How do I trigger an audience analysis in Claude Code?

You can trigger the skill using natural language commands such as 'analyze audience', 'build personas', 'segment audience', or 'who is our target'.

Does this skill provide messaging recommendations?

Yes, it generates specific value propositions, objection handlers, and tone-of-voice guidelines for every persona it creates.

Can I use this for B2B segmentation?

Absolutely. The skill includes frameworks for firmographic and technographic segmentation, making it ideal for B2B SaaS and enterprise growth strategies.

What data sources does the Audience Synthesis skill support?

The skill supports first-party data (Google Analytics, Salesforce, HubSpot), second-party data (Social insights, Ads), and third-party enrichment data (Clearbit, Industry reports).

Audience Synthesis

Name: Audience Synthesis
Author: jmagly

byjmagly

•

Marketing Automation

Synthesizes disparate audience data into unified, actionable personas and data-driven behavioral segments.

About

The Audience Synthesis skill transforms raw data from CRM systems, web analytics, social platforms, and third-party research into comprehensive audience profiles. It identifies demographic clusters, maps detailed customer journeys, and recommends specific targeting strategies based on observed behavioral patterns. By automating the aggregation and analysis of first, second, and third-party data, it provides developers and marketers with a clear understanding of their ideal customer profiles and high-growth opportunities.

Key Features

Advanced behavioral, value-based, and lifecycle segmentation
67 GitHub stars
Comprehensive growth opportunity reporting with targeting recommendations
Automated generation of data-driven personas with psychographic insights
Multi-source data aggregation from CRM, Analytics, and Social platforms
Detailed customer journey mapping and channel preference identification

Use Cases

Analyzing churn risks and identifying high-value retention opportunities
Optimizing marketing spend through precise lookalike audience definitions
Developing data-backed ICPs (Ideal Customer Profiles) for product launches

About

Key Features

Advanced behavioral, value-based, and lifecycle segmentation
67 GitHub stars
Comprehensive growth opportunity reporting with targeting recommendations
Automated generation of data-driven personas with psychographic insights
Multi-source data aggregation from CRM, Analytics, and Social platforms
Detailed customer journey mapping and channel preference identification

Use Cases

Analyzing churn risks and identifying high-value retention opportunities
Optimizing marketing spend through precise lookalike audience definitions
Developing data-backed ICPs (Ideal Customer Profiles) for product launches