• 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 Parameter Custom Dimensions

    Using your Parameter Custom Dimensions to Discover Ecommerce Opportunities

    Google Analytics can provide eCommerce businesses with a wealth of opportunity, but some of its best features remain unknown to the majority of users.

    One such feature that helps you better understand what is going on in your store involves storing parameters as custom dimensions and stripping them off the URLs. When you strip out the parameters from page URLs you can then know the specific number of page views for any particular page. This enables you to rank your pages by pageviews and conversion factors; whereas when the parameters were part of the URL you could not do this easily.

    So for example in this image we can see there were 2,873 views of the /womens page for the time period selected. If the parameters had still been part of the URL as it was in the unfiltered view, these pageviews would have been distributed over a couple dozen or so different combinations and it would have been impossible to tell how many people viewed the page.

    So we’ve been able to get the total number of pageviews which is essential, but what about those parameters? Luckily because we’ve saved them as custom dimensions, it means the data is no longer lost. We can see the information by choosing the parameters as a secondary dimension.

    So, for example, you can see page views of women’s clothing grouped by clothing size, as pictured below:

    Essentially, we can now use these parameters anywhere where we can view data in Google Analytics. They come in handy in all sorts of different places, and it depends on what parameters are being saved. The list of parameters is dependent upon your eCommerce platform, and some platforms allow you to add your own custom parameters as well (but be careful not to include Personally Identifiable Information if you are going to do this).

    Here are some ideas for using your parameters to find opportunities:

    • If your store uses category parameters, you can identify views of specific categories of products.
    • If your store allows visitors to order products in different ways, identify if certain product orderings are more profitable than others, and make the more profitable products rank within the top few products in the default product order.
    • If your store captures clothing or shoe sizes or other ‘size’ data, you can add them to audiences, and let visitors know when you have new products in stock in their chosen size.
    • If your store captures email mailing list IDs then you may be able to send vouchers or special offers via email to people who responded to an email campaign, but didn’t complete their purchase.
    • If your store captures product list page count then you can identify visitors who were really motivated to search for something special. Perhaps they looked through several pages in a search list, but didn’t find what they were after, or couldn’t decide what to get. These visitors may be highly motivated if you can lure them back with a special offer.
    • If your store captures data about colour selections then you can send custom offers based on the visitors’ favourite colours.
    • If your store captures gift voucher codes then you can identify all the sessions where someone uses a gift voucher to pay.
    • If any of the characteristics of your product or service are being listed as parameters you can get a better idea of what people are searching for on your store.

    The trick with using this data is to consider ways that a customer service representative at a brick and mortar shop may help their customers, and then find ways to help your online customers in the same way. Letting them know about products they might like through helpful suggestions and remarketing can be one such strategy.

    In essence, you are trying to attract people to your eCommerce store much in the same way that retail outlets seek footfall. You are trying to understand your customers, and then tailor your offerings to the people who are already interested in your products and services.

    Before we finish up on this topic of parameters and custom dimensions – what do you do if you want to capture data, but it isn’t coming through as a parameter? Stay tuned, and we will soon discuss enhanced eCommerce settings, and the data that can be collected using this framework.

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