AEO performance tracking

Primary metrics for AEO performance:

1. 1AI System Appearance Rate: What percentage of target queries return your business in AI answers?
2. 2Appearance Frequency: Are you appearing more frequently over time?
3. 3Citation Frequency: How often are you cited by Perplexity compared to competitors?
4. 4Query Volume Covered: How many different queries return your business?
5. 5Competitive Position: Are you outranking or underranking competitors?
6. 6Review Metrics: Review count growth, rating stability, response rate
7. 7Citation Growth: New citations added, citation consistency improvement
8. 8Content Performance: Content publication frequency, topic coverage expansion

Each metric tracks different component of AEO strategy. Collectively, they reveal whether your strategy is working.

Track not just your appearance rate but competitors' rates.

Competitive benchmarking spreadsheet:

This spreadsheet reveals: where you're losing to competitors, where you're winning, and where you're tied.

Appearance gaps (competitors appear, you don't) become optimization priorities. If Competitor A appears in 80% of test queries and you appear in 20%, they're capturing 4x as much visibility.

Perplexity explicitly cites sources, making citation tracking straightforward.

Monthly, test 30-50 queries and document: - Which of your content pieces get cited - How many times you're cited vs. competitors - Which topics generate citations - Which competitors' content gets cited more frequently

Citation frequency directly correlates with Google Search ranking for those queries (because Perplexity sources from top Google results). If you're not being cited by Perplexity but competitors are, improve your Google Search ranking for those queries.

Track citation trends. Citation count should increase monthly as you improve Google rankings and publish new content.

Track citation consistency across platforms:

Monthly audit of NAP consistency: - Pull current citations across 15+ platforms - Compare against canonical NAP - Count inconsistencies - Track trends month-over-month

Goal: zero inconsistencies within 90 days, then maintain consistency. Inconsistency directly reduces AI visibility.

Track content production and performance:

Metrics: - Number of new content pieces published (goal: 2-4 monthly for brands, 0-1 for dispensaries) - Topics covered (expanding topic coverage improves visibility) - Content word count (goal: 2,000+ for cornerstone, 800-1,200 for supporting) - Internal linking (track how many internal links each piece receives) - Backlinks earned (track new backlinks to content monthly)

Monitor technical metrics monthly using free Google tools:

Core Web Vitals (use PageSpeed Insights): - Largest Contentful Paint (target: under 2.5 seconds) - Cumulative Layout Shift (target: under 0.1)

Site performance metrics: - Page load time - Mobile vs. desktop performance - SSL certificate validity - Crawl errors in Google Search Console

Improving technical metrics improves both SEO and AEO performance.

Create monthly AEO performance report:

1. 1Executive Summary: Overall progress, key wins, areas needing attention
2. 2Appearance Rate Trends: Monthly tracking, by AI system, by query type
3. 3Competitive Benchmarking: How you're performing vs. key competitors
4. 4GBP Metrics: Review growth, ratings, profile engagement
5. 5Citation Status: Consistency, new citations, remaining gaps
6. 6Content Performance: New content published, topics, performance
7. 7Technical Status: Core Web Vitals, other technical metrics
8. 8Perplexity Citations: Which content got cited, citation frequency trends
9. 9Tactical Adjustments: Based on data, what's working, what needs adjustment
10. 10Next Month Priorities: Focus areas and expected improvements

Monthly reporting maintains accountability and enables rapid tactical adjustment based on performance data.

Free tools: - Google Search Console: Search performance, crawl data - Google PageSpeed Insights: Core Web Vitals, technical metrics - Google Business Profile analytics: Review, rating, engagement metrics - Manual spreadsheets: Appearance rate, competitive benchmarking

Paid tools (optional but helpful): - Semrush/Ahrefs: Backlink tracking, keyword ranking for Google - Moz Local: Citation consistency auditing

AEO performance improves slowly compared to paid search but faster than traditional organic search.

Realistic timeline:

Months 1-2 (Foundation Work): Implement GBP fixes, add missing citations, fix technical issues. Minimal visibility improvement expected.

Gemini and Perplexity show improvement first.

Months 5-6 (Acceleration): Content starts generating visibility improvement. Citation consistency drives improvement.

Months 7-12 (Maturation): AEO visibility stabilizes. Focus shifts to maintaining advantage over competitors.

Unlike Google Search, which provides granular ranking data in Search Console, AI systems provide zero direct measurement of your visibility or ranking. You cannot log into ChatGPT and see "You rank #3 for cannabis strains." This measurement gap means businesses must establish proprietary tracking systems or use third-party tools to measure AEO performance. Without active measurement, businesses have no visibility into whether AEO optimization is working. This differs fundamentally from Google Search, where ranking improvements are immediately observable. The practical implication: cannabis businesses need to establish rigorous monthly testing protocols to measure appearance rates across AI systems.

Monthly appearance rate testing reveals not just your performance but competitive performance simultaneously. Testing which competitors appear in answers for your target queries provides competitive benchmarking that's impossible with Google Search (where visibility to individual users is not transparent). This competitive transparency allows cannabis businesses to see exactly which competitors are outperforming them in AI search and by what margin. If you appear in 15% of Gemini answers and Competitor A appears in 80%, that gap quantifies the visibility opportunity. This data-driven competitive understanding enables strategic prioritization: rather than guessing which optimizations matter, you can see which competitors' tactics are succeeding and replicate them strategically.