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FEBRUARY 6, 2026 // UPDATED FEB 8, 2026

The 10 AI Visibility Metrics You Should Track Weekly

Stop guessing about your AI visibility performance. Here are the 10 essential metrics to track weekly, how to measure them, and what benchmarks to aim for.

AUTHOR
DJL
Dr. James Liu
HEAD OF RESEARCH
READ TIME
8 MIN

Effective AI visibility management requires consistent measurement. But with so many possible metrics to track, which ones actually matter?

Based on analyzing hundreds of AI visibility campaigns, here are the 10 metrics that best predict success—and how to track each one.

The Essential 10 Metrics

1. Share of Voice (SOV)

What it measures: How often your brand is mentioned when users ask AI about your category.

How to track it:

  • Run standardized queries across ChatGPT, Claude, and Perplexity
  • Track which brands are mentioned in each response
  • Calculate your mention rate vs. competitors
  • Use automation for consistent weekly tracking

Benchmark targets:

Market PositionTarget SOV
Market Leader30%+
Challenger15-25%
Niche Player10-15%

Weekly action: Run 20 category-relevant queries and track your mention rate.


2. AI Platform Referral Traffic

What it measures: Direct visitors coming from AI platforms to your website.

How to track it:

  • In GA4, go to Reports → Acquisition → Traffic Acquisition
  • Filter for sources containing "openai", "perplexity", "anthropic", "claude"
  • Create a custom segment for "AI Platform Traffic"

Benchmark targets:

  • Early stage: 100+ monthly AI visitors
  • Growing: 500+ monthly
  • Mature: 2,000+ monthly

Weekly action: Check week-over-week change in AI referral volume.


3. AI Visitor Conversion Rate

What it measures: How well AI-referred visitors convert compared to other channels.

How to track it:

  • Set up conversion goals in GA4
  • Compare AI segment conversion rate to site average
  • Track by conversion type (signup, purchase, demo request)

Benchmark targets:

  • Minimum: Equal to site average
  • Good: 1.5x site average
  • Excellent: 2x+ site average

Weekly action: Compare AI conversion rate to previous 4-week average.


4. Brand Search Lift

What it measures: Increase in people searching for your brand name, often influenced by AI recommendations.

How to track it:

  • Google Search Console for branded query impressions
  • Google Trends for relative search volume
  • Compare to pre-AI visibility baseline

Benchmark targets:

  • Monthly growth: 5-15%
  • Quarterly growth: 20-40%
  • Significant lift correlates with AI visibility improvements

Weekly action: Check branded search impressions vs. previous week.


5. Sentiment Score

What it measures: Whether AI mentions your brand positively, neutrally, or negatively.

How to track it:

  • Analyze AI responses mentioning your brand
  • Categorize as positive, neutral, or negative
  • Calculate weighted sentiment score

Scoring example:

Positive mention: +1
Neutral mention: 0
Negative mention: -2

Sentiment Score = Sum of scores / Number of mentions

Benchmark targets:

  • Minimum: 0.3 (slightly positive)
  • Good: 0.5-0.7
  • Excellent: 0.8+

Weekly action: Run 10 brand-specific queries and score sentiment.


6. Recommendation Position

What it measures: Where you appear in AI recommendation lists (first, second, third, etc.).

How to track it:

  • When mentioned, note your position in the list
  • Track position distribution over time
  • Calculate average position

Benchmark targets:

PositionImpact
1stHighest click-through
2nd-3rdStrong visibility
4th-5thModerate visibility
6th+Low impact

Weekly action: Track position for your top 10 target queries.


7. Competitor Gap

What it measures: The difference between your share of voice and your top competitor's.

How to track it:

  • Track SOV for your top 3 competitors
  • Calculate the gap (Competitor SOV - Your SOV)
  • Monitor gap trend over time

Benchmark targets:

  • Closing gap: Negative trend (you're catching up)
  • Maintaining position: Stable gap
  • Falling behind: Growing gap

Weekly action: Calculate gap vs. #1 competitor.


8. Content Citation Rate

What it measures: How often AI references your content as a source.

How to track it:

  • For platforms that cite sources (Perplexity), track citations
  • Note which content pieces get cited
  • Measure citation frequency

Benchmark targets:

  • Early stage: Any citations
  • Growing: 5+ weekly citations
  • Mature: 20+ weekly citations

Weekly action: Count citations in Perplexity for brand queries.


9. Query Coverage

What it measures: What percentage of relevant queries you appear in.

