Multi-Touch Attribution Tracking Model
Posted: Thu Dec 12, 2024 10:41 am
Cross-device attribution allocation
Beyond platform differences, you also have to consider device-based attribution. Was the sale made from a desktop or mobile device?
How would you assign credit for a sale that started on a computer, but ended up taking place on a friend's laptop?
It’s common for consumers to switch between devices, but this makes it difficult to track a particular person as they make these typical changes. While advertising platforms are getting much better at tracking cross-device analytics, attribution tools haven’t caught up.
Facebook led the way in perfecting cross-device tracking, and following in its footsteps, Google Analytics is adding cross-device capabilities with Google Signals.
Google Signals can track anyone who has ads personalization turned on, and this is helpful with attribution. For example, the report shows if they started on mobile and then continued on desktop and then back to mobile.
Multi-touch attribution models offer a method of slicing up information as a way to prioritize and measure the return on all of your marketing efforts.
It reflects the way Google Search, Facebook Ads, email, digital ads, and other initiatives can target the same customer with the same product over and over again. Each traffic source gave the customer a reason to buy, and they were likely enticed with deals or discounts along their journey.
Of course, Facebook and Google are tracking each ad view and impression austria business email list individually. Each platform sees that the customer made a purchase, even if they never clicked on an ad, both will say they drove the sale.
But with the multi-touch attribution model, the brand must now explain how much each interaction contributed to the customer and, ultimately, whether it caused the purchase.
First Interaction Attribution Model vs. Last Interaction Attribution Model
The first interaction attribution model assigns 100% credit to the first marketing touchpoint. For example, 100% would go to the first channel that introduced the purchase idea.
On the flip side, the last interaction attribution model gives credit to the last channel that prompted the purchase. This source is awarded 100% of the referral rate value, because this final interaction is the one that supposedly led you to make a purchase.
Last-interaction attribution tends to be the default model for advertising platforms, but advertisers have the option to change the attribution model in Google Analytics Attribution tools or Facebook Attribution.
There are other models between these two extremes that analyze the merit of a sale based on different variables. For example, a percentage of merit can be weighted and distributed based on how each touchpoint is perceived to have contributed to the sale.
Beyond platform differences, you also have to consider device-based attribution. Was the sale made from a desktop or mobile device?
How would you assign credit for a sale that started on a computer, but ended up taking place on a friend's laptop?
It’s common for consumers to switch between devices, but this makes it difficult to track a particular person as they make these typical changes. While advertising platforms are getting much better at tracking cross-device analytics, attribution tools haven’t caught up.
Facebook led the way in perfecting cross-device tracking, and following in its footsteps, Google Analytics is adding cross-device capabilities with Google Signals.
Google Signals can track anyone who has ads personalization turned on, and this is helpful with attribution. For example, the report shows if they started on mobile and then continued on desktop and then back to mobile.
Multi-touch attribution models offer a method of slicing up information as a way to prioritize and measure the return on all of your marketing efforts.
It reflects the way Google Search, Facebook Ads, email, digital ads, and other initiatives can target the same customer with the same product over and over again. Each traffic source gave the customer a reason to buy, and they were likely enticed with deals or discounts along their journey.
Of course, Facebook and Google are tracking each ad view and impression austria business email list individually. Each platform sees that the customer made a purchase, even if they never clicked on an ad, both will say they drove the sale.
But with the multi-touch attribution model, the brand must now explain how much each interaction contributed to the customer and, ultimately, whether it caused the purchase.
First Interaction Attribution Model vs. Last Interaction Attribution Model
The first interaction attribution model assigns 100% credit to the first marketing touchpoint. For example, 100% would go to the first channel that introduced the purchase idea.
On the flip side, the last interaction attribution model gives credit to the last channel that prompted the purchase. This source is awarded 100% of the referral rate value, because this final interaction is the one that supposedly led you to make a purchase.
Last-interaction attribution tends to be the default model for advertising platforms, but advertisers have the option to change the attribution model in Google Analytics Attribution tools or Facebook Attribution.
There are other models between these two extremes that analyze the merit of a sale based on different variables. For example, a percentage of merit can be weighted and distributed based on how each touchpoint is perceived to have contributed to the sale.