Multi-Touch Attribution in Hector

Every campaign has a goal, and at Hector, we ensure each one gets the credit it deserves. That’s why we meticulously designed the Multi-Touch Attribution report within Amazon Marketing Cloud, so you can seamlessly assess campaign performance with clarity and precision.

Instead of attributing 100% of a sale to the last touch (as Amazon does), Hector allows you to see all four attribution models for every campaign. 

This means you can finally determine whether that broad keyword campaign contributed to a final conversion and even evaluate its ROAS based on first-touch attribution. 

Why does Multi-Touch Attribution matter?

Customer acquisition is not linear.
Shoppers interact with multiple ads before making a purchase.
Each ad plays a role in influencing the customer’s buying decision.
Amazon attributes 100% of the purchase credit to the last touch.
The last keyword, search term, or campaign receives full credit for the purchase.
Customers search for multiple keywords before buying.
They view and click on multiple ads before making a purchase.
Each view and click contribute to the final decision and deserve a share of the credit.
Performance should be evaluated using an appropriate attribution model.

Understanding Campaign Optimization & Attribution Models

Example:

🔹 You notice that a long-tail keyword has a better ROAS than a single-word keyword, so you reduce spending on the single-word keyword.
🔹 You lower bids and even cut budgets for those keywords.
🔹 This happens because last-touch attribution gives full credit to the long-tail keyword and its campaign.
🔹 However, we know that customers search for multiple keywords before making a purchase.
🔹 So, how do we determine which keywords they searched before arriving at the long-tail keyword and completing the purchase?
🔹 In AMC, you can view the first and last search terms a customer used before buying, we’ll cover this later.
🔹 Now, what if Amazon attributed full credit to the first keyword searched and clicked? In that case, the single-word keyword and campaign would show a better ROAS than the last-touch keyword or campaign.
🔹 What if you don’t want to assign all the credit to either the first or last touch?
🔹 You can distribute equal credit between the first- and last-touch keywords, this is called the linear attribution model.
🔹 Want to allocate 30% credit to the first touch and 70% to the last touch? Use the position-based attribution model.

By choosing the right attribution model, you gain a more accurate view of campaign performance and optimize your ad spend effectively

Whether it's SP, SB, SD, or DSP campaigns, Hector lets you analyze performance beyond a single touchpoint.