Attribution Overview

Overview

We try to make it easy for you to see attribution reporting options that (1) are based off of actual revenue numbers from your ecommerce store and (2) give you multiple perspectives to choose from.

We use information from Google Analytics, post-purchase surveys, discount codes, and information you provide in your Brand Supplied Data to give you those multiple perspectives.

Where to see attribution data

There are a couple places you can go to see attribution data. The most appropriate place to look depends on how you are trying to analyze the data.

• Order-level data — To see attribution information where you can drill down to information about individual orders, you can use the Order Attribution view, which is available in the Order & Order Line Revenue and Transactional Sales explores.

• Customer-level data — You can see attribution values for each customer's first, second, and last orders using the Customer RFM & First/Second/Last Order view. This view is available in customer-centric explores like LTV Time Series, but is also available in any explores that contain a customer ID, like Order & Order Line Revenue.

• Aggregated data — You can see aggregated attribution info in the Marketing Attribution explore. This explore rolls up order-level attribution data to the channel and vendor level so that you can calculate metrics like ROAS and CPA as well as compare the results to the vendor-reported numbers from your ad platforms.

Attribution models

Survey-Based attribution

Survey-Based attribution relies on information submitted from your customers through post-purchase surveys. For example, if your customer answers the "How did you hear about us?" question in a Fairing post-purchase survey, this information will be reflected in Survey-Based attribution dimensions.

-> Learn more about Survey-Based attribution

Discount Code attribution

Discount Code attribution assigns credit to different channels and vendors based on the discount code value associated with an order.

-> Learn more about Discount Code attribution

Google Analytics-based attribution models (First Click, Last Click, and Assisted)

All of the following models give you different perspectives on attribution using Google Analytics data:

• Last Click — Attributes credit to the traffic source that initiated the session in which a user made a purchase.

• First Click — Attributes credit to the first traffic source the user interacted with in the 30 days prior to the purchase.

• Assisted — Assigns credit for an order to every non-last-click traffic source that the user interacted with in the 30 days prior to purchase. Think of this as "non-last-click" attribution.

• Last Click + Assisted — Combines Last Click and Assisted attribution models. Think of this as "any click" attribution because a traffic source will get credit for the order if there was a touchpoint at any point in the 30 days prior to purchase.

• Last Ad Click — Attributes credit to the last advertising channel the user interacted with before making a purchase. i.e. Paid Search, Paid Social Display

• Last Marketing Click — Attributes credit to the last marketing channel the user interacted with before making a purchase. i.e Ads Traffic, Email SMS or Affiliate.

-> Learn more about First Click, Last Click, and Assisted attribution models

Custom Attribution

Custom Attribution lets you use a waterfall approach to sift through multiple attribution data sources for a single order and return a single channel and vendor value based on the priority you specify in the Daasity app.

-> Learn more about Custom Attribution

Vendor-Reported attribution

Vendor-Reported attribution shows the performance metrics straight from your marketing platforms.

-> Learn more about Vendor-Reported attribution

Dynamic attribution measures

In the Marketing Attribution explore, there is a set of "Dynamic" fields:

These dynamic measures aren't actually a separate attribution model. Rather, you can place these measures in your reports, and then use the Dynamic Attribution Method filter-only field to choose which attribution measures should be reflected in the dynamic measures. This enables you to quickly flip back and forth between methods without having to overload your reports with different measures: