7.3 Counting Unique Items
Some COUNTER Metric_Types count the number of unique items that had a certain activity, such as a Unique_Item_Requests or Unique_Item_Investigations.
For the purpose of COUNTER metrics, an item is the typical unit of content being accessed by users, such as articles, book chapters, book segments, whole books (if delivered as a single file), and multimedia content. The item MUST be identified using the unique ID which identifies the work (e.g. chapter or article) regardless of format (e.g. PDF, HTML, or EPUB). If no item-level identifier is available, then use the item name in combination with the identifier of the parent item (i.e. the article title + ISSN of the journal, or chapter name + ISBN of the book).
The rules for calculating the unique item counts are as follows:
If multiple transactions qualifying for the Metric_Type in question represent the same item and occur in the same user-sessions, only one unique activity MUST be counted for that item.
A user session is defined any of the following ways: by a logged session ID + transaction date, by a logged user ID (if users log in with personal accounts) + transaction date + hour of day (day is divided into 24 one-hour slices), by a logged user cookie + transaction date + hour of day, or by a combination of IP address + user agent + transaction date + hour of day.
To allow for simplicity in calculating session IDs, when a session ID is not explicitly tracked, the day will be divided into 24 one-hour slices and a surrogate session ID will be generated by combining the transaction date + hour time slice + one of the following: user ID, cookie ID, or IP address + user agent. For example, consider the following transaction:
Transaction date/time: 2017-06-15 13:35
IP address: 192.1.1.168
User agent: Mozilla/5.0
Generated session ID: 192.1.1.168|Mozilla/5.0|2017-06-15|13
The above replacement for a session ID does not provide an exact analogy to a session. However, statistical studies show that the result of using such a surrogate for a session ID results in unique counts are within 1-2 % of unique counts generated with actual sessions.