Attribution IQ in Calculated Metrics

I am Trevor Paulsen with Adobe Analytics product management and will show you new features added to calculated metrics related to attribution IQ. To start up, I have got a free form table pulled up. I have got my marketing channels, orders and revenue. Customers often want to be able to create calculated metrics that use attribution models. You can do that by creating a calculated metric and by bringing-in a metric into the calculated metric builder. You will notice under the settings cog the newly added attribution option where I can specify different attribution model. I can specify any of the listed attribution models like last touch, first touch… or more sophisticated models like U shaped, J curve, J time decay or custom. I like to compare last touch orders with first touch orders by simply dragging-in. Selecting minus and subtracting last touch from first touch or vice versa.

By doing that I am able to see how different these two attribution models perform for each of my channels. When I apply that to a freeform table. When I compare these two models: first and last touch, I see which channels are more often participating in first touch context from the last touch context. I see the email happens to participate more often in the last touch case than the first touch case. Very usefull. Calculated metrics allows me to mix and match various attribution models. Example: hybrid model created with half time decay and half linear, and combine them into a new hybrid model, getting new way of looking at attribution. I can do things like creating revenue per order using the new attribution models. So, by adding a time decay revenue divided by a time decay order, I can now see revenue per order in an attribution context. So, calculated metrics let me mix and match any model or compare any models in Analysis workspace. That is calculated metrics using attribution IQ. -