Persado: Scaling Emotional Resonance through AI-Driven Language
At Persado, the work was to move language from subjective opinion to measurable system. By treating every word as data and every emotion as a variable, we aligned brand empathy with performance so that campaigns felt more human precisely because they were more scientific.
Reduction in CAC through AI-optimized, multi-channel campaigns that matched language to segment-specific motivations.
Year-over-year growth in inbound lead volume by tuning demand generation and paid media to emotional and semantic signals.
Increase in organic search visibility and high-intent keyword rankings through language-informed SEO and content strategy.
From subjective art to objective science
Copywriting has long been treated as a purely creative discipline. At Persado, the work reframed language as a measurable system—one where emotion, tone, and structure could be tagged, tested, and tuned without losing humanity.
The goal was to make every line of copy accountable to outcomes while still honoring brand voice, empathy, and the lived reality of the people on the other end of the message.
Principle
Language became the ultimate data point. If a message drove uplift, we learned why. If it violated brand safety, we removed it from the model entirely—even if the numbers looked superficially strong.
The ICE framework & AI velocity
ICE Prioritization
Structured experimentation using ICE (Impact, Confidence, Ease) to decide which hypotheses to test first and where AI-optimized language would likely drive the greatest uplift.
Emotion & Tone Taxonomy
Every variant was labeled against a strict taxonomy—excitement, urgency, curiosity, security, and more—so emotional patterns could be tracked across campaigns and channels.
Signal, Not Noise
We only elevated patterns to “signals” once they reproduced uplift across contexts with stable baselines, rejecting noisy data and tactics that conflicted with brand values.
The ultra-high-net-worth challenge
A financial institution wanted to understand which emotional triggers resonated with ultra-high-net-worth individuals, but the segment was too small for traditional A/B testing to reach statistical significance.
Instead of guessing, the solution borrowed the machine learning concept of transfer learning and applied it to language.
This allowed the institution to bring highly refined, validated emotional concepts to their most valuable clients without burning limited attention on weak or unproven variants.
Loyalty as engineered relevance
By mapping language patterns to cohort identity, status, and emotional architecture, Persado moved beyond extracting value from customers. The work created messaging systems that made people feel recognized, not targeted.
The result was a compounding advantage: as the system learned, relevance improved, and that improved relevance deepened loyalty in ways competitors struggled to replicate.
Leadership Lens
The role showed that AI in marketing works best when it is constrained by ethics, brand guidelines, and a clear definition of what “good” looks like for both the business and the customer.
Persado Platform
Core engine for language generation, emotional labeling, and uplift measurement across channels.6Sense, Pathfactory, Drift
Account intelligence, content experiences, and conversational entry-points informed by emotional and behavioral data.Salesforce, Pardot, Marketo
Lifecycle orchestration, scoring, and reporting on how AI-optimized messages performed over time.GA4, Tableau, Amplitude, Segment
End-to-end visibility into user behavior, cohort performance, and the downstream impact of language decisions.Scaling the feeling of being understood
At Persado, the work proved that loyalty is built on relevance, and relevance can be engineered. When language is treated as a system—bounded by ethics, powered by AI, and tuned to human emotion—the result is growth that feels less like extraction and more like relationship-building.