Analytics

Monitor your AI usage and credit consumption with detailed analytics that help you optimize your team’s AI interactions and control spending across all 37+ models.

Analytics Dashboard

Usage Overview

Get a complete picture of your AI usage:

Usage by Model - Track which AI models your team uses most
Usage by User - Monitor individual team member activity (for organizations)
Timeline Analytics - View usage patterns over time with customizable intervals
Credit Reports - Detailed credit consumption and cost analysis
Performance Metrics - Response times and prompt execution speed

Usage Analytics

By AI Model

Track usage across all available models:

📊 Model Usage (Last 30 Days)
├── ChatGPT Models
│   ├── GPT-4o (2x): 2,450 prompts (4,900 credits used)
│   ├── GPT-4 Turbo (1x): 1,200 prompts (1,200 credits used)
│   └── GPT-3.5 Turbo (0.3x): 800 prompts (240 credits used)
├── Claude Models
│   ├── Claude 3.7 Sonnet (2.5x): 1,100 prompts (2,750 credits used)
│   ├── Claude 3.5 Sonnet (1x): 600 prompts (600 credits used)
│   └── Claude 3 Haiku (0.5x): 300 prompts (150 credits used)
├── Other Models
│   ├── Llama 3.3 70B (1x): 400 prompts (400 credits used)
│   ├── DeepSeek V3 (1x): 150 prompts (150 credits used)
│   └── All Others: Combined usage
└── Total Credits Used: 10,390 credits

By Team Member (Organizations)

Monitor individual usage patterns:

User	Total Prompts	Top Model	Credits Used	Avg Cost per Prompt
sarah@company.com	1,250	GPT-4o (2x)	2,650 credits	2.1 credits
mike@company.com	980	Claude 3.7 (2.5x)	2,180 credits	2.2 credits
anna@company.com	720	GPT-4 Turbo (1x)	720 credits	1.0 credits
tom@company.com	650	Llama 3.3 (1x)	615 credits	0.9 credits
team@company.com	4,600	Mixed	6,165 credits	1.3 credits

Timeline Analytics

View usage patterns with flexible time controls:

Date Range Selection:

Today / Yesterday
Last 7 days / Last 30 days
Last 3 months / Last 6 months
Custom date range picker

Granularity Options:

By Hour - Detailed hourly breakdown (for daily/weekly views)
By Day - Daily usage patterns (for weekly/monthly views)
By Week - Weekly trends (for monthly/quarterly views)
By Month - Monthly overview (for yearly analysis)

Example Timeline View:

📈 Credit Usage Timeline - Last 30 Days (Daily)
Week 1: ████████████████ 2,850 credits
Week 2: ██████████████ 2,450 credits
Week 3: ████████████████████ 3,100 credits
Week 4: ████████████ 2,000 credits

Peak Day: March 15 (485 credits)
Peak Hour: 2-3 PM (average 65 credits/hour)
Most Active Days: Tuesday, Wednesday, Thursday

Credit Analytics

Credit Usage Reports

Track your credit consumption in detail:

Monthly Credit Report:

💰 March 2024 Credit Usage
├── Total Credits Used: 12,847 credits
├── Plan Credits Used: 15,000 (from Team Plan)
├── Additional Credits Used: 2,847 (from credit pack)
├── Average Credits per Prompt: 1.85 credits
└── Breakdown by Model Multiplier:
    ├── Premium Models (2x-5x): 8,250 credits (64%)
    ├── Standard Models (1x): 3,120 credits (24%)
    ├── Economy Models (0.1x-0.5x): 1,477 credits (12%)
    └── Credits Remaining: 2,153 credits

Credit Trends:

Daily credit consumption patterns
Weekly credit usage comparisons
Monthly credit budget tracking
Credits per user (organizations)
Model efficiency analysis

Budget Management

Credit Monitoring:

Set monthly credit usage limits
Track consumption against allocation
Usage alerts at 75%, 90%, and 100%
Automatic credit usage reports

Cost Optimization Insights:

Most credit-efficient models for your use cases
Users with highest/lowest credit efficiency
Peak usage times and credit impact
Recommendations for reducing credit consumption

🎯 Credit Optimization Recommendations
├── Switch to Llama 3.3 70B (1x) instead of GPT-4o (2x) for analysis tasks
├── Use Claude 3 Haiku (0.5x) for simple rewrites instead of Claude 3.7 (2.5x)
├── Schedule heavy processing during off-peak hours
└── Potential monthly savings: 2,500 credits (17%)

Performance Analytics

Response Time Monitoring

Track how fast your prompts execute:

Response Time Metrics:

⚡ Prompt Response Times
├── Average Response Time: 2.3 seconds
├── Fastest Model: Claude 3 Haiku (0.8s avg)
├── Slowest Model: o3 mini (4.1s avg)
└── Performance by Time:
    ├── Peak Hours (9AM-5PM): 2.8s avg
    ├── Off-Peak Hours: 1.9s avg
    └── Weekend: 1.5s avg

