Advanced: Build Convert Experiment Reports in Looker Studio Using GA4 and BigQuery

 

Template Overview

This guide provides ready-to-use templates and step-by-step instructions to create professional Convert.com experiment analysis dashboards in Looker Studio. You'll get exact configurations, styling instructions, and a complete template you can duplicate and customize.

Template Package Contents

1. BigQuery Data Source Template
2. Dashboard Layout Template
3. Chart Configuration Templates
4. Calculated Field Templates
5. Filter Control Templates
6. Styling Guide

Part 1: Data Source Template Setup

Step 1: Create Your BigQuery Data Source

1.1. Access Data Sources

1. Go to datastudio.google.com
2. Click "Create" → "Data Source"
3. Select "BigQuery" connector
4. Choose "Custom Query" option

1.2. Copy and Customize the Template Query

-- CONVERT.COM EXPERIMENT ANALYSIS TEMPLATE
--  REQUIRED CUSTOMIZATIONS MARKED WITH YOUR_ PREFIX

WITH experiment_data AS (
  SELECT
    PARSE_DATE('%Y%m%d', event_date) AS date,
    event_timestamp,
    user_pseudo_id,
    event_name,

    -- Extract Convert.com experiment details
    REGEXP_EXTRACT(
      (SELECT value.string_value 
       FROM UNNEST(event_params) 
       WHERE key = 'exp_variant_string'), 
      r'CONV-(\d+)-\d+'
    ) AS experiment_id,

    REGEXP_EXTRACT(
      (SELECT value.string_value 
       FROM UNNEST(event_params) 
       WHERE key = 'exp_variant_string'), 
      r'CONV-\d+-(\d+)'
    ) AS variation_id,

    --  CUSTOMIZE: Replace with your actual variation IDs
    CASE 
      WHEN REGEXP_EXTRACT(
        (SELECT value.string_value 
         FROM UNNEST(event_params) 
         WHERE key = 'exp_variant_string'), 
        r'CONV-\d+-(\d+)'
      ) = 'YOUR_CONTROL_ID' THEN 'Control'
      WHEN REGEXP_EXTRACT(
        (SELECT value.string_value 
         FROM UNNEST(event_params) 
         WHERE key = 'exp_variant_string'), 
        r'CONV-\d+-(\d+)'
      ) = 'YOUR_VARIATION_A_ID' THEN 'Variation A'
      WHEN REGEXP_EXTRACT(
        (SELECT value.string_value 
         FROM UNNEST(event_params) 
         WHERE key = 'exp_variant_string'), 
        r'CONV-\d+-(\d+)'
      ) = 'YOUR_VARIATION_B_ID' THEN 'Variation B'
      ELSE 'Other'
    END AS variation_label,

    --  CUSTOMIZE: Replace with your conversion events
    CASE 
      WHEN event_name = 'experience_impression' THEN 'Impression'
      WHEN event_name IN (
        'YOUR_PRIMARY_CONVERSION',    -- e.g., 'purchase'
        'YOUR_SECONDARY_CONVERSION',  -- e.g., 'sign_up'
        'YOUR_TERTIARY_CONVERSION'    -- e.g., 'generate_lead'
      ) THEN 'Conversion'
      WHEN event_name IN (
        'YOUR_MICRO_CONVERSION_1',    -- e.g., 'add_to_cart'
        'YOUR_MICRO_CONVERSION_2'     -- e.g., 'begin_checkout'
      ) THEN 'Micro-Conversion'
      ELSE 'Other'
    END AS event_category,

    -- Revenue data
    COALESCE(
      (SELECT value.double_value FROM UNNEST(event_params) WHERE key = 'value'),
      ecommerce.purchase_revenue,
      0
    ) AS event_value,

    -- Dimensions for analysis
    device.category AS device_category,
    geo.country AS country,
    traffic_source.source AS traffic_source,
    traffic_source.medium AS traffic_medium

