How to Personalize Promotions with the Right Discount Level for Each Customer
This guide explains how to use the Promotion Recommendation score from Batch AI Predict to automatically determine the most effective discount level for each customer, maximizing both conversion and m
What Is the Promotion Recommendation Score?
Batch AI Predict's Promotion Recommendation score predicts, for each customer, the most effective discount level to offer in order to maximize the probability of purchase while protecting your margin. Rather than a single float with the promotion sensitivity score, the output is a recommended promotional mechanic (for example, 10%, 20%, or free delivery) calibrated to each customer's individual sensitivity.
Promotion Recommendation vs. Promotion Sensitivity: which one do you need?
Promotion Sensitivity → You want to know whether a customer needs a discount at all. Focus: identifying who to include in a promotional campaign.
Promotion Recommendation → You want to know which promotional mechanic suits each customer. Focus: offer calibration and margin optimization.
Why Use It?
Offering a 30% discount to a customer who would have converted at 10% is a direct margin loss. Offering 10% to a customer who needed 20% to convert means losing the sale. Promotion Recommendation solves both problems simultaneously.
With the Promotion Recommendation score, you can:
Avoid over-discounting your most loyal and conversion-ready customers.
Recover conversions from price-sensitive customers by offering them the threshold they actually need.
Run a single promotional campaign while personalizing the offer depth for every customer in your database.
How to Use This Score in Batch
Personalization: Inject the Recommended Discount Level Dynamically (Primary Use)
The core use case: use the recommended discount value as a personalization variable in your campaign template, so each customer automatically receives the right offer.
How to set it up:
In your email or push template composer, add a discount variable block.
Use the Batch personalization syntax to inject the recommended discount:
{{ profile.custom_attributes.batch_ai_promo_recommendation }}
Build your template logic so the displayed offer (percentage, banner, CTA) adapts based on this value.
Every customer who receives the campaign sees a different discount level, calculated specifically for them.
Segmentation: Exclude Low-Discount Customers from Heavy Promotional Campaigns
You can also use the recommended discount value as a segmentation filter to protect margin on your least price-sensitive profiles.
Example setup:
Exclude customers whose recommended discount is below a defined threshold from a high-discount promotional campaign
Send them a non-promotional version of the campaign instead
Real-World Use Cases
Industry
Example use case
Retail
End-of-season sale: send each customer a personalized discount level (10%, 20%, or 30%) automatically injected into a single email template, based on their predicted conversion threshold
Beauty & Cosmetics
Monthly promotional campaign: replace a fixed 20% discount for all with a personalized offer that protects margin on loyal customers while recovering conversions from price-sensitive ones
Travel
Flash sale: personalize the discount depth for each booker profile, offering deeper reductions only to customers who demonstrably need them to convert
Media & Entertainment
Subscription renewal campaign: calibrate the renewal discount individually to maximize the number of retained subscribers at the lowest possible promotional cost
Related Documentation
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