🤖LLM Rank Tracker
This tool enables you to monitor your brand's visibility and sentiment across AI-powered search results, including Google AI Overview and Google AI Mode. Track how often your brand appears in AI-generated responses, analyze competitor mentions, monitor citations, and measure sentiment over time to understand your brand's presence in the AI search landscape.
Initial Setup: Configuring Required API Credentials
Before you can start tracking your brand in AI responses, you need to configure the required API credentials. The LLM Rank Tracker requires two different API services to function properly.
Required API Credentials
1. DataForSEO Credentials
DataForSEO provides access to Google's AI-powered search features:
Purpose: Required for tracking Google AI Mode and Google AI Overview
Cost: Pay-as-you-go pricing, approximately $1.2 per 1,000 queries
Account Type: You must have your own DataForSEO account
Important: You cannot use rented API key services for LLM Rank Tracker. DataForSEO restricts certain endpoints that are essential for the queue mode functionality. Multiple users sharing a rented API key would slow down processing for everyone. For optimal performance, use your own DataForSEO account.
2. OpenAI API Key
OpenAI's API is used for intelligent data extraction:
Purpose: Required for extracting structured brand mentions from AI responses
Model Used: GPT-4o-mini for cost efficiency
Cost: Minimal due to efficient prompt design and caching. You can track the costs in your Open AI dashboard.
Optional API Credentials
3. Google NLP API Key (Optional)
Google's Natural Language API provides advanced sentiment analysis:
Purpose: Enables sentiment analysis of brand mentions in AI responses
When to use: If you want to track how positively or negatively your brand is mentioned
Note: Without this API key, sentiment analysis will be skipped and sentiment scores will not be available
Pricing Structure:
Free Tier: First 5,000 units per month are free (1 unit = 1,000 characters)
Paid Tiers:
5,001 to 1,000,000 units: $0.0010 per unit
1,000,001 to 5,000,000 units: $0.0005 per unit
Over 5,000,000 units: $0.00025 per unit
Example: Analyzing 2,500 characters = 3 units
Setting Up Your API Credentials
Click "Configure API Keys" on the onboarding screen or Navigate to Settings > Services in the application
Add DataForSEO Credentials (Required):
Enter your DataForSEO login (email)
Enter your DataForSEO password
Add OpenAI API Key (Required):
Enter your OpenAI API key
Add Google NLP API Key (Optional - for sentiment analysis):
Navigate to Settings > NLP
Enter your Google Natural Language API key
This enables sentiment analysis of brand mentions
Settings page showing where to configure API credentials
If you don't have a DataForSEO account yet, visit this guide for step-by-step instructions on creating one.
How to Create Your First LLM Rank Tracker
Creating an LLM Rank Tracker involves configuring what to track (your brand variants), where to track (AI engines), and how to track (search terms and schedule).
Step 1: Access the LLM Rank Tracker Tool
Navigate to the LLM Rank Tracker section from the main menu. You'll see a list of existing trackers (if any) and an "Add LLM Rank Tracker" button in the top-right corner.
Step 2: Configure Basic Tracker Settings
Clicking "Add LLM Rank Tracker" opens a configuration modal. Let's go through each field in detail:
Brand Variants
Purpose: All variations of your brand name that should be tracked in AI responses.
How to Add: Type a brand variant in the input field and hit the enter or comma key (",") to aplly.
What to Include:
Official brand name: "SEO Utils"
Common variations: "SEOUtils", "SEO Utils App"
Abbreviations: "SU" (if commonly used)
Misspellings: "SEO Util", "SEOUtils"
Previous names: If recently rebranded
Domain variations: "seoutils.app"
AI Engines Selection
Available Options:
Google AI Overview:
Appears in regular Google search results
Shows as a collapsible AI-generated summary
Desktop-only feature
Provides citations to source websites
Google AI Mode:
Accessed via Google's AI mode search
Conversational AI responses
Different from regular search results
Currently English-only
Location and Language Configuration
Location / Language Dropdown:
Select your primary target market
Affects how queries are sent to AI engines
Influences the results you receive
Geo Target (Optional):
For more specific location targeting
Enter city, state, or region
Overrides the general location setting
Examples: "New York, NY", "London", "California"
Schedule Configuration
Schedule Frequency: Determines how often the tracker runs automatically.
