Use cases for AI capabilities in Adobe Target

Hi ​@AbdulJo1  

Have you tried to implement below target capabilities which is primarily based on AI 

• Auto-Target (machine‑learning–driven personalization)
• Automated Personalization (AP) (algorithmic content selection and ranking)

Thanks, 

Hi ​@AbdulJo1 

Enabling AI in Adobe Target (Auto-Allocate and Auto-Target) is the best way to move from static testing to 'always-on' optimization. Here are the three most successful use cases: 

1. The 'Breaking News' or High-Velocity Campaign (Auto-Allocate)

• The Problem: In a 48-hour flash sale, a standard A/B test spends 24 hours just 'learning,' losing potential revenue on the losing variant.
• The AI Use Case: Use Auto-Allocate. The AI shifts traffic in real-time to the winning banner/offer as soon as statistical significance starts to lean one way.
• Value: It minimizes 'regret' (lost conversions) by not wasting 50% of your traffic on a poor performer during a short window. 

2. The 'Paradox of Choice' on Homepages (Auto-Target)

• The Problem: A 'one-size-fits-all' hero banner ignores that a returning customer has different needs than a first-time visitor.
• The AI Use Case: Use Auto-Target. Target uses an ensemble of Machine Learning algorithms to look at the visitor's browser, location, and past behavior to serve the version most likely to convert that specific individual.
• Value: This handles the 'long tail' of your audience that manual segments (like 'Chrome Users in London') often miss. 

3. Large-Scale Content Testing (Automated Personalization - AP)

• The Problem: You have 5 different headlines, 3 images, and 2 CTA buttons. Manually testing every combination (MVT) would take months to reach significance.
• The AI Use Case: Use Automated Personalization (AP). The AI tests all combinations and learns which 'offer' performs best for which user profile automatically.
• Value: It automates the 'mapping' of content to users without you having to build 30 different manual rules. 

Thanks,

Santosh Kumar