☕[AT Community Q&A Coffee Break] WEDNESDAY 4/12/23, 8am PT: AI Features, Automated Personalization & Auto-Target with Matthew Bailie & Georgia Frailey of the Adobe Target Consulting Team ☕

Hi @lonestarspock  

Our documentation that you have read through has the public information available on the sync service. Feel free to follow up with consulting services or client care on specifics around your use case. They may be able to provide additional details needed.

Hey @joef2, thanks for your question - short answer is no you cannot.

Hi @lonestarspock, I recommend following up with Client Care on specific SLAs based on your use case.

Hi @optimizing! Yes, you can absolutely use A4T as the reporting source for Auto-Target. There are modifications that you must apply so that attribution is correct. Please see this link for thorough instructions and context: https://experienceleague.adobe.com/docs/target-learn/tutorials/integrations/set-up-a4t-reports-in-analysis-workspace-for-auto-target-activities.html?lang=en

Hope that helps!

Hi @tushar_kar, from my understanding of the question, you're looking to update a section of an activity after clicking on a link selector. You can use the Modifications panel in the VEC while editing the activity to make several possible changes, mainly through CSS Selector, Mbox, and Custom Code modifications. These changes include inserting offers or changes to the actual element itself.

You can learn more through the following documentation: https://experienceleague.adobe.com/docs/target/using/experiences/vec/modifications/vec-code-editor.html?lang=en

@ajasullivan Auto-Target uses customer attributes to generate look-alike models to help predict who should see what content. These models incorporate both customer behavior (pages visited, what are they clicking on) along with their attributes (1st-3rd party data). Auto-Target is more about creating a personalized experience. Recommendations is a much lighter in that only the algorithm you select (e.g. post popular, most viewed) is used to determined what content to show to the customer. Also, with Recommendations you don't get ML insight reports. There are different use cases for Auto-Target and Recommendations.

Hi @gavinattard 

1) I hear you on it being difficult to get insights from the insights reports. I created a document that help teams analyze these two reports. @amelia_waliany will upload the document here in this post. The document will explain best practices for learning from the AP/AT insights reports. 

2)You can send a ticket to client care and have them remove segments from ML model generation. 

Hey @jeffersonba, here's an easy way to organize your thoughts about Target activities:

Optimization: 

A/B: I assume you get that one

Auto-Allocate: Similar to A/B, however it consistently allocates more traffic to the overall winning experience

Multi-Variate: Discover which element is the most influential. 

Personalization:

Experience Targeting: rules based personalization. Ex: People in California will see X experience, People in NY will see Y experience

Auto-Target: machine uses context of each user to predict and serve the experience they are most likely to convert on. Bonus: use same easy setup as A/B. Models generates at experience level. 

Automated Personalization: Scalable way to personalize when multiple locations involved - such as order of content. Models generate at the offer level. 

Hi @rcbt , thanks for your question!
Auto-Allocate is better suited for low traffic pages (ballpark sub 2,000 visits per day). Auto-Target requires per experience a minimum of 1,000 visits and 50 conversions per experience for machine learning models to generated. Keep in mind there are ways to increase traffic to a page my using redirects or coordinating a marking push to increase traffic for a time period.