--- 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 (prospect, new, active, at-risk, churned, win-back) - **Lookalike Audience Guidance**: Defining seed audience characteristics for platform-based lookalike targeting - **Anti-Persona Definition**: Explicitly defining who should be excluded from targeting to prevent wasted spend and misaligned messaging - **Buying Committee Mapping**: For B2B, mapping all roles involved in purchase decisions with their individual motivations and objections

## Process

**Primary Workflow: Persona Development & Segmentation**

1. **Discovery & Data Collection** - Gather all available customer data (analytics, CRM exports, survey results, interview transcripts) - Review existing marketing materials, landing pages, and ads for implicit audience assumptions - Analyze competitor targeting (who are they going after? what messaging do they use?) - If no data exists, conduct a market analysis to build hypothesis personas - Document the data quality level: data-rich, data-limited, or hypothesis-only

2. **JTBD Analysis** - Identify the core job the customer is hiring the product to do - Map functional jobs: What task needs to be accomplished? - Map social jobs: How does the customer want to be perceived by others? - Map emotional jobs: How does the customer want to feel? - Identify the "struggling moment" — what triggers the search for a solution? - Document competing solutions (including non-consumption and manual workarounds) - Define desired outcomes and how customers measure success

3. **Persona Construction** - Build 3-5 primary personas (avoid persona proliferation) - For each persona, complete all six dimensions: - **Demographic profile**: Concrete characteristics with ranges, not single points - **Psychographic profile**: Values, beliefs, lifestyle factors that influence purchase decisions - **Behavioral profile**: How they buy, where they spend time, what content they consume - **Need-state profile**: Specific pain points, urgency drivers, and desired outcomes - **Information profile**: Research behavior, trusted sources, content preferences - **Decision profile**: Criteria, objections, influencers, and timeline - Give each persona a memorable name and narrative (but avoid stereotyping) - Assign estimated segment size and revenue potential - Prioritize personas by business impact

4. **Anti-Persona Development** - Define 1-3 anti-personas: people who may seem like targets but are poor fits - Common anti-persona types: price-sensitive bargain hunters (for premium brands), feature-seekers who will never buy (tire kickers), wrong company size or industry - Document specific signals that identify anti-personas in your data - Create exclusion criteria for ad targeting and lead qualification

5. **Segmentation Strategy** - Select the segmentation approach based on available data and business needs: - **RFM**: When transaction data is available — score by recency, frequency, monetary value - **Behavioral**: When usage/engagement data exists — group by behavior patterns - **Value-based**: When LTV data is available — prioritize high-value segments - **Lifecycle**: When customer journey stage data exists — customize by stage - **Needs-based**: When qualitative research is available — group by pain point - Define segment boundaries and naming conventions - Map segments to personas (segments are data-driven groups; personas are the human stories within them) - Assign channel and messaging strategies per segment

6. **Activation Planning** - For each persona/segment, define: - Priority channels for reaching them - Messaging themes and value propositions that resonate - Content types and formats they prefer - Lookalike audience seed criteria for paid platforms - Lead scoring rules based on persona fit - Create a persona-to-campaign mapping guide - Build a validation plan to test persona hypotheses with real campaign data

## Reference Files

- `persona-builder.md` — Six-dimension persona template, persona interview guide, data-to-persona methodology, and persona validation framework - `jtbd-framework.md` — Jobs-to-Be-Done analysis methodology, job mapping canvas, outcome-driven innovation scoring, and competing solutions analysis - `segmentation.md` — RFM scoring model, behavioral segmentation framework, lifecycle segmentation definitions, and segment-to-action mapping - `psychographic-profiling.md` — Values and attitudes framework, lifestyle analysis, motivation mapping, and psychographic data collection methods - `customer-research-methods.md` — Quantitative and qualitative research methods: survey design, interview techniques, voice-of-customer programs, and synthesis methods with budget guidance

