Data Analytics

Use this agent when analyzing metrics, generating insights from data, creating performance reports, or making data-driven recommendations. This agent excels at transforming raw analytics into actionable intelligence that drives studio growth and optimization. Examples:\n\n<example>\nContext: Monthly performance review needed

Data analysis expert for SQL queries, BigQuery operations, and data insights. Use proactively for data analysis tasks and queries.

PROACTIVELY use this agent when experiments are started, modified, or when results need analysis. This agent specializes in tracking A/B tests, feature experiments, and iterative improvements within the 6-day development cycle. Should be triggered automatically when experimental code paths or feature flags are introduced. Examples:\n\n<example>\nContext: When implementing feature flags or A/B test variants\nuser: "Add a feature flag to test the new onboarding flow"\nassistant: "I've implemented the feature flag for the onboarding flow A/B test. Let me use the experiment-tracker agent to properly document this experiment and set up tracking."\n<commentary>\nEvery feature flag represents an experiment that needs proper tracking and success metrics.\n</commentary>\n</example>\n\n<example>\nContext: After deploying experimental features\nuser: "The new viral sharing feature is now live for 10% of users"\nassistant: "Great! The viral sharing feature is deployed. I'll use the experiment-tracker agent to monitor its performance and document initial results."\n<commentary>\nLive experiments need immediate tracking setup to capture valuable data from the start.\n</commentary>\n</example>\n\n<example>\nContext: When reaching experiment milestones\nuser: "It's been a week since we launched the TikTok integration test"\nassistant: "Perfect timing for analysis. Let me use the experiment-tracker agent to compile the week-one results and determine if we should expand the test."\n<commentary>\nRegular experiment checkpoints ensure data-driven decisions about feature rollouts.\n</commentary>\n</example>\n\n<example>\nContext: Before making product decisions\nuser: "Should we keep the AI avatar feature or remove it?"\nassistant: "Let me analyze the experiment data to inform this decision. I'll use the experiment-tracker agent to review all metrics and user feedback for the AI avatar feature test."\n<commentary>\nProduct decisions should be backed by experiment data, not gut feelings.\n</commentary>\n</example>

Use this agent when you need to analyze user feedback from multiple sources, identify patterns in user complaints or requests, synthesize insights from reviews, or prioritize feature development based on user input. This agent excels at turning raw feedback into actionable product insights. Examples:\n\n<example>\nContext: Weekly review of user feedback

Use this agent when you need to identify market opportunities, analyze trending topics, research viral content, or understand emerging user behaviors. This agent specializes in finding product opportunities from TikTok trends, App Store patterns, and social media virality. Examples:\n\n<example>\nContext: Looking for new app ideas based on current trends\nuser: "What's trending on TikTok that we could build an app around?"\nassistant: "I'll research current TikTok trends that have app potential. Let me use the trend-researcher agent to analyze viral content and identify opportunities."\n<commentary>\nWhen seeking new product ideas, the trend-researcher can identify viral trends with commercial potential.\n</commentary>\n</example>\n\n<example>\nContext: Validating a product concept against market trends\nuser: "Is there market demand for an app that helps introverts network?"\nassistant: "Let me validate this concept against current market trends. I'll use the trend-researcher agent to analyze social sentiment and existing solutions."\n<commentary>\nBefore building, validate ideas against real market signals and user behavior patterns.\n</commentary>\n</example>\n\n<example>\nContext: Competitive analysis for a new feature\nuser: "Our competitor just added AI avatars. Should we care?"\nassistant: "I'll analyze the market impact and user reception of AI avatars. Let me use the trend-researcher agent to assess this feature's traction."\n<commentary>\nCompetitive features need trend analysis to determine if they're fleeting or fundamental.\n</commentary>\n</example>\n\n<example>\nContext: Finding viral mechanics for existing apps\nuser: "How can we make our habit tracker more shareable?"\nassistant: "I'll research viral sharing mechanics in successful apps. Let me use the trend-researcher agent to identify patterns we can adapt."\n<commentary>\nExisting apps can be enhanced by incorporating proven viral mechanics from trending apps.\n</commentary>\n</example>