Response Time Tracking:

Real-time response time display
Historical response time trends
Model-specific performance data
User-specific response times
Time-of-day performance patterns

Model Performance Comparison

Compare different models for your use cases:

Model	Avg Response Time	Success Rate	Credits per Prompt	User Rating
Claude 3.7 Sonnet (2.5x)	1.8s	98.5%	2.5 credits	4.8/5
GPT-4o (2x)	3.1s	97.2%	2.0 credits	4.7/5
GPT-4 Turbo (1x)	2.4s	96.8%	1.0 credits	4.5/5
Llama 3.3 70B (1x)	3.2s	95.1%	1.0 credits	4.3/5
Claude 3 Haiku (0.5x)	0.8s	94.2%	0.5 credits	4.2/5

Credit Insights

Peak Usage Analysis

Understand when your team uses credits most:

Daily Patterns:

Peak hours: 10 AM - 12 PM, 2 PM - 4 PM
Low usage: Early morning, late evening
Weekend usage: 20% of weekday volume

Weekly Patterns:

Highest: Tuesday, Wednesday, Thursday
Lowest: Friday afternoon, Monday morning
Weekend: Research and planning tasks

Popular Use Cases by Credit Consumption

See what your team uses credits for most:

Email Writing & Communication (28% of credits) - Mostly 1x models
Content Creation & Editing (22% of credits) - Mix of 1x-2.5x models
Data Analysis & Summarization (18% of credits) - Mostly 1x models
Code Development & Review (15% of credits) - 1x-2x models
Complex Research Tasks (12% of credits) - 2x-5x models
Other Tasks (5% of credits) - Various models

Credit Efficiency by Task Type

Most Credit-Efficient Workflows:

🏆 Credit Efficiency Leaderboard
├── Email Templates (Claude 3 Haiku): 0.5 credits/prompt
├── Data Summaries (GPT-4 Turbo): 1.0 credits/prompt
├── Code Reviews (Llama 3.3): 1.0 credits/prompt
├── Content Creation (Claude 3.5): 1.0 credits/prompt
└── Complex Analysis (Claude 3.7): 2.5 credits/prompt

Reporting Features

Automated Reports

Daily Reports:

Yesterday’s credit usage summary
Cost breakdown by model multiplier
Top users and models
Performance highlights

Weekly Reports:

7-day credit usage trends
Credit efficiency analysis
Team productivity insights
Model performance comparison

Monthly Reports:

Complete credit analytics
Budget analysis and remaining credits
ROI assessment
Credit optimization recommendations

Export Options

Data Export Formats:

CSV for spreadsheet analysis
PDF for executive reports
JSON for technical integration
Dashboard screenshots

Report Scheduling:

Daily credit summaries
Weekly team reports
Monthly executive briefings
Custom report intervals

Credit Optimization Tools

Smart Model Selection

AI-Powered Recommendations:

Suggest optimal models for specific tasks
Balance quality and credit cost
Learn from your usage patterns
Provide model switching suggestions

Example Optimization Alert:

💡 Smart Suggestion
For your "Email Response" prompts, consider switching from
GPT-4o (2x credits) to Claude 3.5 Sonnet (1x credits).
Based on similar prompts, quality remains high while
saving 50% credits. Potential monthly savings: 850 credits.

Credit Budgeting

Advanced Budget Controls:

Department-level credit allocation
User-specific credit limits
Project-based credit tracking
Automatic credit purchasing when limits reached

Budget Dashboard:

📊 March Credit Budget Status
├── Total Budget: 20,000 credits
├── Used: 15,230 credits (76%)
├── Remaining: 4,770 credits (24%)
├── Projected End-of-Month: 19,500 credits
└── Status: ✅ On track

Getting Started with Analytics

Setting Up Credit Analytics

Access Your Dashboard
- Navigate to Analytics from the main menu
- View your credit usage overview immediately
Customize Your View
- Select date range and granularity
- Filter by models or users
- Set up credit tracking preferences
Monitor Your Usage
- Check credit consumption patterns
- Track model efficiency
- Monitor team credit usage

Best Practices

Credit Optimization:

Review monthly credit reports
Identify most efficient models for your tasks
Monitor user credit consumption patterns
Set appropriate budget limits

Performance Monitoring:

Track response times during different periods
Compare model performance for similar tasks
Optimize prompt timing for faster responses
Monitor success rates across models

Smart Usage:

Use economy models (0.1x-0.5x) for simple tasks
Reserve premium models (2x-5x) for complex analysis
Consider model switching recommendations
Monitor credit efficiency by task type

Ready to optimize your AI credit usage and costs? Start exploring your analytics dashboard today!