Analyze Enhanced Ecommerce data

In this article:

Conversion Rate and Average Order Value

To track your Conversion Rate and Average Order Value, use the Ecommerce Overview report.

The scorecards below the graph provide a summary of your business with four metrics:

Ecommerce Conversion Rate and Average Order Value are especially telling:

  1. Ecommerce Conversion Rate is the percentage of visits that result in an ecommerce transaction. This value helps you assess the effectiveness of your marketing and site design. Is your marketing delivering an audience that is primed to buy, and is your site designed to make purchasing easy for those users?
    While conversion rates vary, research average conversion rates for your business vertical to find a good initial benchmark. If you already have a target conversion rate for your business, use this report to see how you’re performing against that rate. Use comparative date ranges to see how you’re trending over time (did we improve over last month, last year?).
  2. Average Order Value helps you assess how well you’re closing deals on your site. Are your product lists generating interest in multiple products? If you’re selling coats, are you also selling the hats and gloves to go with them? Are your quantity discounts encouraging users to buy in multiples?

Campaign performance

The Overview report shows how campaigns are performing in the context of your site and marketing strategy. Analytics tracks the following metrics to measure campaigns, order coupons, and affiliate marketing:

  • Transactions
  • Revenue
  • Average Order Value

You can see the aggregate performance of each component (e.g., the collective performance of your campaigns), and quickly see whether your campaigns are driving the share of business you intended.

Use the scorecards above the Marketing section to compare overall site performance to your individual marketing components:

Dig deeper into campaign performance with the Campaigns and AdWords Campaigns reports. For example, if the metric values here aren’t what you were expecting, you can check the details of individual campaigns to see where there are performance weaknesses. On the other hand, if the Overview report indicates strong campaign performance, you can check these other reports to see if the success is limited to a single campaign, or whether it’s supported more broadly by all your campaigns.

Purchase funnel performance

The Shopping Behavior Analysis report lets you evaluate the strengths and weaknesses of your purchase funnel.

This visualization lets you see the flow of users through and out of your funnel. If you notice an unusually large exodus at any point, examine that content.

If users are leaving after viewing product details and not adding items to their carts, the product descriptions might not be compelling or don’t provide the right balance of information. For example, if your audience is mainstream consumer and your product descriptions are overly technical, those details might not constitute a convincing argument. Or there could simply be a malfunction that prevents users from adding items.

If users are leaving after adding items to their carts, thye might be comparison shopping, loading up carts to see which retailer will follow up with the best incentive to complete the transaction. Compare pricing and incentives with other retailers: you have an opportunity to be the first to offer a price or incentive that distinguishes you from everyone else.

If users abandon the process at checkout, the process might be too complicated, or users might be surprised by excessively high shipping charges.

Checkout funnel performance

The Checkout Behavior Analysis report lets you evaluate the points at which users abandon your checkout process.

For example, if a lot of users leave at the first step where you require them to log in to an account, consider adding an option to checkout as a guest, or let them sign in with an existing Google or Twitter account to simplify the process.

High abandonment at any point can also signal a technical problem. For example, while you may let users sign in with a different account, you may be having problems accepting OpenID authentication. Or it could be something simple like a page taking an excessively long time to load.

If the reasons for abandonment aren’t obvious, conduct usability testing.

Product performance

Where the Overview report lets you evaluate aggregate performance, the Product Performance report lets you evaluate the performance of individual products.

This report offers two perspectives on product performance:

Summary Shopping behavior
  • Revenue generated by product
  • Quantity sold
  • Average price
  • Refund amounts
  • Cart-to-detail ratio
  • Buy-to-detail ratio
  • Product views in a list
  • Product-detail views
  • Product adds to cart
  • Product removals from cart
  • Number of times product was included in checkout
  • Unique purchases
  • Cart-to-detail ratio
  • Buy-to-detail ratio

In addition to revenue and quatity, this report shows how well your site design facilitates conversions. For example, the Shopping Behavior view shows how well products performed in the context of product lists. How often did list placement encourage users to view individual products? How well did your site design guide users to product details, add the products to shopping carts, and complete purchases?

Category and brand managers can use the Product Category and Product Brand dimensions to evaluate sales and shopping metrics in the context of their specific functions.

Product List performance

In addition to tracking the marketing that drives users to your site, you also want information about the success of your intra-site marketing, the product lists you show users to illustrate product options, related products, or the lists you use to upsell or cross-sell.

The Product List Performance report lets you see how well lists and individual products perform together.

  • Use Product List Name as the primary dimension o see data from a list perspective. For each list, you see the number of products users viewed in the list, the number of times users clicked products in the list, and the click-through rate for the list. This combination of metrics shows how well a list is performing in terms of getting products in front of users, and whether the layout, text, and graphics are encouraging users to click through to detailed information.
  • Use Product List Position as the primary dimension to see which list positions perform best.
  • Use Product as the primary dimension to see how individual products are performing in the lists in which they appear.
  • Use Product as the primary dimension and Product List Position as the secondary dimension to see how products are performing relative to their list positions. If a product in a lower position is outperforming products in higher positions, move the better-performing product to a higher position in the list.

Coupon and affiliate marketing

Analytics lets you track conversions that include product- and order-coupon codes, as well as conversions that result from affiliate marketing.

For product-coupon codes, you can see the associated:

  • Product Revenue: revenue from all products purchased with the product coupon
  • Unique Purchases: the number of unique purchases that included the product-coupon code
  • Product Revenue per Purchase: the average product revenue for each purchase that included the product-coupon code

For order-coupon and affiliate codes, you can see the associated:

  • Revenue: total revenue associated with each order-coupon or affiliate code
  • Transactions: total number of transactions associated with each order-coupon or affiliate code
  • Average Order Value: average order value for all transactions associated with each order-coupon or affiliate code

The data in the Product Coupon and Order Coupon reports give you the raw numbers for activity associated with coupon codes.

To see how effective these efforts were in the broader context of your business, use the Overview report to see how your overall numbers were affected during the times you offered and honored the coupons; for example:

  • If you offered coupons in the week preceding Mother’s Day or Memorial Day, use comparative date ranges to compare that week to the week before and the week after to see what kind of lift and drop-off you incurred.
  • If you offered coupons in one geographic region but not another, segment by region for that date range to evaluate the difference in Revenue and Transactions between regions, and see whether the coupons were effective.

Use the Affiliate Code report to see which of your affiliates are generating the highest-value conversions for you.

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