audience-intelligence
starsforks
How to install audience-intelligence?
indranilbanerjee/digital-marketing-pro/audience-intelligence
$npx -y skills add indranilbanerjee/digital-marketing-pro --skill audience-intelligenceResearch target audiences. Use when: buyer personas, segmentation, Jobs-to-Be-Done, psychographic profiling, audience deep-dive.
SKILL.md
| 1 | # Audience Intelligence |
| 2 | |
| 3 | ## When to Use This Skill |
| 4 | |
| 5 | Activate this module when the user's request involves any of the following: |
| 6 | |
| 7 | - **Buyer Persona Creation**: Building detailed profiles of ideal customers for marketing and product decisions |
| 8 | - **Audience Research**: Understanding who a brand's customers or prospects are at a demographic, psychographic, and behavioral level |
| 9 | - **Segmentation Strategy**: Dividing an audience into meaningful groups for targeted marketing |
| 10 | - **Jobs-to-Be-Done (JTBD) Analysis**: Identifying the functional, social, and emotional jobs customers hire a product to do |
| 11 | - **Psychographic Profiling**: Understanding audience values, attitudes, interests, lifestyles, and motivations |
| 12 | - **Anti-Persona Definition**: Defining who is NOT the target customer to prevent wasted spend |
| 13 | - **Audience Sizing & TAM Estimation**: Estimating the size of addressable audience segments |
| 14 | |
| 15 | **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" |
| 16 | |
| 17 | ## Brand Context (Auto-Applied) |
| 18 | |
| 19 | Before producing any marketing output from this module: |
| 20 | |
| 21 | 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. |
| 22 | 2. **If you need the full profile**, read: `~/.claude-marketing/brands/{slug}/profile.json` |
| 23 | 3. **Apply brand voice** — Formality, energy, humor, authority levels must shape all content tone and word choices |
| 24 | 4. **Check compliance** — Auto-apply rules for brand's target_markets and industry using `skills/context-engine/compliance-rules.md` |
| 25 | 5. **Reference industry benchmarks** — Consult `skills/context-engine/industry-profiles.md` for the brand's industry |
| 26 | 6. **Use platform specs** — Reference `skills/context-engine/platform-specs.md` for character limits and format requirements |
| 27 | 7. **Check campaign history** — Run `python "${CLAUDE_PLUGIN_ROOT}/scripts/campaign-tracker.py" --brand {slug} --action list-campaigns` before planning new work |
| 28 | 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." |
| 29 | 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. |
| 30 | |
| 31 | Do not ask the user for information that already exists in their brand profile. |
| 32 | |
| 33 | ## Required Context |
| 34 | |
| 35 | Before executing audience intelligence work, gather: |
| 36 | |
| 37 | 1. **Business Description**: What does the company sell, to whom, and what problem does it solve? |
| 38 | 2. **Existing Customer Data**: Any analytics, CRM data, survey results, or customer interviews available |
| 39 | 3. **Product/Service Details**: Features, pricing, positioning, and key differentiators |
| 40 | 4. **Current Audience Assumptions**: Who does the team think their customers are today? |
| 41 | 5. **Market Context**: Industry, competitive landscape, market maturity |
| 42 | 6. **Geographic Scope**: Local, regional, national, or global audience |
| 43 | 7. **Business Model**: B2B, B2C, B2B2C, D2C — this fundamentally shapes persona structure |
| 44 | 8. **Sales Process**: Self-serve, sales-assisted, enterprise sales — determines decision-maker mapping |
| 45 | |
| 46 | 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. |
| 47 | |
| 48 | ## Capabilities |
| 49 | |
| 50 | - **Multi-Dimensional Persona Building**: Personas built across six dimensions: |
| 51 | - **Demographic**: Age, gender, location, income, education, job title, company size |
| 52 | - **Psychographic**: Values, attitudes, lifestyle, personality traits, motivations |
| 53 | - **Behavioral**: Purchase patterns, channel preferences, content consumption, decision-making style |
| 54 | - **Need-State**: Current pain points, unmet needs, desired outcomes, urgency level |
| 55 | - **Information**: Where they research, who they trust, content format preferences, information journey |
| 56 | - **Decision**: Decision criteria, objections, influencers, timeline, risk tolerance |
| 57 | - **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 innovat |
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