audience-intel

Solid

Synthesize what we're learning about our audience

AI & Automation 448 stars 122 forks Updated today NOASSERTION

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Quality Score: 83/100

Stars 20%
88
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
90
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

## Purpose Aggregate audience insights from all sources to refine persona understanding and inform marketing strategy. ## Usage - `/audience-intel` - Full audience analysis - `/audience-intel [persona]` - Focus on specific persona/segment --- ## Steps 1. **Gather audience data:** - Search 00-Inbox/Meetings/ for customer conversations - Check People/ for customer person pages - Reference `/customer-intel` output if available 2. **Identify patterns:** - Common roles/titles - Shared pain points - Similar goals/motivations - Buying triggers - Decision criteria 3. **Segment insights:** - Group by persona/role - Note differences between segments - Identify underserved audiences 4. **Extract messaging insights:** - What language do they use? - What problems do they describe? - What outcomes do they want? - What objections do they raise? 5. **Generate intelligence report with:** - Persona patterns - Pain points by segment - Motivations and goals - Messaging implications - Content recommendations --- ## Output Format ```markdown # ๐Ÿ‘ฅ Audience Intelligence **Period:** [Timeframe] **Interactions analyzed:** [Count] ## Persona Patterns ### [Persona Name] (Primary Audience) - **Typical roles:** [Titles] - **Company size:** [Range] - **Top pain points:** 1. [Pain point 1] 2. [Pain point 2] - **Key motivations:** [What drives them] - **Decision criteria:** [What they care about] ## Messaging Insights ### Langu...

Details

Author
davekilleen
Repository
davekilleen/Dex
Created
6 months ago
Last Updated
today
Language
Python
License
NOASSERTION

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