How Scheduling Works:
First run happens immediately when you create the tracker
Subsequent runs occur at the scheduled interval
SEO Utils must be open for scheduled runs
Recommended Schedules:
On-demand (0): Manual runs only
Daily (1): For competitive industries or active campaigns
Weekly (7): For stable markets with regular monitoring needs
Monthly (30): For long-term trend analysis or low-competition niches
After filling all fields, click "Create Tracker". The system will redirect you to the tracker detail page
Managing Your LLM Rank Tracker
Once your tracker is created and running, you'll need to manage various aspects to maintain effective tracking.
Understanding the Report Header
The report header provides essential information at a glance:
Report Title: Shows your primary brand name
Edit Button: Quick access to modify tracker settings
Key Metrics Bar:
Brand variants count with list on hover
AI engines count with details on hover
Search terms count (clickable)
Snapshots count (clickable)
Last updated timestamp with next run on hover
Running the Tracker Manually
To run the tracker outside of its schedule:
Click "Run Tracker" button in the top-right
Confirm in the modal showing:
Number of brand variants
Total search terms
AI engines to query
Monitor progress in the Log Panel
Wait for completion notification
Managing Search Terms
Access search term management by clicking the search terms count in the header.
Organizing with Tags
Tags help categorize search terms for better analysis:
Creating Tags:
Select search terms using checkboxes
Click "Update Tags" from bulk actions
Add relevant tags:
By intent: "informational", "commercial", "comparison"
By product: "rank-tracker", "serp-clustering"
By competition: "vs-competitor", "alternative-searches"
By priority: "high-priority", "monitoring"
Search terms organized with multiple tags
Managing Snapshots
Snapshots represent daily tracking data points. Access via the snapshots count in the header.
Understanding Snapshots
Key Concepts:
One snapshot per day maximum
Re-running on the same day updates existing snapshot
Each snapshot contains all search term results
Deleting a snapshot removes all associated data
Managing Snapshot Data
Viewing Details:
Snapshots are listed newest first
Use date sorting to find specific periods
Search by date using the search box
Deleting Snapshots:
Click the three-dot menu on a snapshot
Select "Delete"
Confirm deletion (irreversible)
Warning: Deleting a snapshot permanently removes:
All position data for that date
Associated citations and sources
Sentiment analysis results
Competitor data for that date
Understanding the Report Tabs
The LLM Rank Tracker provides four comprehensive analysis tabs, each offering unique insights into your brand's AI visibility.
Overview Tab: Brand Performance Metrics
The Overview tab provides a high-level view of your brand's performance across AI platforms.
Key Performance Indicators (KPIs)
1. Visibility
Definition: How often your brand appears in AI responses
Calculation: (Queries with brand mention / Total queries) × 100
Good benchmark: 20-30% for branded searches, 5-10% for non-branded
2. Top 3 Visibility
Definition: Percentage of queries where your brand ranks in the top 3 positions
Calculation: (Queries where brand ranks 1-3 / Total queries) × 100
Indicates: How prominently your brand appears when mentioned
3. Average Position
Definition: The average position across all queries in the selected date range where your brand was mentioned
Range: 1-10+ (lower numbers indicate better visibility)
Position 0: Not mentioned in the response
4. Latest Position
Definition: The average position from the snapshot closest to your selected end date
Purpose: Shows your most recent performance within the date range
Use case: Quickly assess current standing without changing date ranges
KPI cards with period comparisons
Secondary Metrics
Below the primary KPIs, you'll find three additional metrics that provide deeper insights:
1. Sentiment Score
Definition: Average sentiment of your brand mentions (0-100 scale)
Calculation: Converts sentiment from -1 to +1 range to 0-100 scale
Range: 0 (very negative) to 100 (very positive)
Good benchmark: 70+ indicates positive brand perception
2. Total Citations
Definition: Number of cited sources that mention your brand
What it measures: How many URLs/sources referenced by AI contain mentions of your brand
Calculation: Count of citations where your brand appears in the cited content
Importance: More citations = stronger brand presence in AI's source material
3. Detection Rate
Definition: Percentage of search terms where your brand appears
Calculation: (Search terms with brand mentions / Total search terms) × 100
What it shows: How many of your tracked queries mention your brand
Good benchmark: Higher percentage = better brand coverage
Performance Chart
The line chart visualizes your selected metrics over time, comparing your brand against top competitors.
