Real-Time Data Integration
Funnel Architect pulls actual performance data from:
Meta Ads - Link clicks, landing page views
Shopify - Add to cart, checkout, purchase events
Automatically synced - Always showing current data
Interactive Visualization
The funnel chart displays:
Visual flow - See your funnel at a glance
Conversion rates - Percentage at each stage
Actual counts - Real numbers of users
Color-coded stages - Quick health assessment
Green: Healthy conversion rate
Yellow: Needs attention
Red: Critical issue
Display Modes
Choose how to view your data:
Sum - Total numbers across selected timeframe
See aggregate performance
Good for campaign analysis
Shows total impact
Average - Average performance per day
Smooth out day-to-day variance
Better for trend analysis
More stable metrics
Percentage - Conversion rates between stages
Focus on efficiency
Compare stage performance
Identify bottlenecks
Timeframe Selection
Analyze different periods:
Last 7 days
Last 14 days
Last 30 days
Last 90 days
Custom date range
Segmentation
Break down performance by:
All Users - Complete view
Mobile vs Desktop - Device-specific insights
New vs Returning - Customer type analysis
Persona A vs Persona B - Audience segment comparison
Simulation Mode
Test potential improvements before implementing:
Adjust Sliders - Move conversion rates up or down
See Impact - Watch how changes flow through funnel
Calculate ROI - Understand potential revenue impact
Plan Changes - Prioritize optimization efforts
Example: Improve landing page rate from 72% to 80% → See how many more purchases you'd get
Issue Diagnosis
Funnel Architect automatically identifies problems:
Scroll Depth Metrics
P50 and P90 scroll depth
Indicates content engagement
Shows if users see key information
Time on Page
Average session duration
Engagement indicator
Attention quality measure
Bounce Rate
Single-page sessions
Landing page effectiveness
First impression impact
Error Rate
Technical issues per 100 sessions
User experience problems
Friction points
AI-Powered Fixes
For each issue, get specific recommendations:
What to fix - Exact problem area
How to fix it - Actionable steps
Expected lift - Predicted improvement
Implementation guide - Detailed instructions