  --  CUSTOMIZE: Replace with your BigQuery table path
  FROM `YOUR_PROJECT.YOUR_DATASET.events_*`
  WHERE 
    _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 90 DAY)) 
    AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())
    AND (
      event_name = 'experience_impression' 
      --  CUSTOMIZE: Add your conversion events
      OR event_name IN (
        'YOUR_PRIMARY_CONVERSION',
        'YOUR_SECONDARY_CONVERSION', 
        'YOUR_TERTIARY_CONVERSION',
        'YOUR_MICRO_CONVERSION_1',
        'YOUR_MICRO_CONVERSION_2'
      )
    )
),

-- Attribution logic
user_impressions AS (
  SELECT 
    user_pseudo_id,
    experiment_id,
    variation_id,
    variation_label,
    MIN(event_timestamp) AS first_impression_time
  FROM experiment_data 
  WHERE event_category = 'Impression'
  GROUP BY 1, 2, 3, 4
)

-- Final output for Looker Studio
SELECT 
  e.date,
  e.experiment_id,
  e.variation_id,
  e.variation_label,
  e.event_category,
  e.event_name,
  e.device_category,
  e.country,
  e.traffic_source,
  e.traffic_medium,

  -- Metrics
  COUNT(*) AS total_events,
  COUNT(DISTINCT e.user_pseudo_id) AS unique_users,
  SUM(e.event_value) AS total_revenue,

  -- Attribution
  COUNT(DISTINCT CASE 
    WHEN e.event_category IN ('Conversion', 'Micro-Conversion') 
      AND e.event_timestamp >= ui.first_impression_time
    THEN e.user_pseudo_id 
  END) AS attributed_conversions,

  SUM(CASE 
    WHEN e.event_category IN ('Conversion', 'Micro-Conversion') 
      AND e.event_timestamp >= ui.first_impression_time
    THEN e.event_value 
    ELSE 0 
  END) AS attributed_revenue

FROM experiment_data e
LEFT JOIN user_impressions ui 
  ON e.user_pseudo_id = ui.user_pseudo_id 
  AND e.experiment_id = ui.experiment_id
WHERE ui.user_pseudo_id IS NOT NULL
GROUP BY 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
ORDER BY 1 DESC, 4

1.3. Data Source Configuration

• Name your data source: "Convert Experiment Data"
• Click "Connect"
• Configure field types as needed
• Click "Create Report"

---

Part 2: Dashboard Template Creation

Step 2: Set Up Dashboard Layout

2.1. Dashboard Settings

1. Canvas Size: Fixed size (1600 x 1200)
2. Theme: Custom (we'll configure colors below)
3. Title: "Convert.com Experiment Analysis Dashboard"

2.2. Create Header Section

• Position: Top of dashboard
• Height: 80px
• Background: #f8f9fa (light gray)

---

Part 3: Filter Controls Template

Step 3: Implement Filter Controls

3.1. Date Range Control

Control Type: Date range control
Position: Header section, left
Size: 200px width × 40px height
Default Value: Last 30 days
Style: 
  - Border: 1px solid #dee2e6
  - Background: white
  - Font: Google Sans, 14px

Implementation Steps:

1. Click "Add a control" → "Date range control"
2. Position in header section
3. In "Setup" tab:
   • Default date range: Last 30 days
4. In "Style" tab:
   • Border color: #dee2e6
   • Background: #ffffff

3.2. Experiment Filter

Control Type: Drop-down list
Position: Header section, center
Size: 200px width × 40px height
Control field: Experiment ID
Allow multiple selections: No

Implementation Steps:

1. "Add a control" → "Drop-down list"
2. Setup:
   • Control field: Experiment ID
   • Metric: none
   • Allow multiple selections: unchecked
3. Style: Match date range control

3.3. Variation Filter

Control Type: Multi-select dropdown
Position: Header section, right
Size: 200px width × 40px height
Control field: Variation Label

Part 4: Scorecard Templates

Step 4: Create Performance Scorecards

4.1. Control Scorecard Template

Chart Configuration:

Chart Type: Scorecard
Data Range: Your data source
Filters: Variation Label EQUALS Control
Position: Row 2, Left column
Size: 250px width × 150px height

Metrics Configuration:

Metric 1: Users Exposed
  - Field: Unique Users
  - Filter: Event Category = "Impression"
  - Aggregation: Count Distinct
  - Format: Number, no decimals

