Powerful Features to Win AI Recommendations

GEO Style Key Features

GEO Style provides comprehensive decision intelligence for AI discovery. Our key features include decision feed tracking, change detection, revenue impact estimation, ROI calculation, attribution tracking, brand safety monitoring, competitive intelligence, E-E-A-T analysis, content workflow from idea to publish linked to recommendations and decisions, and Moves to Win actionable recommendations.

Key Features

• Decision Feed: Command queue of buying decisions you're winning or losing, ranked by impact score. Shows status (LOST, WEAK, COMPETITIVE, WON), winning competitor, explanation, and suggested actions. Prioritize high-impact opportunities
• Sentiment Intelligence: Track sentiment trends over time and compare against competitors with real-time analysis. Understand brand perception
• AI Prompt Discovery: Automatically discover high-value prompts from competitor analysis and user patterns. Find untapped opportunities
• Demand Scoring: Prioritize prompts by actual buyer demand with cluster analysis and intent weighting. Focus on what matters
• Competitive Intelligence: Head-to-head comparisons showing who AI chooses and why. Tracks share of recommendations, win rates, prompt dominance, and competitor movements (gains/losses). Understand competitive position
• Citation Types (Used vs Cited): Distinguish between USED citations (API metadata) and CITED citations (text URLs) for deeper insights. Understand citation quality
• Reputation Risk Monitoring: Monitor mentions for negative sentiment, misinformation, and brand reputation risks. Creates alerts with severity levels (LOW, MEDIUM, HIGH, CRITICAL) and sends email notifications. Protect brand reputation
• E-E-A-T Analysis: Measure Experience, Expertise, Authoritativeness, and Trustworthiness signals. Calculates overall E-E-A-T score based on citations, mentions, and brand safety indicators. Build AI trust signals
• GEO Maturity Model: Assess decision intelligence maturity (0-5 scale) with actionable next steps. Calculates level based on presence rate, citation rate, share of voice, recommendation weight, first position rate, and cross-model presence. Know your AI discovery maturity
• Moves to Win: Actionable recommendations bound to specific decisions and competitors. Tracks effectiveness by measuring decision status changes after completion with effectiveness scores (0-100). Take action that works
• Content Workflow: Create and manage content with a workflow from idea to draft, review, and publish. Link content to recommendations and decisions, generate AI briefs and drafts, and track effectiveness. Scale content that wins decisions
• Content Studio: Build reusable recipes that write content in steps — research, brief, outline, draft, revision, and search metadata — then run one for a single piece or fan it across a batch of topics, pages, or backlog actions. Produce content at the size of your backlog
• CMS Publishing: Push approved content straight to WordPress or Webflow from the content editor. Connect a CMS, map fields, preview the payload, push as draft or live, and publish on a schedule. Ship the fix without leaving the loop
• Website Health: One score and one fix queue for the site itself, with GEO readiness, security, and accessibility as three domains of the same audit. Know whether your site is fit to be cited
• Accessibility Analysis: WCAG-mapped findings scored across POUR, grouped into a fix queue by rule and page template so one change clears many pages. Fix the barrier once, not once per page
• Security & Trust Surface: External security exposure indicators with the evidence behind them, plus authorized scanner verification inside a scope you declare. See your exposure the way an outsider does
• Revenue Impact Estimation: Estimate revenue at risk from lost decisions with confidence-adjusted ranges. Provides per-opportunity estimates showing current vs potential monthly revenue and revenue gap. Quantify opportunity cost
• Attribution Tracking: Connect AI citations to Google Analytics traffic and measure conversion impact. Tracks referrer URLs, traffic sources, sessions, conversions, revenue, time lag, and correlation scores. Prove AI drives revenue
• Model Analytics: Model-specific behavior analysis and strategies. Tracks performance per model including presence rates, citation rates, win rates, and model-specific patterns with cross-model presence tracking. Optimize per AI model
• Executive Dashboard: High-level summary for leadership with key metrics, trends, and competitor insights. Available on the Dashboard via the Executive view. Shows total/won/lost/competitive/weak decisions, revenue impact, top competitors, and trend indicators. Align leadership on AI strategy
• Prompt Clustering: Groups similar prompts to reduce duplication and identify patterns. Uses embedding-based similarity (cosine similarity) with text-based fallback and canonical prompt linking. Identify prompt patterns
• Change Detection: Automatically track decision status changes and competitor movements over time. Records changes in DecisionChangeHistory with real-time alerts via GraphQL subscriptions. Stay ahead of competitive shifts