Metric Selection: Use the dropdown to switch between different KPIs and metrics:
Visibility Score (default)
Average Position
Top 3 Visibility
Sentiment Score
Citations Count
Detection Rate
Chart Features:
Blue line: Your brand's performance
Colored lines: Top 10 competitors. The chart automatically selects the top 10 competitors based on your chosen metric. This means you're always comparing against the most relevant competition for each specific measurement.
Search Terms Performance Table
The table shows how your brand performs for each tracked search term:
Key Metrics:
Avg. Position: Average ranking across all AI engines (lower is better)
Visibility: Percentage of AI engines mentioning your brand
Sentiment: Tone of mentions (0-100 scale)
Citations: Number of sources referencing your brand
Individual AI Engines: Position in each platform
Using the Table:
Sort by any column to find opportunities
Filter by position range to focus on specific rankings
Search for specific terms or groups
Compare periods to track progress
Quick Tip: Focus on terms with positions 4-6—these are easiest to improve to top 3.
Competitors Tab: Competitive Intelligence
The Competitors tab reveals who else appears in AI responses for your tracked queries.
Competition Map (Scatter Plot)
What does it show?
The x-axis represents the Detection Rate (%) - how consistently a brand appears across all tracked search terms.
The y-axis represents the Average Position of a brand across all its mentions.
The size of each bubble represents the overall visibility of the brand. A larger bubble indicates higher visibility.
The color represents different brands for easy differentiation.
How to read it?
Bottom-right corner (low average position & high detection rate) → This means a brand appears consistently and ranks well (closer to position #1).
Top-left corner (high average position & low detection rate) → This means a brand appears sporadically and ranks poorly.
Large bubbles → These indicate brands with strong visibility across many queries.
Small bubbles → These brands have lower presence in AI responses.
Key benefits of the scatter plot
Identify market leaders → Look for large bubbles in the bottom-right corner.
Spot opportunities → Find areas with few competitors or weak positioning.
Track competitive movement → Monitor how positions shift over time.
Competitors Performance Table
Detailed metrics for each competitor:
Key Metrics Explained:
Visibility %:
How often they appear vs. total queries
Higher percentage = stronger AI presence
Compare to your own visibility
Total Mentions:
Raw count of appearances
Indicates content volume recognized by AI
Average Position:
Their typical ranking when mentioned
Lower numbers = more prominent placement
Detection Rate:
Consistency of appearances over time
100% = mentioned every day tracked
Lower % = sporadic mentions
Top 3 Rate:
Percentage of mentions in positions 1-3
Indicates prominence in AI responses
Competitors table with sortable columns
Competitive Analysis Strategies:
Identify Direct Threats:
High visibility + good positions
Consistent detection rates
Growing trend lines
Find Opportunities:
Competitors with declining metrics
Gaps where no one dominates
Queries with weak competition
Learn from Leaders:
Study their content strategy
Analyze their cited sources
Understand their positioning
Citations Tab: Source Authority Analysis
The Citations tab reveals which sources AI engines reference when responding to your tracked queries, helping you understand the authority landscape in your industry.