Metric 2: Conversions  
  - Field: Attributed Conversions
  - Aggregation: Sum
  - Format: Number, no decimals

Metric 3: Conversion Rate
  - Calculation: (Attributed Conversions / Users Exposed) * 100
  - Format: Percentage, 2 decimals

Styling:

Border: 2px solid #1f77b4 (blue for control)
Background: #f8f9ff
Font: Google Sans
Primary metric size: 36px
Label size: 14px

Implementation Steps:

1. Add chart → Scorecard
2. Setup tab:
   • Metric: Unique Users
   • Filter: Variation Label = "Control" AND Event Category = "Impression"
3. Style tab:
   • Border: 2px solid #1f77b4
   • Background: #f8f9ff
   • Number color: #1f77b4
4. Duplicate for additional metrics

4.2. Variation A Scorecard Template

Same configuration as Control, but:

Filter: Variation Label EQUALS Variation A
Border color: #ff7f0e (orange)
Background: #fff8f0
Number color: #ff7f0e

4.3. Statistical Summary Scorecard

Chart Type: Scorecard  
Metrics: Calculated fields for uplift
Position: Row 2, Right column
Size: 300px width × 150px height

Part 5: Chart Templates

Step 5: Performance Trends Chart

5.1. Daily Trend Char

Configuration:

Chart Type: Time series (line chart)
Position: Row 3, full width
Size: 1500px width × 300px height

Setup:

Date Range Dimension: Date
Breakdown Dimension: Variation Label
Metrics: 
  - Conversion Rate (calculated field)
  - Revenue per User (calculated field)
Sort: Date ascending
Secondary axis: Revenue per User

Styling:

Control line: #1f77b4, 3px thickness
Variation A line: #ff7f0e, 3px thickness  
Variation B line: #2ca02c, 3px thickness
Grid lines: #e9ecef
Background: white
Legend position: Bottom

Implementation:

1. Add chart → Time series chart
2. Setup:
   • Date range dimension: Date
   • Breakdown dimension: Variation Label
   • Metric: Create calculated field for conversion rate
3. Style:
   • Series colors: Set as specified above
   • Reference lines: Add if needed

Step 6: Conversion Funnel Template

6.1. Funnel Chart Configuration

Chart Type: Stepped area chart
Position: Row 4, Left column  
Size: 500px width × 400px height

Setup:

Dimension: Event Category
Breakdown: Variation Label
Metric: Unique Users
Sort: Custom order (Impression, Micro-Conversion, Conversion)

Custom Sort Order Implementation:

• Create calculated field:

CASE 
  WHEN Event Category = "Impression" THEN 1
  WHEN Event Category = "Micro-Conversion" THEN 2  
  WHEN Event Category = "Conversion" THEN 3
  ELSE 4
END

Step 7: Device Performance Chart

7.1. Device Analysis Template

Chart Type: Grouped bar chart
Position: Row 4, Center column
Size: 400px width × 400px height

Configuration:

Dimension: Device Category
Breakdown: Variation Label  
Metrics:
  - Conversion Rate
  - Revenue per User
Sort: Total users (descending)

Step 8: Geographic Analysis

8.1. World Map Template

Chart Type: Geo chart (World map)
Position: Row 4, Right column
Size: 400px width × 400px height

Setup:

Geographic dimension: Country
Color metric: Conversion Rate
Size metric: Users Exposed (optional)
Color scale: Blue to red gradient

Step 9: Data Table Template

9.1. Detailed Analysis Table

Chart Type: Table
Position: Row 5, full width
Size: 1500px width × 400px height

Columns Configuration:

1. Date (Date format)
2. Variation Label (Text)
3. Event Category (Text)  
4. Device Category (Text)
5. Users (Number, no decimals)
6. Conversions (Number, no decimals)
7. Conversion Rate (Percentage, 2 decimals)
8. Revenue (Currency, 2 decimals)
9. Revenue per User (Currency, 2 decimals)

Table Settings:

Rows per page: 50
Enable search: Yes
Enable export: Yes
Show summary row: Yes
Conditional formatting: Yes (highlight top performers)

