Jasmine, marketing manager at a retail brand, wants to acquire new customers, as well as drive conversions online and offline.

Quality users

Jasmine wants to find new customers for women’s shoes. She uses AI to discover the types of user behavior that are most likely to convert: having visited the fashion blog on her company’s website; having browsed articles containing keywords like “boots”, “heels” and “leather shoes” on external sites; and loving cats.

She then sends them cross-screen ads at the right time to drive website sign-ups.

Increase revenue

Jasmine leverages AI-driven segmentation to target Facebook users who have purchased boots once in the past 30 days, or added air cushion shoes to the shopping cart in app in the last 10 days.

She entices consumers who don’t shop regularly online to visit a physical store for purchase with a discount voucher delivered by an ad.


To convert offline customers online, Jasmine sends them AI-powered product recommendations through SMS or EDM, such as leather care kit for customers who have purchased leather shoes offline, or shoes with different special features for those who are interested in waterproof footwear products.

On the other hand, to drive online visitors to purchase in-store, Jasmine uses AI to discovers their interests on external sites for creating more personalized in-store experience.

AI enables Jasmine to engage consumers at different stages of their life cycle seamlessly, and optimize both paid and owned channels for higher ROI.

What's more? Audience intelligence

AI enables Jasmine to map offline customers’ email addresses to anonymized online identities, and then discover their online interests for more effective audience segmentation, eventually driving more in-store foot traffic from returning customers.