Citation Metrics Overview
At the top of the tab, five key metrics provide a snapshot of citation patterns:
Key Metrics:
Total Citations: Total number of links found across all AI responses for your tracked search terms
Unique URLs: Number of distinct URLs cited across all domains (not limited to your website)
Unique Domains: Number of distinct domains that received citations in AI responses
Brands Found: Number of distinct brand names detected in the citations (including yours and competitors)
Most Appearances: The highest number of times any single URL was cited
Citation Analysis Charts
Two visualization charts help you understand citation patterns:
Top 20 Citations by Domain: Bar chart showing which domains are cited most frequently
Daily Mentions by Top Domains: Line chart tracking citation trends over time for the most cited domains
URL Overview Tab
The URL Overview provides a detailed list of all cited URLs with rich context:
Table Information:
Citation URL: The specific page cited (with title when available)
Search Term: Which query triggered this citation
Mentioned Brands: Brands associated with this citation (your brand highlighted)
AI Engine: Which AI platform cited this URL
Found On: When the citation was first discovered
Filtering Options:
Filter by AI Engine
Filter by Mentioned Brands
Search across URLs and search terms
Domain Overview Tab
The Domain Overview aggregates citations by domain, showing the bigger picture:
Table Information:
Domain: Website domain with citation bar visualization
URLs: Number of unique pages cited from this domain (click to expand)
Citations: Total citation count with percentage share
Expandable Details: Click the URL count to see:
All specific pages cited from that domain
Citation count per page
AI engines that cited each page
Associated brands per citation
Expanded domain details showing individual URLs
Strategic Insights from Citations
Why Citations Matter:
Authority Signals: Frequently cited sources are considered authoritative by AI
Content Opportunities: Identify which types of content get cited
Partnership Targets: Find websites for potential collaborations
Competitive Intelligence: See where competitors get their authority
Action Items Based on Citation Data:
Create Content on Cited Domains: If certain domains dominate citations, consider guest posting or partnerships
Analyze Cited Content: Study what makes content "citation-worthy"
Build Relationships: Connect with editors and authors of frequently cited sources
Fill Citation Gaps: Create authoritative content where citations are lacking
Citation Strategy: Focus on domains that appear in both the "Top Citations" chart and have high brand association. These represent the most valuable opportunities for building your AI visibility through strategic content placement.
Sentiment Tab: Brand Perception Analysis
The Sentiment tab analyzes how AI platforms perceive and present brands in their responses, tracking sentiment scores over time and across different queries.
Sentiment Over Time by Brand
The line chart visualizes sentiment trends for each brand across the selected date range:
Chart Features:
Multiple brand lines: Each brand gets its own colored line
Sentiment scale: 0-100 (normalized from -1 to +1 scale)
Interactive tooltips: Hover to see exact sentiment scores
Dynamic legend: Shows all brands found in responses
Understanding Sentiment Scores:
80-100: Very positive sentiment
60-80: Positive sentiment
40-60: Neutral sentiment
20-40: Negative sentiment
0-20: Very negative sentiment
Sentiment Analysis by Brand Table
Below the chart, a comprehensive table breaks down sentiment metrics for each brand:
Table Columns:
Brand: Brand name with building icon for your brand
Source: AI engine that provided the sentiment data
Sentiment: Overall sentiment score with emoji indicator
😊 Positive (60%+)
😐 Neutral (40-60%)
😟 Negative (<40%)
Positive/Neutral/Negative: Count of mentions by sentiment type
Mentions: Total number of brand mentions
Expandable Keyword Analysis: Click the chevron button next to any brand to reveal detailed keyword-level sentiment:
The expanded view shows:
Search Term: The specific query
Sentiment Score: Score for that keyword-brand combination
Response Context: Actual text where the brand was mentioned
AI Engine: Which platform generated this response
This granular view helps you:
Identify which queries generate positive/negative sentiment
Read exact AI responses about your brand
Spot opportunities to improve brand perception
Compare sentiment across different AI engines
How Sentiment Analysis Works
Text Analysis Process:
Text Extraction: When a brand is mentioned in an AI response, the system extracts the specific text segment containing the brand mention
Google NLP Processing: The extracted text is sent to Google's Natural Language API for sentiment analysis
Sentiment Scoring: Google NLP returns a sentiment score ranging from -1 (very negative) to +1 (very positive)
Score Normalization: The system converts this to a 0-100 scale for easier interpretation
What Text is Analyzed:
The actual text snippet where your brand is mentioned in the AI response
Context around the brand mention is included for accurate sentiment detection
Each brand mention is analyzed separately if multiple mentions exist
Supported Languages for Sentiment: Sentiment analysis is currently available for:
English (en)
Spanish (es)
French (fr)
German (de)
Italian (it)
Portuguese (pt)
Japanese (ja)
Korean (ko)
Chinese (zh, zh-CN, zh-TW)
Russian (ru)
Strategic Insights from Sentiment Analysis
Sentiment Monitoring Benefits:
Brand Health Tracking: Monitor overall brand perception in AI responses
Competitive Benchmarking: Compare your sentiment against competitors
Issue Detection: Quickly spot queries generating negative sentiment
Content Strategy: Focus on improving content for problematic queries
Action Items Based on Sentiment:
For Negative Sentiment:
Review the specific queries and responses
Update content to address concerns
Create positive content around those topics
Monitor improvements over time
For Neutral Sentiment:
Add more compelling value propositions
Include customer success stories
Highlight unique benefits
For Positive Sentiment:
Amplify successful messaging
Use similar tone in other content
Leverage positive AI responses in marketing
Sentiment Alert: Pay special attention to queries where your brand has significantly lower sentiment than competitors. These represent immediate opportunities for improvement through better content and messaging.
