Web Analytics

Implementation Adobe Analytics : The basic information you need to cover

Every implementation is different.
Every website is different.
But there are some information and event that, no matter the type of website you run, you would like to have data about.
I will try to give my though on what is necessary to have – at a minimum – on your implementation of Adobe Analytics

Traffic Information :

Dimensions : 

  • Page Category : Categorizing your website pages by Category is a must. (ie : Snowboard vs Ski section)
  • Page Template : Categorizing your website pages by Template is also a must. (ie : Category Page vs Product Detail Page)
  • Page URL : retrieving the page URL on your website in a clean way (without parameters)
  • Path : retrieving only the path of your URL is important as well. it will enable you to have clearer view on the difference, getting rid of the domain.
  • Domain : Yes, even if you have only one website, you don’t know what is going to happen in 5 years from now, so I’ll recommend to do that.
  • Subdomain : This up to debate, but I think it doesn’t cost anything and as stated before, you don’t know what is coming in 5 years from now (or even 6 months sometimes 🙂 )
  • Internal Search term : If you have a search platform on your site, you want to retrieve which keyword has been used.
  • Filters : Which filter is being used on your website. This can be tricky as there is probably going to be multiple filter that can be used at the same time.
  • Campaign_id : The campaign_id is one of the most important information, so make sure that you have it before going live with your normal attribution & retention.
  • Campaign_id with different retention period : It is now possible to change the attribution model of your data directly in your tool (Google analytics or Adobe Analytics) but the retention is not yet possible. So be sure to have a different retention period set for a campaign variable. I would always suggest : keep your basic 30 days retention in your normal campaign dimension, then create a copy of the campaign dimension with only the visit retention. Because every visit is different.
  • JS code version : This is quite interesting to set up in order to know if all of the visitors are seeing the last version of your code implementation.

Metrics :

  • Page view : no matter what your basic tool give you, you want to have your own metric set for counting the page views
  • Search Results : number of search results that has been returned from the search
  • Filter usage : if a filter has been used.
  • Internal Search term instances : number of time a internal Search term is being used.
  • Campaign landing : a metric to make sure to know how many campaign arrives on your website.
  • JS Error : number of time a try/catch (mostly the catch) worked (see my article). It will enable faster debugging.
  • Secondary Metrics : Number of contact form sent, number of Account status check, etc…
    Whatever that the user is doing and have a specific meaning on your context. Think hard on it because some may become key indicator at some point.

 

Ecommerce Information : 

Dimensions : 

  • Product : The famous product dimension is definitely a MUST
  • Cart Addition Campaign : the campaign that have been used at the moment of the cart addition
  • Universal Cart addition origin : On cart addition events : See this (super long) blog post to understand 😉
  • Path origin : on Cart addition events : Where does any Product added and that happen
  • Checkout : you need to make  sure that you clearly have identified the different steps of your checkout for further analysis
  • Blockers on checkout : Elements that could block the user from moving forward on buying your product(s).
    Examples : Minimum Order Value, Shipping Fee, Forms mandatory field missing.

Metrics : 

  • Prod view : when a product is being view.
  • Cart Addition : the most important metric of all (almost 😉 ). Number of add to cart action done on your website.
  • Cart Removal : number of time a product is removed from the basket
  • Number of product added to cart : Amount of product added to cart
  • Number of product remove from cart : Amount of product remove from the cart
  • Revenue added : – no explanation needed –
  • Revenue remove : – no explanation needed –
  • Revenue : The total revenue generated on your site.
  • Value Coupon : Total discount given by coupons
  • Shipping Fee : Shipping fee paid by the user

 

I hope this list will help you on your starting point when you need to do a new implementation.
As explained above, it is not exhaustive, it is the minimum that need to be done to start working with your Analytics reports.
Most of the difficulty lies in the checking that these variable are set with the correct values and what to do with them later on.
As they say… Garbage in –> Garbage out.

 

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