Describes how to calculate common metrics using data feeds.
Hits normally excluded from Adobe Analytics are included in data feeds. Use
exclude_hit = 0 to remove excluded hits from queries on raw data. Data sourced data are also included in data feeds. If you want to exclude data sources, exclude all rows with
hit_source = 5,7,8,9.
Internet irregularities, system irregularities, or the use of custom visitor IDs can rarely use the same
visit_num values for different visits. Use
visit_start_time_gmt when counting visits to make sure that these visits are counted.
All methods Adobe uses to identify unique visitors (custom visitor ID, Experience Cloud ID service, etc.) are all ultimately calculated as a value in
post_visid_low. The concatenation of these two columns can be used as the standard of identifying unique visitors regardless of how they were identified as a unique visitor. If you would like to understand which method Adobe used to identify a unique visitor, use the column
post_page_event = 100 for custom links
post_page_event = 101 for download links
post_page_event = 102 for exit links
All metrics are counted in the
post_event_list column as comma-delimited integers. Use
event.tsv to match numeric values with the desired event. For example,
post_event_list = 1,200 indicates that the hit contained a purchase event and custom event 1.
Hits must first be grouped by visit, then ordered according to the hit number within the visit.
post_cust_hit_time value from the subsequent hit’s
If a hit’s
currency value doesn’t match a report suite’s currency, it is converted using that day’s conversion rate. The column
post_product_list uses the converted currency value, so all hits use the same currency in this column.
duplicate_purchase = 1.
event_list contains the purchase event.
post_product_list column to extract all price data. The
post_product_list column is formatted the same as the
quantity in the product string to calculate Units
price in the product string to calculate revenue