## Output Formats

| Deliverable | Format | Description | |---|---|---| | Buyer Persona Document | Document (per persona) | Complete six-dimension persona with narrative, data points, and activation guidance | | Persona Summary Card | One-page visual | Quick-reference persona card for team alignment | | JTBD Analysis | Document | Job map, struggling moments, desired outcomes, and competing solutions | | Segmentation Model | Spreadsheet + document | Segment definitions, criteria, sizes, and strategy per segment | | Anti-Persona Profiles | Document | Who to exclude, why, and identification signals | | Buying Committee Map | Visual diagram + document | B2B decision-maker map with roles, motivations, and influence paths | | Audience Activation Guide | Document | Channel, messaging, and content recommendations per persona/segment | | Lookalike Audience Spec | Document | Seed audience criteria and platform-specific setup instructions |

## Edge Cases

### B2B Buying Committees (Multiple Personas per Deal) - **Situation**: Enterprise B2B purchases involve 6-10 decision-makers with different roles, motivations, and objections - **Approach**: Build individual personas for

--- 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 (prospect, new, active, at-risk, churned, win-back) - **Lookalike Audience Guidance**: Defining seed audience characteristics for platform-based lookalike targeting - **Anti-Persona Definition**: Explicitly defining who should be excluded from targeting to prevent wasted spend and misaligned messaging - **Buying Committee Mapping**: For B2B, mapping all roles involved in purchase decisions with their individual motivations and objections

## Process

**Primary Workflow: Persona Development & Segmentation**

1. **Discovery & Data Collection** - Gather all available customer data (analytics, CRM exports, survey results, interview transcripts) - Review existing marketing materials, landing pages, and ads for implicit audience assumptions - Analyze competitor targeting (who are they going after? what messaging do they use?) - If no data exists, conduct a market analysis to build hypothesis personas - Document the data quality level: data-rich, data-limited, or hypothesis-only

2. **JTBD Analysis** - Identify the core job the customer is hiring the product to do - Map functional jobs: What task needs to be accomplished? - Map social jobs: How does the customer want to be perceived by others? - Map emotional jobs: How does the customer want to feel? - Identify the "struggling moment" — what triggers the search for a solution? - Document competing solutions (including non-consumption and manual workarounds) - Define desired outcomes and how customers measure success

3. **Persona Construction** - Build 3-5 primary personas (avoid persona proliferation) - For each persona, complete all six dimensions: - **Demographic profile**: Concrete characteristics with ranges, not single points - **Psychographic profile**: Values, beliefs, lifestyle factors that influence purchase decisions - **Behavioral profile**: How they buy, where they spend time, what content they consume - **Need-state profile**: Specific pain points, urgency drivers, and desired outcomes - **Information profile**: Research behavior, trusted sources, content preferences - **Decision profile**: Criteria, objections, influencers, and timeline - Give each persona a memorable name and narrative (but avoid stereotyping) - Assign estimated segment size and revenue potential - Prioritize personas by business impact

4. **Anti-Persona Development** - Define 1-3 anti-personas: people who may seem like targets but are poor fits - Common anti-persona types: price-sensitive bargain hunters (for premium brands), feature-seekers who will never buy (tire kickers), wrong company size or industry - Document specific signals that identify anti-personas in your data - Create exclusion criteria for ad targeting and lead qualification

5. **Segmentation Strategy** - Select the segmentation approach based on available data and business needs: - **RFM**: When transaction data is available — score by recency, frequency, monetary value - **Behavioral**: When usage/engagement data exists — group by behavior patterns - **Value-based**: When LTV data is available — prioritize high-value segments - **Lifecycle**: When customer journey stage data exists — customize by stage - **Needs-based**: When qualitative research is available — group by pain point - Define segment boundaries and naming conventions - Map segments to personas (segments are data-driven groups; personas are the human stories within them) - Assign channel and messaging strategies per segment

