Conversion Funnel Deep Analysis

What This Sidekick Query Does

Perform a deep conversion funnel analysis for my Shopify store to identify where visitors drop off and how to improve each stage.

Store Information:

  Store URL: [YOUR_STORE_URL]
  Industry/niche: [YOUR_NICHE, e.g., fashion, electronics, beauty]
  Monthly sessions: [MONTHLY_SESSIONS, e.g., 50000]
  Current overall conversion rate: [CONVERSION_RATE, e.g., 2.1%]
  Average order value: [AOV, e.g., $65]
  Analysis period: [TIME_PERIOD, e.g., last 90 days]


Funnel Stages to Analyze:


  Awareness to Landing (Top of Funnel):
    
      Sessions by traffic source and landing page category
      Bounce rate by traffic source and device type
      Landing page load time impact on bounce rate
      Expected benchmark bounce rates for [YOUR_NICHE] stores
    
  
  Landing to Product View:
    
      Percentage of sessions that view at least one product page
      Navigation paths from landing pages to product pages
      Collection page engagement rate and click-through to products
      Search usage rate and search-to-product-view conversion
    
  
  Product View to Add-to-Cart:
    
      Add-to-cart rate overall and by product category
      Product page engagement metrics (scroll depth, time on page)
      Impact of product images, reviews, and pricing on cart additions
      Comparison of add-to-cart rates: desktop vs mobile vs tablet
    
  
  Add-to-Cart to Checkout Initiation:
    
      Cart abandonment rate before checkout begins
      Average time between add-to-cart and checkout start
      Cart page drop-off reasons (shipping cost reveal, no guest checkout)
      Impact of cart value on checkout initiation rate
    
  
  Checkout Initiation to Purchase:
    
      Checkout completion rate by step (information, shipping, payment)
      Drop-off rate at each checkout step
      Impact of payment methods offered on completion rate
      Checkout errors and their frequency
    
  
  Overall Funnel Metrics:
    
      Calculate the conversion rate between each stage
      Identify the single biggest drop-off point with estimated revenue impact
      Compare funnel performance: [TIME_PERIOD] vs previous period
      Segment funnel by device type, traffic source, and new vs returning visitors
    
  


Optimization Recommendations:
For each stage with significant drop-off, provide:

  The specific problem identified from the data
  Three concrete actions to reduce drop-off at that stage
  Expected improvement range based on industry benchmarks
  Priority ranking (high/medium/low) based on potential revenue impact


Calculate the estimated monthly revenue increase if each drop-off point improved by [TARGET_IMPROVEMENT, e.g., 10]%.

Expected Output

Tips to Improve Results