Selves (AI Personas)
Definition
Selves are audience representations built from public behavioral, cultural, linguistic, and contextual signals. Each Self reflects how a specific type of customer thinks, interprets messages, makes decisions, and reacts to content. A Self is not a persona, profile, or avatar. It is a structured representation of how that audience behaves in real communication. Selves allow teams to see how different audience groups respond to messages before launching anything.
Why It Matters
Different audiences understand messages differently, care about different benefits, interpret tone in different ways, have different objections, and expect different details. Selves reveal these differences.
Teams use Selves to: test messages, evaluate clarity, detect objections early, predict misunderstandings, strengthen product storytelling, and align cross-functional teams. Selves turn guessing how the audience will react into a structured, testable process.
What It Reflects
Each Self captures observable audience patterns, such as:
1. Motivations
What this audience is trying to achieve.
2. Clarity Needs
Which details they require to understand a product.
3. Tone Preferences
How formal, direct, playful, or detailed the content should be.
4. Category Expectations
What they expect a product in this category to say, contain, or prove.
5. Objections
What makes them hesitate or doubt.
6. Interpretation Patterns
How they read, misread, or misunderstand messaging.
7. Emotional Triggers
What helps them feel confident in a product or brand.
These are behavioral and interpretive patterns, not demographic assumptions.
Where It Is Used
Selves power multiple modules:
- Arena — Tests how each Self understands a message, headline, product description, PDP, script, or value prop.
- Bevel — Organizes audience structure and identifies audience segments worth testing.
- Edge — Aligns content clarity with audience expectations to improve AI Visibility.
- Deal — Uses Self patterns to respond more accurately in WhatsApp conversations.
Selves make the message → test → deploy cycle audience-driven.
Real-World Examples
- A message that works for "Value Seekers" may confuse "Aspirational Shoppers."
- A headline that feels clear to "Tech-savvy Users" may overwhelm "Everyday Consumers."
- A PDP written for "Experts" may underperform for "First-time Buyers."
- Selves reveal these differences before campaigns, PDPs, or landing pages go live.
What Selves Are Not
Selves are not: demographic personas, psychographic profiles, user accounts, behavioral predictions of individuals, lookalike audiences, or identity data. Selves are communication and interpretation models of audience groups based on public, non-personal signals.
How Teams Use Selves
Teams improve outcomes by using Selves to: validate clarity, test narrative variations, compare which benefits matter most, uncover confusion or hesitation points, refine tone and structure, create more effective PDPs, ads, and landing pages, and guide creative development. Selves act as a continuous feedback loop between what teams say and how audiences understand it.