6. **Activation Planning** - For each persona/segment, define: - Priority channels for reaching them - Messaging themes and value propositions that resonate - Content types and formats they prefer - Lookalike audience seed criteria for paid platforms - Lead scoring rules based on persona fit - Create a persona-to-campaign mapping guide - Build a validation plan to test persona hypotheses with real campaign data

## Reference Files

- `persona-builder.md` — Six-dimension persona template, persona interview guide, data-to-persona methodology, and persona validation framework - `jtbd-framework.md` — Jobs-to-Be-Done analysis methodology, job mapping canvas, outcome-driven innovation scoring, and competing solutions analysis - `segmentation.md` — RFM scoring model, behavioral segmentation framework, lifecycle segmentation definitions, and segment-to-action mapping - `psychographic-profiling.md` — Values and attitudes framework, lifestyle analysis, motivation mapping, and psychographic data collection methods - `customer-research-methods.md` — Quantitative and qualitative research methods: survey design, interview techniques, voice-of-customer programs, and synthesis methods with budget guidance

## Output Formats

| Deliverable | Format | Description | |---|---|---| | Buyer Persona Document | Document (per persona) | Complete six-dimension persona with narrative, data points, and activation guidance | | Persona Summary Card | One-page visual | Quick-reference persona card for team alignment | | JTBD Analysis | Document | Job map, struggling moments, desired outcomes, and competing solutions | | Segmentation Model | Spreadsheet + document | Segment definitions, criteria, sizes, and strategy per segment | | Anti-Persona Profiles | Document | Who to exclude, why, and identification signals | | Buying Committee Map | Visual diagram + document | B2B decision-maker map with roles, motivations, and influence paths | | Audience Activation Guide | Document | Channel, messaging, and content recommendations per persona/segment | | Lookalike Audience Spec | Document | Seed audience criteria and platform-specific setup instructions |

## Edge Cases

### B2B Buying Committees (Multiple Personas per Deal) - **Situation**: Enterprise B2B purchases involve 6-10 decision-makers with different roles, motivations, and objections - **Approach**: Build individual personas for

--- 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 (prospect, new, active, at-risk, churned, win-back) - **Lookalike Audience Guidance**: Defining seed audience characteristics for platform-based lookalike targeting - **Anti-Persona Definition**: Explicitly defining who should be excluded from targeting to prevent wasted spend and misaligned messaging - **Buying Committee Mapping**: For B2B, mapping all roles involved in purchase decisions with their individual motivations and objections

## Process

**Primary Workflow: Persona Development & Segmentation**

1. **Discovery & Data Collection** - Gather all available customer data (analytics, CRM exports, survey results, interview transcripts) - Review existing marketing materials, landing pages, and ads for implicit audience assumptions - Analyze competitor targeting (who are they going after? what messaging do they use?) - If no data exists, conduct a market analysis to build hypothesis personas - Document the data quality level: data-rich, data-limited, or hypothesis-only

2. **JTBD Analysis** - Identify the core job the customer is hiring the product to do - Map functional jobs: What task needs to be accomplished? - Map social jobs: How does the customer want to be perceived by others? - Map emotional jobs: How does the customer want to feel? - Identify the "struggling moment" — what triggers the search for a solution? - Document competing solutions (including non-consumption and manual workarounds) - Define desired outcomes and how customers measure success

3. **Persona Construction** - Build 3-5 primary personas (avoid persona proliferation) - For each persona, complete all six dimensions: - **Demographic profile**: Concrete characteristics with ranges, not single points - **Psychographic profile**: Values, beliefs, lifestyle factors that influence purchase decisions - **Behavioral profile**: How they buy, where they spend time, what content they consume - **Need-state profile**: Specific pain points, urgency drivers, and desired outcomes - **Information profile**: Research behavior, trusted sources, content preferences - **Decision profile**: Criteria, objections, influencers, and timeline - Give each persona a memorable name and narrative (but avoid stereotyping) - Assign estimated segment size and revenue potential - Prioritize personas by business impact

