Amazon by default attributes the sales to an ad campaign based on a last-touch attribution model, leaving brands or advertisers with no visibility for the other interactions of the same customer with multiple touchpoints, before making the purchase.
The attribution model is a framework used in advertising to figure out how much credit is to be given to different marketing campaigns or touchpoints for a customer’s conversion i.e. purchase event. It plays a crucial role in understanding how your different marketing activities translate into conversions or sales. It also enables businesses to trace the impact of each ad interaction on the customer’s journey to conversion.
Using multi-touch attribution insights within Adbrew, advertisers can unlock four different types of attribution models, to analyze diverse attributions (aggregated by different ad campaigns) that contributed to & impacted the customers’ purchases. These include the following-
First Touch: This attribution model emphasizes the initial interaction a customer has with an ad campaign. In this model, credit for a conversion is assigned to the first touchpoint, providing insights into the entry point of a customer into the sales funnel.
Last Touch: The last touch attribution model gives credit for a conversion solely to the final interaction before the conversion/purchase event. This is the default attribution model of most Amazon PPC campaigns.
Position-based: This emphasizes both the first and last touchpoints in the customer’s journey. It allocates a higher percentage (70%) of credit to the last touchpoint while significantly lower (30%) to the first one, recognizing the significance of initiating and finalizing the conversion.
Linear Touch: The linear touch attribution model distributes credit for a conversion equally across all touchpoints in the customer’s journey. It provides a holistic view of the customer’s interaction with the ad throughout the entire funnel.
Adbrew provides in-detail metrics for Multi-Touch Attribution with two methodologies, one by individual campaign and another by high-level approach i.e. type of campaign. By utilizing these attribution-focused metrics, advertisers can easily analyze which type of attribution is working well for an individual campaign and also help to tweak their strategies, when it comes to the type of campaigns i.e. Sponsored Products, Brands, Display, or Amazon DSP.
Note:
For each of the visualizations, i.e. Path-to-Conversion, Time-to-Conversion, New-to-Brand, and Multi-Touch Attribution, one can select a variety of metrics from the dropdown (as shown below) to probe the performance of specific campaigns i.e. Sponsored Ads, DSP, or both, a different set of attributions and time range.