Part 6: Calculated Fields Templates

Step 10: Essential Calculated Fields

10.1. Conversion Rate Calculation

Field Name: Conversion Rate
Formula: (Attributed Conversions / CASE WHEN Unique Users = 0 THEN 1 ELSE Unique Users END) * 100
Type: Number
Default Aggregation: Auto

Implementation:

1. In data source, click "Add a field"
2. Name: "Conversion Rate"
3. Formula: As above
4. Save

10.2. Revenue per User

Field Name: Revenue per User
Formula: Total Revenue / CASE WHEN Unique Users = 0 THEN 1 ELSE Unique Users END
Type: Number (Currency)
Default Aggregation: Auto

10.3. Uplift Percentage

Field Name: Uplift vs Control
Formula: 
  CASE 
    WHEN Variation Label = "Control" THEN 0
    ELSE (Conversion Rate - AVG(CASE WHEN Variation Label = "Control" THEN Conversion Rate END)) / 
         AVG(CASE WHEN Variation Label = "Control" THEN Conversion Rate END) * 100
  END
Type: Number (Percentage)

10.4. Statistical Significance

Field Name: Significance Level
Formula: 
  CASE
    WHEN Unique Users >= 1000 AND ABS(Uplift vs Control) >= 10 THEN "High Confidence"
    WHEN Unique Users >= 500 AND ABS(Uplift vs Control) >= 15 THEN "Medium Confidence"  
    WHEN Unique Users >= 100 THEN "Low Confidence"
    ELSE "Insufficient Data"
  END
Type: Text

Part 7: Styling Template

Step 11: Consistent Styling Guide

11.1. Color Palette

Primary Colors:
- Control: #1f77b4 (Blue)
- Variation A: #ff7f0e (Orange)  
- Variation B: #2ca02c (Green)
- Variation C: #d62728 (Red)

Background Colors:
- Dashboard: #ffffff (White)
- Chart backgrounds: #ffffff
- Header: #f8f9fa (Light gray)
- Control sections: #f8f9ff (Light blue)
- Variation sections: #fff8f0 (Light orange)

Text Colors:
- Primary: #212529 (Dark gray)
- Secondary: #6c757d (Medium gray) 
- Success: #28a745 (Green)
- Warning: #ffc107 (Yellow)
- Danger: #dc3545 (Red)

Border Colors:
- Default: #dee2e6 (Light gray)
- Control: #1f77b4 (Blue)
- Variation: #ff7f0e (Orange)

11.2. Typography Settings

Font Family: Google Sans (primary), Roboto (fallback)

Font Sizes:
- Dashboard title: 24px, Bold
- Section headers: 18px, Bold  
- Chart titles: 16px, Bold
- Metric values: 36px, Bold
- Metric labels: 14px, Normal
- Table headers: 14px, Bold
- Table data: 12px, Normal
- Filters: 14px, Normal

11.3. Spacing Guidelines

Margins:
- Dashboard margins: 20px
- Between sections: 30px
- Between charts: 20px
- Chart internal padding: 15px

Chart Dimensions:
- Scorecard: 250px × 150px
- Trend chart: 1500px × 300px
- Funnel chart: 500px × 400px
- Device chart: 400px × 400px  
- Geo chart: 400px × 400px
- Data table: 1500px × 400px

Part 8: Template Implementation Checklist

Step 12: Complete Implementation Guide

12.1. Pre-Implementation Checklist

• [ ] Verify GA4 BigQuery Export is Active

-- Test query to verify data
SELECT COUNT(*) as total_events
FROM `YOUR_PROJECT.analytics_XXXXXX.events_*`
WHERE _TABLE_SUFFIX = FORMAT_DATE('%Y%m%d', CURRENT_DATE())

• [ ] Identify your event names

-- Get list of your events
SELECT event_name, COUNT(*) as event_count
FROM `YOUR_PROJECT.analytics_XXXXXX.events_*`
WHERE _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY)) 
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())
GROUP BY 1
ORDER BY 2 DESC

