Using the Explore view number visualization, calculate the average lifetime spend per user. This will require 3 measures, one that sums the average price for purchase actions, one that counts all users, and a third that divides the 2 to generate an average, run this from the beginning of time to now.
Using Explore number view build a query that has 3 measures. Measure 1 should return the sum of price filtered to events with action that matches purchase_confirmed. Measure 2 should return a count of unique user actors that is filtered to all user actors. Measure 3 should use the calculate method to divide measure 1 by measure 2. Starting at the beginning of time and ending now.
Average lifetime spend is a standardized staple in business analytics and is very helpful as a starting point to build other queries like customer acquisition cost, revenue attribution for sales and marketing channels, engagement rates relationship to return, and general conversion rates.
Note: The numbers and result do not need to be an exact match as the data changes over time. The query construction is what is most important. See images below.
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