• 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 Ecommerce Fixing Parameters

    Fixing the Problem of Parameters in your Ecommerce URLS in Google Analytics

    If you’ve read other articles in this series, you are probably familiar by now with the concept of filtering data to make it more valuable for your eCommerce store. This is undoubtedly a critical aspect of your overall Google Analytics configuration. We’ve covered spam filters, IP address filters, lowercase filters and trailing slashes filters, but even more important than any of these for an eCommerce store is appropriately dealing with the URL parameters.

    Essentially you need to strip all the parameters out of your URLs. This is an absolutely critical component of eCommerce Google Analytics configuration because unless you filter out the parameters, heavily parameterized pages (i.e. all of your shopping pages) will just give you garbage data. It doesn’t get much important than that for an eCommerce store!

    Every parameter creates a different URL, meaning that it is important for us to strip them out. If your website only had one parameter then it would not be such a big deal, but eCommerce sites have many parameters.

    So, for example, if you have a parameter of “sort_order”, the user could select a sort order of either ascending, descending or default (i.e. no parameter). Then you would have three URLs; one for each alternate sort order.

    Now let’s imagine that you have 20 different parameters, each with two alternate options, and a default option. Let’s say that any of these parameters can be present in any URL. The number of different pages that could be created from the combination of different parameters would be:

    i.e. 3,486,784,401 different combinations. Yes, that’s about three and a half billion. You do not want to deal with that much complexity!

    Essentially, if you don’t filter out your parameters, and attempt to use Google Analytics to guide the marketing for your eCommerce store, then you will have no idea how many views each of your pages is really getting. It really is a nightmare for any attempt to use your Google Analytics data when it looks like this.

    For example, how many people on this website looked at shoes?

    If you want to be able to accurately answer this question for your eCommerce store, you’d need to strip off the parameters. But before you just go and create a filter that simply deletes the parameters, you can go one better than that.

    While it is true that the parameters are making a mess of your data, those parameters actually contain really useful data. The parameters all indicate ways that your visitors are using your eCommerce store, and can provide you with powerful insights.

    For example, let’s say that you have a shoe store, and “shoe size” is a parameter for your store. You stock a limited range of the smallest and largest shoes in your store.

    If you sell out of these sizes, you could monitor how often these sizes are searched for on your store in order to determine future stocking volume.

    Or if people are searching for a shoe in a particular size and you had already sold out of that size, but got some new stock in, it would even be possible to set up a re-marketing campaign. This could be based on all the people who looked for that shoe in that size in the past, and would provide you with the opportunity to let them know that you have restocked!

    However, before you can do this you need to store the useful parameters in custom dimensions so that you can uniquely identify them later. You don’t want them to stay in the URL where they make a mess.

    Before you start, create a new View for filtering your parameters. My typical name for this view Filtered Data with No Parameters, but you may name yours whatever makes sense for you. It’s valuable to separate your data into a new view for this because you will be stripping data out of your page URLs. You should retain the original version in your Raw Data view and your Filtered Data With Parameters view if you have set one up in the earlier article, Adding Filtered Google Analytics Views Gives You Access to Better Marketing Data.

    In the next article in this series I’ll show you the steps that you need to take to identify your parameter list so that you can create custom dimensions from them.

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