• [ ] Get your variation IDs from Convert.com
• [ ] Confirm BigQuery permissions
• [ ] Plan dashboard sharing strategy

12.2. Implementation Steps

1. Create Data Source (30 minutes)
   • [ ] Copy and customize BigQuery query
   • [ ] Replace all YOUR_ placeholders
   • [ ] Test query execution
   • [ ] Configure field types
   • [ ] Save data source
2. Build Dashboard Framework (45 minutes)
   • [ ] Create new report
   • [ ] Set canvas size and theme
   • [ ] Add header section
   • [ ] Implement filter controls
   • [ ] Test filter functionality
3. Create Core Charts (60 minutes)
   • [ ] Build Control scorecard
   • [ ] Build Variation A scorecard
   • [ ] Create statistical summary
   • [ ] Add performance trend chart
   • [ ] Implement funnel analysis
4. Add Supporting Charts (45 minutes)
   • [ ] Device performance chart
   • [ ] Geographic analysis
   • [ ] Traffic source breakdown
   • [ ] Detailed data table
5. Configure Calculated Fields (30 minutes)
   • [ ] Conversion rate calculation
   • [ ] Revenue per user
   • [ ] Uplift percentage
   • [ ] Statistical significance
6. Apply Styling (30 minutes)
   • [ ] Color scheme implementation
   • [ ] Typography consistency
   • [ ] Spacing optimization
   • [ ] Mobile responsiveness test

12.3. Testing Checklist

• [ ] Data Validation
  • Compare dashboard totals with GA4
  • Verify attribution logic
  • Check filter interactions
  • Test date range changes
• [ ] Performance Testing
  • Load with maximum date range
  • Test with multiple simultaneous users
  • Verify mobile responsiveness
  • Check loading times
• [ ] User Acceptance Testing
  • Share with stakeholders for feedback
  • Test with different permission levels
  • Verify export functionality
  • Confirm scheduled reports work

12.4. Launch Checklist

• [ ] Documentation
  • Create user guide
  • Document customization instructions
  • Establish maintenance schedule
  • Plan training sessions
• [ ] Access Management
  • Configure viewer permissions
  • Set up editor access
  • Establish owner hierarchy
  • Plan access review schedule
• [ ] Monitoring Setup
  • Schedule regular data quality checks
  • Set up performance alerts
  • Plan monthly optimization reviews
  • Establish feedback collection process

Part 9: Customization Templates

Step 13: Industry-Specific Customizations

13.1. E-commerce Template Additions

-- Add to main query for e-commerce metrics
SELECT
  ...,
  -- Product data
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'item_category') as product_category,
  (SELECT value.int64_value FROM UNNEST(event_params) WHERE key = 'quantity') as quantity,

  -- Enhanced e-commerce events
  CASE 
    WHEN event_name = 'purchase' THEN 'Purchase'
    WHEN event_name = 'add_to_cart' THEN 'Add to Cart'
    WHEN event_name = 'begin_checkout' THEN 'Begin Checkout'
    WHEN event_name = 'view_item' THEN 'Product View'
  END as ecommerce_action

Additional Charts for E-commerce:

• Product Performance by Variation
• Shopping Funnel Analysis
• Average Order Value Comparison
• Cart Abandonment Rates

13.2. SaaS Template Additions

-- SaaS-specific metrics
SELECT
  ...,
  -- Subscription data
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'subscription_type') as plan_type,
  (SELECT value.int64_value FROM UNNEST(event_params) WHERE key = 'trial_days') as trial_length,

  -- SaaS events
  CASE 
    WHEN event_name = 'trial_start' THEN 'Trial Started'
    WHEN event_name = 'subscription_purchase' THEN 'Converted to Paid'
    WHEN event_name = 'feature_engagement' THEN 'Feature Usage'
  END as saas_action

13.3. Lead Generation Template

-- Lead gen specific metrics
SELECT
  ...,
  -- Lead data
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'form_name') as form_name,
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'lead_source') as lead_source,

  -- Lead events
  CASE 
    WHEN event_name = 'generate_lead' THEN 'Lead Generated'
    WHEN event_name = 'contact_form_submit' THEN 'Contact Form'
    WHEN event_name = 'newsletter_signup' THEN 'Newsletter'
  END as lead_action