Practical Use Cases and Strategies
Use Case 1: Brand Launch and Awareness Tracking
Scenario: You're launching a new brand or product and need to establish AI visibility from zero.
Strategy:
Baseline Setup: Initial search terms:
What is [brand name]
[Brand] reviews
[Brand] vs alternatives
[Product category] solutions
Best [product type] for [use case]
Track with these metrics:
Detection Rate: Start at 0%, aim for 20%+ in 3 months
Visibility Score: Monitor weekly growth
Sentiment: Ensure positive from the start
Optimization Actions:
Create comprehensive "About" content
Publish on domains with high citation rates
Build comparison pages vs. established brands
Monitor which content gets cited first
Success Metrics:
Week 1-4: First mentions appear
Month 2: 10%+ detection rate
Month 3: Consistent citations from authority domains
Use Case 2: Competitive Displacement Strategy
Scenario: A competitor dominates AI responses in your category.
Strategy:
Analysis Phase (Use Competition Map):
Identify their detection rate and average position
Export their top-cited URLs from Citations tab
Study their sentiment scores by keyword
Target Their Weaknesses:
Find keywords where they have low/negative sentiment
Identify gaps in their citation coverage
Look for outdated information in their cited content
Content Creation Plan:
Create superior content on their top-cited domains
Target keywords where they rank 4-6 (easier to displace)
Build relationships with sites that cite them
Track Progress:
Monitor position changes in head-to-head queries
Track citation share shifts
Compare sentiment scores weekly
Use Case 3: Reputation Crisis Management
Scenario: Negative sentiment appears in AI responses about your brand.
Immediate Response:
Identify Scope (Sentiment Tab):
Filter by negative sentiment (<40%)
Expand keywords to see exact responses
Check which AI engines show negative content
Source Analysis (Citations Tab):
Find which URLs drive negative mentions
Identify if it's from news, reviews, or forums
Check citation frequency of negative sources
Response Strategy:
Create authoritative response content
Update cited pages if you control them
Publish on high-authority domains
Monitor daily until sentiment improves
Tracking Recovery:
Daily sentiment monitoring
Citation source changes
Position improvements for affected queries
Use Case 4: Product Feature Optimization
Scenario: Determine which features to highlight based on AI visibility.
Strategy:
Feature-Specific Tracking: Search terms by feature:
[Brand] [feature] review
How does [brand] [feature] work
[Brand] [feature] vs [competitor]
Best [product] with [feature]
Analyze Performance (Overview Tab):
Which features get mentioned most?
Which have highest positions?
Which generate positive sentiment?
Citation Analysis:
Which features get cited from authority sites?
Are technical specs or benefits cited more?
Optimization:
Double down on well-performing features
Improve content for underperforming features
Create comparison content for strong features
Use Case 5: Multi-Location Brand Management
Scenario: Managing brand visibility across different geographic markets.