4. **Anti-Persona Development** - Define 1-3 anti-personas: people who may seem like targets but are poor fits - Common anti-persona types: price-sensitive bargain hunters (for premium brands), feature-seekers who will never buy (tire kickers), wrong company size or industry - Document specific signals that identify anti-personas in your data - Create exclusion criteria for ad targeting and lead qualification

5. **Segmentation Strategy** - Select the segmentation approach based on available data and business needs: - **RFM**: When transaction data is available — score by recency, frequency, monetary value - **Behavioral**: When usage/engagement data exists — group by behavior patterns - **Value-based**: When LTV data is available — prioritize high-value segments - **Lifecycle**: When customer journey stage data exists — customize by stage - **Needs-based**: When qualitative research is available — group by pain point - Define segment boundaries and naming conventions - Map segments to personas (segments are data-driven groups; personas are the human stories within them) - Assign channel and messaging strategies per segment

6. **Activation Planning** - For each persona/segment, define: - Priority channels for reaching them - Messaging themes and value propositions that resonate - Content types and formats they prefer - Lookalike audience seed criteria for paid platforms - Lead scoring rules based on persona fit - Create a persona-to-campaign mapping guide - Build a validation plan to test persona hypotheses with real campaign data

## Reference Files

- `persona-builder.md` — Six-dimension persona template, persona interview guide, data-to-persona methodology, and persona validation framework - `jtbd-framework.md` — Jobs-to-Be-Done analysis methodology, job mapping canvas, outcome-driven innovation scoring, and competing solutions analysis - `segmentation.md` — RFM scoring model, behavioral segmentation framework, lifecycle segmentation definitions, and segment-to-action mapping - `psychographic-profiling.md` — Values and attitudes framework, lifestyle analysis, motivation mapping, and psychographic data collection methods - `customer-research-methods.md` — Quantitative and qualitative research methods: survey design, interview techniques, voice-of-customer programs, and synthesis methods with budget guidance

## Output Formats

| Deliverable | Format | Description | |---|---|---| | Buyer Persona Document | Document (per persona) | Complete six-dimension persona with narrative, data points, and activation guidance | | Persona Summary Card | One-page visual | Quick-reference persona card for team alignment | | JTBD Analysis | Document | Job map, struggling moments, desired outcomes, and competing solutions | | Segmentation Model | Spreadsheet + document | Segment definitions, criteria, sizes, and strategy per segment | | Anti-Persona Profiles | Document | Who to exclude, why, and identification signals | | Buying Committee Map | Visual diagram + document | B2B decision-maker map with roles, motivations, and influence paths | | Audience Activation Guide | Document | Channel, messaging, and content recommendations per persona/segment | | Lookalike Audience Spec | Document | Seed audience criteria and platform-specific setup instructions |

## Edge Cases

### B2B Buying Committees (Multiple Personas per Deal) - **Situation**: Enterprise B2B purchases involve 6-10 decision-makers with different roles, motivations, and objections - **Approach**: Build individual personas for

--- 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 (prospect, new, active, at-risk, churned, win-back) - **Lookalike Audience Guidance**: Defining seed audience characteristics for platform-based lookalike targeting - **Anti-Persona Definition**: Explicitly defining who should be excluded from targeting to prevent wasted spend and misaligned messaging - **Buying Committee Mapping**: For B2B, mapping all roles involved in purchase decisions with their individual motivations and objections

## Process

**Primary Workflow: Persona Development & Segmentation**

1. **Discovery & Data Collection** - Gather all available customer data (analytics, CRM exports, survey results, interview transcripts) - Review existing marketing materials, landing pages, and ads for implicit audience assumptions - Analyze competitor targeting (who are they going after? what messaging do they use?) - If no data exists, conduct a market analysis to build hypothesis personas - Document the data quality level: data-rich, data-limited, or hypothesis-only