How to track it:

  • Define your target query set (50-100 queries)
  • Test weekly and track appearance rate
  • Identify gaps and opportunities

Benchmark targets:

CoverageStatus
<20%Low visibility
20-40%Developing
40-60%Good
60%+Strong

Weekly action: Test your top 20 queries and calculate coverage %.


10. Revenue Attribution

What it measures: Revenue directly or indirectly tied to AI visibility.

How to track it:

  • Direct: AI referral × conversion rate × AOV
  • Survey: % of customers citing AI × total revenue
  • Correlation: Revenue change vs. AI visibility change

Calculation:

Weekly AI Revenue =
  (Direct AI conversions × AOV) +
  (Survey attribution × Weekly revenue × AI %) +
  (Brand search lift attribution)

Benchmark targets:

  • Track trend, not absolute number
  • Aim for consistent week-over-week growth
  • Compare to investment for ROI

Weekly action: Update revenue attribution calculation.


Building Your Dashboard

Top Row: Key Performance Indicators

┌─────────────────┬─────────────────┬─────────────────┐
│  Share of Voice │  AI Referrals   │  Conversion Rate│
│     18% ↑       │    1,247 ↑      │    4.2% ↓       │
└─────────────────┴─────────────────┴─────────────────┘

Second Row: Trend Charts

  • Share of Voice (12-week trend)
  • AI Referral Traffic (12-week trend)
  • Revenue Attribution (12-week trend)

Third Row: Competitive Position

  • Your SOV vs. Top 3 Competitors
  • Sentiment comparison
  • Query coverage gaps

Bottom Row: Action Items

  • Queries where you're missing
  • Content needing optimization
  • Competitor moves to respond to

Tool Recommendations

Free/Low-Cost Stack:

  • Google Analytics 4 (traffic tracking)
  • Google Search Console (brand search)
  • Manual AI query testing (spreadsheet tracking)
  • Google Data Studio (dashboard)

Professional Stack:

  • Dedicated AI visibility platform
  • Automated query monitoring
  • Competitive intelligence tools
  • Revenue attribution software

Weekly Review Process

15-Minute Weekly Check

Every week, review:

  1. Share of Voice change - Up, down, or stable?
  2. Traffic trend - Are AI referrals growing?
  3. Conversion rate - Any concerning changes?
  4. Competitor movement - Any threats?
  5. Action items - What needs attention?

Monthly Deep Dive

Once monthly, analyze:

  • Full query coverage audit
  • Sentiment analysis across all mentions
  • Content performance by citation rate
  • ROI calculation update
  • Strategy adjustment recommendations

Quarterly Strategy Review

Every quarter:

  • Competitive landscape assessment
  • Query set refinement
  • Benchmark recalibration
  • Goal setting for next quarter
  • Budget and resource planning

Common Tracking Mistakes

Mistake 1: Tracking Too Many Metrics

More metrics doesn't mean better insights. These 10 cover the essentials—adding more creates noise without clarity.

Mistake 2: Inconsistent Query Sets

Using different queries each week makes trends meaningless. Standardize your query set and stick to it.

Mistake 3: Ignoring Competitor Data

Your absolute numbers mean less than your relative position. Always track competitor performance alongside your own.

Mistake 4: Short-Term Focus

Weekly data is noisy. Always look at 4-week rolling averages for decision-making.

Mistake 5: Not Acting on Data

The best dashboard is useless without action. Every weekly review should generate at least one specific action item.

Setting Up Automated Tracking

Basic Automation (Spreadsheet)

  1. Create a Google Sheet with metric columns
  2. Set calendar reminder for weekly data entry
  3. Add formulas for trends and comparisons
  4. Create simple charts for visualization

Intermediate Automation

  1. Use Google Apps Script to pull GA4 data
  2. Create template for query testing results
  3. Build automated trend calculations
  4. Schedule weekly email reports

Advanced Automation

  1. API connections to all data sources
  2. Automated AI query testing
  3. Real-time dashboard updates
  4. Automated alerting for significant changes

Key Takeaways

  1. Focus on these 10 metrics - They cover all essential AI visibility dimensions
  2. Track weekly - Consistent measurement enables trend analysis
  3. Compare to competitors - Relative position matters more than absolute numbers
  4. Act on insights - Data without action is worthless
  5. Build toward automation - Start manual, scale up as you prove value

Ready to start tracking your AI visibility? Get a baseline with a free visibility audit, or talk to our team about implementing a complete measurement system.

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