Setup:
Create Location-Specific Trackers:
One tracker per major market
Use appropriate geo-targeting
Include localized search terms
Location-Specific Queries:
Best [product] in [city]
[Brand] [location] reviews
[Service] near me (with geo-target)
[Brand] vs local competitors
Comparative Analysis:
Compare visibility scores across locations
Identify market-specific competitors
Track sentiment variations by region
Localization Strategy:
Create location-specific content
Build local citations
Address regional concerns
Best Practices and Optimization Tips
Setting Up Effective Tracking
1. Search Term Strategy
The 70-20-10 Rule:
70% Core Terms: Direct brand and product searches
20% Competitive: Comparison and alternative queries
10% Exploratory: Broad industry and problem-solving queries
Search Term Templates: Brand Searches:
[brand] review
is [brand] worth it
[brand] pricing
[brand] customer service
Comparison Searches:
[brand] vs [competitor]
[brand] alternatives
better than [brand]
[brand] or [competitor]
Problem Searches:
how to [solve problem]
best way to [achieve goal]
[industry] tools for [use case]
[problem] solution
2. Metric-Driven Optimization
Weekly Review Checklist:
Monthly Analysis:
Visibility Trends:
Compare month-over-month visibility scores
Identify fastest-growing competitors
Track market share changes
Citation Patterns:
New domains citing content
Changes in citation concentration
Opportunities for guest content
Sentiment Shifts:
Overall brand perception trends
Keyword-specific sentiment changes
Competitive sentiment comparison
Advanced Optimization Techniques
1. Citation Optimization Strategy
Build Citation Authority:
Analyze Top Cited Domains (Citations Tab):
Sort by citation count
Identify accessible platforms
Study cited content types
Content Placement Priority:
Tier 1: Domains with 50+ citations
Tier 2: Domains with 20-49 citations
Tier 3: Emerging domains with growth
Citation-Worthy Content:
Comprehensive guides with clear sections
Data-driven research and statistics
Comparison tables and matrices
Step-by-step tutorials
Expert quotes and insights
2. Position Improvement Tactics
For Positions 4-6 (Quick Wins):
Identify these positions in Overview Tab
Check current citations for these queries
Create content on higher-authority domains
Add structured data markup
Update existing content with fresh data
For No Visibility (Position 0):
Analyze competitors who rank
Check their citation sources
Create foundational content
Build topic authority gradually
Target long-tail variations first
3. Sentiment Optimization
Improving Negative Sentiment:
Identify Root Causes:
Expand keywords in Sentiment Tab
Read actual AI responses
Find common negative themes
Content Response Strategy:
Address concerns directly
Provide updated information
Share positive customer stories
Create FAQ content
Monitor Progress:
Daily sentiment tracking
A/B test messaging approaches
Track which content improves sentiment
4. Competitive Intelligence Framework
Weekly Competitive Analysis:
Competition Map Review:
Screenshot weekly positions
Track movement patterns
Identify rising competitors
Citation Competitive Analysis:
Compare domain overlap
Find exclusive citation sources
Track citation velocity
Sentiment Benchmarking:
Compare sentiment by keyword
Identify perception gaps
Find differentiation opportunities
ROI Measurement and Reporting
Executive Dashboard Metrics
Primary KPIs:
Visibility Score: Overall brand presence
Share of Voice: Your visibility vs. total market
Sentiment Index: Average sentiment across queries
Citation Authority: Unique domains citing you
Calculated Metrics: Share of Voice = (Your Mentions / Total Market Mentions) × 100 Citation Quality Score = (Citations from Top 20 Domains / Total Citations) × 100 Sentiment Advantage = Your Avg Sentiment - Competitor Avg Sentiment
Reporting Best Practices
Weekly Reports Should Include:
Visibility score with week-over-week change
Top 5 position improvements
New citations acquired
Sentiment alerts (if <40%)
Monthly Reports Should Include:
Comprehensive competitor analysis
Citation growth trends
Sentiment analysis by category
Strategic recommendations
Pro Tip: Create automated alerts for:
Visibility drops >10%
New competitors with >20% detection rate
Sentiment scores below 40%
Loss of citations from top domains
Common Pitfalls to Avoid
Over-Optimizing for Current AI Behavior:
AI algorithms evolve rapidly
Focus on quality content, not tricks
Build genuine authority
Ignoring Competitor Innovations:
Weekly Competition Map reviews are essential
New entrants can disrupt quickly
Learn from competitor successes
Neglecting Citation Diversity:
Don't rely on single domains
Build broad citation portfolio
Maintain content freshness
Reactive vs. Proactive Approach:
Don't wait for problems
Anticipate market changes
Test new content formats
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