Crowdlisten

Automated research compilation — track topics across platforms, store raw data, and maintain always-current KB documents with periodic crawl jobs.

Competitive intelligence through audience perception analysis. Use when comparing brands, products, or competitors in social conversations.

Generate SEO-optimized marketing content with brand voice analysis. Blog posts, social media, email campaigns. Use when creating any branded content.

Data-driven content strategy grounded in audience demand. Topic demand analysis, content gaps, platform optimization, voice matching, campaign tracking.

Extract, evaluate, and persist structured context from chat transcripts — decisions, constraints, patterns, preferences, goals. Includes PII protection, skill discovery, and quality evaluation.

Full-cycle crowd intelligence — from research question to compiled truth. Teaches agents WHEN to research, HOW to evaluate evidence, and WHERE to store knowledge so it compounds.

Transform data and analysis into compelling narratives. Problem-Solution, Trend, Comparison, Hero's Journey frameworks. Use when presenting insights to stakeholders.

Automated entity intelligence — discovers social handles and communities, runs crowd research for tracked entities, saves results to entity-scoped wiki pages, handles failures and scheduling. Teaches agents HOW to resolve entities, WHEN to research, and WHERE to store intelligence so it compounds.

Customer feedback analysis from social conversations. Journey friction detection, pain point mapping, persona generation, churn risk signals.

Crowd intelligence knowledge management — the capture-compile-synthesize-prune cycle for building compiled truth from audience data, analyses, and research. Teaches agents to file, merge, age, and retrieve crowd knowledge with judgment.

Generate comprehensive market research reports with Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, BCG Matrix. Use for market analysis, competitive landscape, industry trends.

Multi-agent coordination — teaches agents when to work solo vs. together, how to claim work without conflicts, share knowledge through wiki, and coordinate through the task board. Encodes the judgment that prevents wasted parallel effort.

Turn crowd intelligence into actionable product specs — feature requests, user stories, and acceptance criteria. Teaches agents WHEN evidence is strong enough to spec, HOW to score priority from crowd signals, and WHERE specs fit in the compile-to-ship pipeline. Encodes judgment against premature speccing and thin-evidence anti-patterns.

Teaches agents to decompose complex goals into executable subtasks with dependency ordering. Encodes judgment about task granularity, parallelization opportunities, and result threading between steps.

Turn social listening data into product decisions. JTBD extraction, feature demand scoring, persona generation, user story generation from real audience data.

UX research synthesis — user personas, journey maps, heuristic evaluation (Nielsen's 10), design recommendations. Use when analyzing user behavior or designing experiences.