Retail and eCommerce
The customer operates successful fashion resale website and mobile apps, enabling consumers to buy and sell secondhand clothing online. The customer sought to optimize its retargeting efforts of website abandoners by personalizing its messaging based on website behavior.
Using Lore IO, the customer developed sophisticated website Journeys that modeled complex behaviors. The team created intelligent customer cohorts, and, leveraging Lore IO's flexible APIs, extracted the audiences and retargeted them.
Audience segments included sessions that abandoned carts, partially researched products, unfinished reviews, abandonment due to out of stock, and more.
Customers gained access to the smart data within only two days, with full deployment after one week. After two weeks, the customer had achieved integrated data views ready for personalization available to all teams, including Content, Marketing, Product, Development, and Infrastructure.
Six months following delivery, the customer has increased data access and utilization by 63%, and tripled the number of data sources it leverages for personalization. The customer has increased the depth of its insights, now gaining more intelligence into impact of marketing spend and video consumption behavior.