Part 10: Template Sharing and Collaboration

Step 14: Template Distribution

14.1. Creating Shareable Template

1. Prepare Template for Sharing:
   • [ ] Remove all real data (use sample data)
   • [ ] Replace specific IDs with placeholders
   • [ ] Add instruction annotations
   • [ ] Test with sample BigQuery data
2. Create Template Copy Link:
   • [ ] Open dashboard
   • [ ] Click "Share" → "Make a copy"
   • [ ] Generate shareable link
   • [ ] Test link access

14.2. Template Documentation

Create accompanying documentation:

# Convert.com Dashboard Template - Setup Guide

## Prerequisites
- GA4 BigQuery Export enabled
- Convert.com experiments running
- Looker Studio access

## Customization Required
1. BigQuery table path: Line 45 in data source
2. Variation IDs: Lines 28-35 in data source  
3. Event names: Lines 40-50 in data source
4. Color scheme: Dashboard style settings

## Support
- Email: your-analytics-team@company.com
- Documentation: link-to-your-docs
- Training: link-to-training-schedule

Part 11: Troubleshooting Template

Step 15: Common Issues and Solutions

15.1. Data Issues Template

-- Diagnostic queries for troubleshooting

-- Check if Convert.com events exist
SELECT 
  event_date,
  COUNT(*) as impression_events
FROM `YOUR_PROJECT.analytics_XXXXXX.events_*`
WHERE event_name = 'experience_impression'
AND _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY)) 
AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())
GROUP BY 1
ORDER BY 1 DESC;

-- Verify variation ID extraction
SELECT 
  (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'exp_variant_string') as raw_string,
  REGEXP_EXTRACT(
    (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'exp_variant_string'), 
    r'CONV-\d+-(\d+)'
  ) AS extracted_variation_id
FROM `YOUR_PROJECT.analytics_XXXXXX.events_*`
WHERE event_name = 'experience_impression'
LIMIT 10;

-- Check conversion event coverage
SELECT 
  event_name,
  COUNT(*) as event_count,
  COUNT(DISTINCT user_pseudo_id) as unique_users
FROM `YOUR_PROJECT.analytics_XXXXXX.events_*`
WHERE event_name IN ('YOUR_CONVERSION_EVENTS')
AND _TABLE_SUFFIX = FORMAT_DATE('%Y%m%d', CURRENT_DATE())
GROUP BY 1;

15.2. Performance Issues Template

Issue: Slow Dashboard Loading

-- Optimized query template for large datasets
-- Add to your main query:
WHERE 
  _TABLE_SUFFIX BETWEEN FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)) 
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())  -- Limit to 30 days
  AND event_name IN ('experience_impression', 'YOUR_KEY_EVENTS_ONLY')  -- Limit events

Chart Optimization Settings:

• Maximum rows displayed: 1000
• Enable data sampling: For > 500K rows
• Use extract data: For historical reports

15.3. Access Issues Template

Permission Setup Checklist:

• [ ] BigQuery dataset access
• [ ] Looker Studio sharing permissions
• [ ] Data source permissions
• [ ] Dashboard viewing rights

Template Summary

This comprehensive template package provides:

• Complete BigQuery data source with customization points clearly marked
• Step-by-step dashboard creation with exact specifications
• Ready-to-use chart configurations with styling details
• Calculated field templates for key metrics
• Color schemes and typography guidelines
• Implementation checklist for structured rollout
• Troubleshooting guides for common issues
• Industry customizations for specific business types
• Sharing and collaboration templates

Total Implementation Time: ~4 hours

• Data source setup: 30 min
• Dashboard creation: 3 hours
• Testing and refinement: 30 min

Template Benefits:

• Immediate deployment with minimal customization
• Professional appearance with consistent styling
• Comprehensive analysis covering all key metrics
• Scalable framework for multiple experiments
• Cost-effective solution using free Google tools

By following this template guide, you'll have a production-ready Convert.com analysis dashboard that rivals expensive specialized platforms, all built on free Google infrastructure with professional-grade functionality and appearance.