2. **JTBD Analysis** - Identify the core job the customer is hiring the product to do - Map functional jobs: What task needs to be accomplished? - Map social jobs: How does the customer want to be perceived by others? - Map emotional jobs: How does the customer want to feel? - Identify the "struggling moment" — what triggers the search for a solution? - Document competing solutions (including non-consumption and manual workarounds) - Define desired outcomes and how customers measure success

3. **Persona Construction** - Build 3-5 primary personas (avoid persona proliferation) - For each persona, complete all six dimensions: - **Demographic profile**: Concrete characteristics with ranges, not single points - **Psychographic profile**: Values, beliefs, lifestyle factors that influence purchase decisions - **Behavioral profile**: How they buy, where they spend time, what content they consume - **Need-state profile**: Specific pain points, urgency drivers, and desired outcomes - **Information profile**: Research behavior, trusted sources, content preferences - **Decision profile**: Criteria, objections, influencers, and timeline - Give each persona a memorable name and narrative (but avoid stereotyping) - Assign estimated segment size and revenue potential - Prioritize personas by business impact

4. **Anti-Persona Development** - Define 1-3 anti-personas: people who may seem like targets but are poor fits - Common anti-persona types: price-sensitive bargain hunters (for premium brands), feature-seekers who will never buy (tire kickers), wrong company size or industry - Document specific signals that identify anti-personas in your data - Create exclusion criteria for ad targeting and lead qualification

5. **Segmentation Strategy** - Select the segmentation approach based on available data and business needs: - **RFM**: When transaction data is available — score by recency, frequency, monetary value - **Behavioral**: When usage/engagement data exists — group by behavior patterns - **Value-based**: When LTV data is available — prioritize high-value segments - **Lifecycle**: When customer journey stage data exists — customize by stage - **Needs-based**: When qualitative research is available — group by pain point - Define segment boundaries and naming conventions - Map segments to personas (segments are data-driven groups; personas are the human stories within them) - Assign channel and messaging strategies per segment

6. **Activation Planning** - For each persona/segment, define: - Priority channels for reaching them - Messaging themes and value propositions that resonate - Content types and formats they prefer - Lookalike audience seed criteria for paid platforms - Lead scoring rules based on persona fit - Create a persona-to-campaign mapping guide - Build a validation plan to test persona hypotheses with real campaign data

## Reference Files

- `persona-builder.md` — Six-dimension persona template, persona interview guide, data-to-persona methodology, and persona validation framework - `jtbd-framework.md` — Jobs-to-Be-Done analysis methodology, job mapping canvas, outcome-driven innovation scoring, and competing solutions analysis - `segmentation.md` — RFM scoring model, behavioral segmentation framework, lifecycle segmentation definitions, and segment-to-action mapping - `psychographic-profiling.md` — Values and attitudes framework, lifestyle analysis, motivation mapping, and psychographic data collection methods - `customer-research-methods.md` — Quantitative and qualitative research methods: survey design, interview techniques, voice-of-customer programs, and synthesis methods with budget guidance

## Output Formats

| Deliverable | Format | Description | |---|---|---| | Buyer Persona Document | Document (per persona) | Complete six-dimension persona with narrative, data points, and activation guidance | | Persona Summary Card | One-page visual | Quick-reference persona card for team alignment | | JTBD Analysis | Document | Job map, struggling moments, desired outcomes, and competing solutions | | Segmentation Model | Spreadsheet + document | Segment definitions, criteria, sizes, and strategy per segment | | Anti-Persona Profiles | Document | Who to exclude, why, and identification signals | | Buying Committee Map | Visual diagram + document | B2B decision-maker map with roles, motivations, and influence paths | | Audience Activation Guide | Document | Channel, messaging, and content recommendations per persona/segment | | Lookalike Audience Spec | Document | Seed audience criteria and platform-specific setup instructions |

## Edge Cases

### B2B Buying Committees (Multiple Personas per Deal) - **Situation**: Enterprise B2B purchases involve 6-10 decision-makers with different roles, motivations, and objections - **Approach**: Build individual personas for