Attention Isn’t Enough—The Future of Marketing is Relevance
Impressions and click-through rates tell you what happened, not why a campaign lands in one context and dies in another. Relevance, not raw attention, is what actually predicts action and lasting attachment. EARO proposes an open-source way to measure it across four dimensions—Exposure, Attention, Relevance, Outcome—spanning 22 metrics built for an AI-driven era.
Here’s the truth: 𝗔𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻 alone isn’t predictive—𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 is.
We’ve all seen it:
- An ad goes viral but fails to drive sales.
- A campaign lifts brand awareness in one context but falls flat in another.
- An emotionally resonant creative triggers action in one segment but apathy in another.
Why? Because the game has changed. It’s no longer about getting attention—it’s about earning relevance.
The Shift: From Static to Dynamic
Relevance isn’t just about who sees your ad (demographics) or what they do (behaviors). It’s about:
- Contextual fit: Is your message aligned with the user’s moment?
- Emotional drivers: Does it tap into what actually matters to them?
- Cognitive scaffolding: Does it adapt to how they make meaning?
Traditional metrics (impressions, CTRs) can’t answer these questions. They tell you what happened, not why.
Introducing EARO: A Framework for the Age of AI
I’m building EARO (pronounced “Hero”) — an open-source framework to measure marketing effectiveness holistically.
- Exposure: Did the right people encounter it?
- Attention: Did they actually notice?
- Relevance: Did it resonate in context?
- Outcome: Did it drive action and long-term attachment?
EARO moves beyond static KPIs to model the dynamic interplay of attention, emotion, and cultural signals—critical in the era of Artificial General Intelligence (AGI).
Hierarchy of Metrics in the EARO Framework
The EARO framework consists of four main components—Exposure (E), Attention (A), Relevance (R), and Outcome (O)—each with multiple dimensions and associated metrics. Below is the hierarchical structure. It’s powered by 22 metrics across dimensions:
| Dimension | Metric | Derived score |
|---|---|---|
| Exposure (E) | Reach (RCH) | — |
| Frequency (FRQ) | — | |
| Contextual Exposure Fit (CEF) | Contextual Exposure Score (CES) | |
| Attention (A) | Active Time in View (ATV) | — |
| Attention Score (AS) | — | |
| Engagement Rate (ER) | — | |
| Sustained Attention (SA) | Dwell Time Ratio (DTR) | |
| Emotional Engagement (EE) | Sentiment Engagement Score (SES) | |
| Contextual Attention Fit (CAF) | Platform Attention Index (PAI) | |
| Relevance (R) | Relevance Score (RS) | — |
| Click-Through Rate (CTR) | — | |
| Personalization Index (PI) | — | |
| Cultural Resonance (CR) | Cultural Alignment Score (CAS) | |
| Emotional Relevance (ER) | Emotional Connection Index (ECI) | |
| Dynamic Relevance (DR) | Trend Responsiveness Score (TRS) | |
| Emotional Driver Analysis (EDA) | Emotional Driver Score (EDS) | |
| Outcome (O) | Conversion Rate (CR) | — |
| Return on Ad Spend (ROAS) | — | |
| Brand Lift (BL) | — | |
| Long-Term Value (LTV) | Customer Lifetime Value Growth (CLVG) | |
| Behavioral Impact (BI) | Advocacy Rate (AR) | |
| Attribution Accuracy (AA) | Multi-Touch Attribution Score (MTAS) | |
| Brand Attachment (BA) | Brand Attachment Score (BAS) |
The Big Questions
As AGI evolves, we’re forced to rethink fundamentals:
- What if ads weren’t fixed messages but affordances for meaning-making?
- What if media planning wasn’t just about reach but scaffolding relevance in real time?
- What if AI wasn’t just a prediction tool but a cognitive partner for creative optimization?
The future belongs to marketers who measure—and optimize for—relevance realization.
Let’s discuss: How are you bridging the gap between attention and relevance?
𝗖𝗧𝗔: If you like to peer review a draft of the “Hero” whitepaper, msg below