a budget that makes measurement rational, and an internal team willing to act on what the readout says — including when the readout disagrees with their internal favorite.
Cohort intake closes when six are seated. Selection is rolling.
Apply for the pilot cohort
Fill out the form and we'll be in touch within 24 hours.
No spam, ever. We respond within 24 hours.
What you can expect from working with us.
Mutual NDA standard before any data moves in either direction.
Documented security posture. SECURITY.md and incident response policy available on request before engagement.
Methodology lineage rooted in peer-reviewed consumer neuroscience, affective computing, and computational social science.
West Virginia-based. Independent. Not owned by a holding company, ad network, or measurement vendor with a position to defend.
Founder-led engagements. You will talk to the person who built the stack, not an account manager three layers removed.
Failure modes disclosed in writing. Every readout names what the instruments cannot tell you, alongside what they can.
The discipline is real. Most of the practice isn't.
The pilot cohort seats six. Application takes about four minutes. We respond within two business days. The demo is thirty minutes and commits you to nothing.
Six seats. Rolling intake.
30 minutes. No commitment.
Applying is not a commitment. We will tell you if you are not a fit before you tell us.