• 1. About this Book
  • 2. 10 Reasons why Ecommerce Businesses Need to Have Google Analytics Set Up Correctly
  • 3. Quick Overview of Your Google Analytics Admin - Before You Set Up Your Ecommerce
  • 4. Setting Up Your “All Web Site Data” View in Google Analytics
  • 5. What the Heck are Parameters... And What do I do with the "Exclude Query Parameters" Field in Google Analytics?
  • 6. Adding Filtered Google Analytics Views Gives You Access to Better Marketing Data
  • 7. Setting up an “Include My Domain” Filter in Google Analytics
  • 8. Using Google Analytics Filters to Rid Yourself of Rage-Inducing Referral Spam
  • 9. Formulating Your IP Address Filter in Google Analytics
  • 10. Ensuring that Your Google Analytics Data is Accurate by Applying Lowercase Filters
  • 11. How to Remove Slashes From The End of your URLs in Google Analytics
  • 12. Fixing the Problem of Parameters in your Ecommerce URLS in Google Analytics
  • 13. Acquiring Your Ecommerce Store’s Unique Parameter List for Google Analytics
  • 14. How to Turn your Ecommerce Parameters into Custom Dimensions in Google Analytics
  • 15. Using your Parameter Custom Dimensions to Discover Ecommerce Opportunities
  • 16. Key Google Analytics Settings You Might Have Overlooked for your Ecommerce Configuration
  • 17. What are the Google Analytics Ecommerce Settings For and How are They Set Up?
  • 18. How to Turn on Ecommerce Tracking in Google Analytics
  • 19. Google Analytics Enhanced Ecommerce on popular Ecommerce Platforms
  • 20. Manually Adding Google Analytics Standard Ecommerce Transaction Tracking Code
  • 21. Manually Adding Google Analytics Enhanced Ecommerce Transaction Tracking Code
  • 22. Implementing Enhanced Ecommerce Features to Collect Game Changing Data For Your Ecommerce Store
  • 23. How Do You Use the Ecommerce Reports Built into Google Analytics?
  • 24. What is the Google Analytics Ecommerce Overview Report and What Should You Use It For?
  • 25. What is the Shopping Behavior Report and What Should You Use It For?
  • 26. The Importance of the Checkout Behavior Report in Google Analytics
  • 27. What is the Product Performance Report Used for in Google Analytics?
  • 28. This post has been deleted
  • 29. How can you see Individual Ecommerce Transactions in Google Analytics?
  • 30. What is the Time to Purchase Report in Google Analytics Used For?
  • 31. Deep-dive your Product Sales with the Google Analytics Product List Report
  • 32. Setting Ecommerce Goals in Google Analytics and Why This is So Important
  • 33. Adding Your Ecommerce Goals to Google Analytics
  • 34. Using Google Analytics Goals to Boost Your Ecommerce Conversion Rate
  • 35. Using the Model Comparison Tool in Google Analytics
  • 36. Segmenting Users - A Powerful Tool for Providing Data Insights
  • 37. Building Segments Using the Shopping Behavior Report
  • 38. How to Use the Segment Builder in Google Analytics
  • 39. How to Build Specific Criteria using Google Analytics' Segment Builder
  • 40. Google Analytics Segment Examples to Enhance Your Ecommerce Sales
  • 41. How to use Segmentation Analysis to Identify Opportunities and Increase Conversion
  • 42. Making the Most of the Demographics of Users When Looking at Ecommerce Data
  • 43. Google Analytics Segmentation Example - Transacted vs Did Not Transact
  • 44. Taking your Segmentation Analysis Further
  • 45. Bonus: Six Reasons Why Your Ecommerce Store Needs Google Tag Manager
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    Google Analytics Segment Examples

    Google Analytics Segment Examples to Enhance Your Ecommerce Sales

    As we continue our detailed look at segmentation in Google Analytics, this latest article will help you to build specific segment recipes that you can create and reuse. These examples can help you to compare key audiences to each other in order to find differences that can drive your profitability.

    You can see up to four different segments at the same time in Google Analytics. These can be plotted against each other in graphs or used to read different results as individual rows in tables.

    Note: These examples assumes you are using Enhanced Ecommerce. If you are using Standard Ecommerce you would need to adjust your segments slightly – for example you could use page depth or events to indicate engagement or particular stages in the sales pipeline.

    Now onto the recipes.

    Users who abandoned because they weren’t interested

    For this segment we will identify all users who were not interested enough to look at a product listing. We could choose to include or exclude this group of users in our segment, or create one segment of each condition and compare them.

    To create this segment we use Advanced Conditions and set the conditions:

    Filter Users Include Product List Views per user = 0

    AND Transactions per user = 0

    You can see these settings depicted in the image below:

    Users who were interested but did not buy anything

    For this segment we will identify all users who were interested enough to look at a product listing, but did not ultimately complete their transactions.

    To create this segment we use Advanced Conditions and set the conditions:

    Filter Users Include Product List Views per user > 0

    AND Transactions per user = 0.

    You can see these settings displayed in the image below:

    Users who added an item to the cart

    For this segment we will identify all users who added an item to their cart.

    To create this segment we use Advanced Conditions and set the conditions:

    Filter Users Include Quantity Added To Cart per user > 0

    These relatively straightforward settings are depicted below:

    Users who added a specific product to the cart

    For this segment we will identify all users who added a specific item to their cart.

    To create this segment we use Advanced Conditions and set the conditions:

    Filter Users Include Quantity Added To Cart per user > 0

    AND Product exactly matches <product name>

    This is demonstrated in this image:

    Users who completed their purchase

    For this segment we will identify all users who completed their purchase.

    To create this segment we can choose Behavior and set the conditions:

    Transactions per user > 0.

    Again, this is shown in the image below:

    Users who specified a clothing size (or some other custom parameter)

    This segment is an example of a segment created from a custom dimension that was added for a custom parameter. You may not have the same parameter, but the concept applies to any parameter accessible through a custom dimension.

    The custom dimensions menu is shown in the following image:

    Note: The image shows Filter Sessions, but to see Users this will need to be changed to Users.

    Once you have been through the process listed here, you will have built several segments around different user audiences. This will be extremely useful in helping you to better understand your customers, and the way that your eCommerce store is working.

    In future blog posts, we will look at using these segments in order to find your best opportunities and grow your conversion rate.

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