/audience-intelligence

name: audience-intelligence
description: "Audience research module — builds six-dimension buyer personas (demographic, psychographic, behavioral, need-state, information, decision), Jobs-to-Be-Done maps, RFM/behavioral/lifecycle segmentation models, anti-personas with exclusion criteria, B2B buying-committee maps, and lookalike seed specs. Triggers on \"/digital-marketing-pro:audience-intelligence\", \"who are our customers\", \"build buyer personas\", \"segment our audience\", \"run a JTBD analysis\". Reads the brand profile, industry benchmarks, and campaign history, and works from CRM/survey/analytics data when supplied — or labels hypothesis personas explicitly when data is thin. For a single quick persona document, /digital-marketing-pro:audience-profile is the lighter sibling."

Audience Intelligence

When to Use This Skill

Activate this module when the user's request involves any of the following:

• **Buyer Persona Creation**: Building detailed profiles of ideal customers for marketing and product decisions
• **Audience Research**: Understanding who a brand's customers or prospects are at a demographic, psychographic, and behavioral level
• **Segmentation Strategy**: Dividing an audience into meaningful groups for targeted marketing
• **Jobs-to-Be-Done (JTBD) Analysis**: Identifying the functional, social, and emotional jobs customers hire a product to do
• **Psychographic Profiling**: Understanding audience values, attitudes, interests, lifestyles, and motivations
• **Anti-Persona Definition**: Defining who is NOT the target customer to prevent wasted spend
• **Audience Sizing & TAM Estimation**: Estimating the size of addressable audience segments

**Trigger phrases**: "buyer persona," "target audience," "who are our customers," "customer profile," "segmentation," "audience segments," "Jobs-to-Be-Done," "JTBD," "psychographic," "ideal customer profile," "ICP," "anti-persona," "lookalike audience," "audience research," "buying committee," "customer avatar"

Brand Context (Auto-Applied)

Before producing any marketing output from this module:

1. **Check session context** — The active brand summary was output at session start. Use the brand name, industry, voice settings, channels, goals, compliance, and competitors shown there. 2. **If you need the full profile**, read: `~/.claude-marketing/brands/{slug}/profile.json` 3. **Apply brand voice** — Formality, energy, humor, authority levels must shape all content tone and word choices 4. **Check compliance** — Auto-apply rules for brand's target_markets and industry using `skills/context-engine/compliance-rules.md` 5. **Reference industry benchmarks** — Consult `skills/context-engine/industry-profiles.md` for the brand's industry 6. **Use platform specs** — Reference `skills/context-engine/platform-specs.md` for character limits and format requirements 7. **Check campaign history** — Run `python "${CLAUDE_PLUGIN_ROOT}/scripts/campaign-tracker.py" --brand {slug} --action list-campaigns` before planning new work 8. **If no brand exists**, say: "No brand profile found. Use /digital-marketing-pro:brand-setup to create one, or I can proceed with general best practices." 9. **Check brand guidelines** — If `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` exists, load and enforce: `restrictions.md` for banned words, restricted claims, and mandatory disclaimers; `channel-styles.md` for channel-specific tone overrides (may differ from base voice); `messaging.md` for approved key messages, taglines, and positioning language; `voice-and-tone.md` for detailed voice rules beyond the 4 numeric scores. If producing content for a specific channel, channel style rules take precedence over base voice settings.

Do not ask the user for information that already exists in their brand profile.

Required Context

Before executing audience intelligence work, gather:

1. **Business Description**: What does the company sell, to whom, and what problem does it solve? 2. **Existing Customer Data**: Any analytics, CRM data, survey results, or customer interviews available 3. **Product/Service Details**: Features, pricing, positioning, and key differentiators 4. **Current Audience Assumptions**: Who does the team think their customers are today? 5. **Market Context**: Industry, competitive landscape, market maturity 6. **Geographic Scope**: Local, regional, national, or global audience 7. **Business Model**: B2B, B2C, B2B2C, D2C — this fundamentally shapes persona structure 8. **Sales Process**: Self-serve, sales-assisted, enterprise sales — determines decision-maker mapping

If the user has minimal data, build hypothesis-driven personas based on business model, product, and market analysis. Label these clearly as hypotheses to be validated.

Capabilities

• **Multi-Dimensional Persona Building**: Personas built across six dimensions:
• **Demographic**: Age, gender, location, income, education, job title, company size
• **Psychographic**: Values, attitudes, lifestyle, personality traits, motivations
• **Behavioral**: Purchase patterns, channel preferences, content consumption, decision-making style
• **Need-State**: Current pain points, unmet needs, desired outcomes, urgency level
• **Information**: Where they research, who they trust, content format preferences, information journey
• **Decision**: Decision criteria, objections, influencers, timeline, risk tolerance
• **JTBD Framework**: Mapping functional jobs (what they need done), social jobs (how they want to be perceived), and emotional jobs (how they want to feel) with outcome-driven innovation metrics
• **RFM Segmentation**: Recency, Frequency, Monetary value analysis for customer base segmentation
• **Behavioral Segmentation**: Grouping by usage patterns, engagement levels, and purchase behavior
• **Value-Based Segmentation**: Grouping by customer lifetime value and profitability potential
• **Lifecycle Segmentation**: Grouping by customer lifecycle stage (pr