A quantitative neuromarketing tool that A/B tests marketing copy using simulated human brain activity.
Instead of relying on basic NLP sentiment analysis or LLM "guesses," NeuroCopy runs text through Meta's TRIBE (Text and aRticulation Implicit Brain Evaluation) foundation model to predict actual fMRI BOLD responses across targeted regions of the human brain.
Standard neuromarketing averages the brain's response over the entire text. This is a flawed metric—a great hook combined with a terrible Call-to-Action (CTA) will yield a flat average, masking the drop-off in user attention.
NeuroCopy implements a Temporal Dynamics Layer to calculate an proprietary Alpha Score:
- Reward vs. Friction: Isolates activation in the Default Mode Network (Safety/Appeal) and subtracts activation in the Anterior Cingulate and Insula (Risk/Cognitive Load).
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CTA Momentum (The Dopamine Derivative): Calculates the mathematical derivative (
$dy/dx$ ) of engagement during the final 25% of the ad copy. - Positive momentum at the CTA heavily weights the final Alpha Score, identifying copy that successfully drives a user toward a conversion event.
- Jupyter Command Center: Batch-process dozens of ad variations entirely within a notebook interface.
- Temporal Heatmaps: Visualize the exact micro-second a user's brain spikes or flatlines while reading your pitch.
This pipeline requires ~16GB of System RAM and a dedicated NVIDIA GPU (T4 or better) for inference.
- Clone this repository.
- Install dependencies:
pip install -r requirements.txt - Open
neuro_optimizer.ipynbin a Kaggle or Google Colab environment with GPU acceleration enabled. - Input your ad variations and execute the pipeline.
- Sponsorship Pitches: Test B2B outreach messaging for friction and cognitive load before sending.
- Ad Creatives: A/B test hooks and CTAs without spending a dime on Meta/Google ad budgets.
- Landing Pages: Identify the exact sentence causing cognitive friction in your value proposition.