Analytics for e-commerce: What to track and why

E-commerce analytics goes beyond pageviews. Understanding how visitors become customers requires tracking the right metrics at each stage of the buying journey.

The e-commerce [funnel](/glossary/funnel)

Every purchase follows a path:

1. Awareness: Visitor lands on your site
2. Interest: They browse products
3. Consideration: They view specific product pages
4. Intent: They add items to cart
5. Purchase: They complete checkout

Analytics helps you understand where customers drop off and why.

Essential metrics for online stores

Traffic metrics

Visitors by source: Know where your customers come from.

• Organic search visitors often have high purchase intent
• Social traffic might browse more but convert less
• Email subscribers typically convert at higher rates
• Paid traffic ROI depends on your ad targeting

New vs returning visitors: Returning visitors convert at 2-3x the rate of new visitors. Track this ratio to understand customer loyalty.

Engagement metrics

Product page views: Which products get attention? High views with low add-to-cart rates suggest pricing or description problems.

Time on product pages: Longer time often indicates serious consideration. Very short times might mean the page doesn't match expectations.

Search queries: What do visitors search for on your site? This reveals demand you might not be meeting.

Conversion metrics

Add-to-cart rate: Percentage of visitors who add items to cart. Industry average is 5-10%. Below 5% suggests product page problems.

Cart abandonment rate: Percentage who add to cart but don't purchase. Average is 70%. High rates indicate checkout friction.

[Conversion rate](/glossary/conversion-rate): Percentage of visitors who complete a purchase. E-commerce average is 2-3%. Top performers hit 5%+.

Revenue metrics

Average order value (AOV): Total revenue divided by number of orders. Increasing AOV is often easier than increasing traffic.

Revenue per visitor: Total revenue divided by total visitors. This combines conversion rate and AOV into one metric.

Customer lifetime value: How much a customer spends over their entire relationship with you. Essential for understanding true marketing ROI.

Setting up e-commerce tracking

Track key events

Configure your analytics to capture:

• Product views: Which items get seen
• Add to cart: What gets selected
• Remove from cart: What gets reconsidered
• Begin checkout: Who starts the process
• Purchase complete: Who finishes

With Glyphex, use custom events to track these actions:

// Track add to cart
glyphex.track('add_to_cart', {
  product_id: 'SKU123',
  product_name: 'Blue Widget',
  price: 29.99
});

// Track purchase
glyphex.track('purchase', {
  order_id: 'ORD456',
  total: 89.97,
  items: 3
});

Create a conversion funnel

Set up a funnel to visualize drop-off at each stage:

1. Homepage or landing page
2. Category page
3. Product page
4. Cart page
5. Checkout
6. Order confirmation

Identify where the biggest drops occur. That's where to focus optimization efforts.

Analyzing product performance

Top performers

Identify products with:

• Highest view-to-cart ratio
• Best conversion rates
• Highest revenue contribution

These are your winners. Feature them prominently, ensure they're always in stock, and study what makes them successful.

Underperformers

Look for products with:

• High views but low add-to-cart (pricing or description issue)
• High add-to-cart but low purchase (checkout friction)
• Low views despite good conversion (visibility problem)

Each pattern suggests a different fix.

Optimizing the checkout flow

Checkout is where sales are won or lost. Track:

Exit points

Where do people abandon checkout? Common culprits:

• Shipping cost reveal: Unexpected costs cause 48% of abandonments
• Account creation required: 24% abandon when forced to register
• Complex forms: Every extra field reduces completions
• Payment options: Missing preferred payment method loses sales

Checkout completion time

How long does checkout take? Faster is better. Identify steps that take longest and simplify them.

Error rates

How often do form errors occur? Which fields cause problems? Fix confusing labels and validation issues.

Traffic source analysis for e-commerce

Not all traffic is equal. Analyze by source:

Organic search

• Which keywords drive purchases (not just visits)?
• Which product pages rank well?
• What's the conversion rate from organic traffic?

Paid advertising

• Cost per acquisition by campaign
• Return on ad spend (ROAS)
• Which ad creatives drive sales?

Email marketing

• Revenue per email sent
• Conversion rate from email traffic
• Which email types drive most sales?

Social media

• Which platforms send buying traffic?
• Social conversion rate vs site average
• Impact of social proof on conversions

Seasonal and trend analysis

E-commerce has patterns. Track:

Day of week

When do people buy? Schedule promotions and email sends accordingly.

Time of day

Peak shopping hours vary by audience. Time-sensitive offers should align with when your customers are active.

Seasonal trends

Compare year-over-year to understand:

• Holiday shopping patterns
• Seasonal product demand
• Impact of annual promotions

Mobile commerce tracking

Mobile shopping continues to grow. Track mobile separately:

• Mobile vs desktop conversion rates
• Mobile cart abandonment rate
• Mobile checkout completion rate

If mobile converts significantly worse, prioritize mobile UX improvements.

Using data to increase revenue

Increase conversion rate

• Simplify checkout process
• Add trust signals (reviews, security badges)
• Improve product photography
• Write better product descriptions
• Offer guest checkout

Increase average order value

• Product recommendations ("Customers also bought")
• Bundle deals
• Free shipping thresholds
• Upsells at checkout
• Volume discounts

Increase traffic quality

• Focus ad spend on high-converting audiences
• Optimize for purchase-intent keywords
• Build email list for repeat customers
• Retarget cart abandoners

Weekly e-commerce review

Build a regular analytics routine:

1. Revenue and orders: Up or down from last week?
2. Conversion rate: Any significant changes?
3. Top traffic sources: What's driving sales?
4. Best/worst products: Any surprises?
5. Cart abandonment: Higher or lower than usual?

Consistent monitoring catches problems early and reveals opportunities quickly.

Start with what matters most

You can't optimize everything at once. Start with:

1. Conversion rate: The highest-leverage metric
2. Cart abandonment: Often the biggest leak
3. Top product performance: Protect your winners

Build from there as you develop your analytics practice.