Jetlore’s Prediction Platform maps consumer behavior to structured actionable data with the power of artificial intelligence, maximizing customer engagement, conversions and revenue.
B2C brands need a holistic understanding of their consumers.
Today, B2C brands have millions of customers with often no real insight into who those customers really are and why they bought what they did. In order to truly market to customers, retailers and large B2C brands need to understand what a customer is doing before, during and after a purchase, to be able to provide any fact-based attempt at marketing to them. If a retailer isn't capturing that data, the outreach is based on rule-automated and human-curated gut-instincts, triggered alerts based on rules, and other sub-optimal marketing attempts.
Current state: Conflicting
With Jetlore’s Prediction Platform™, marketers benefit from the power of artificial intelligence as it analyzes consumer behavior, aggregates thousands of unique predictive attributes on millions of customers in real-time, and maps those attributes to structured actionable data, building a comprehensive, holistic view of each customer.
Jetlore's Prediction Platform learns and adapts to each customer's unique preferences via semantic attributes, taking the consumer experience to the next level - beyond traditional personalization - to predictions, creating the foundation for a true B2C CRM.
Jetlore: AI-powered Predictive Content
The Prediction Platform Products
Jetlore's Learning-to-Rank Technology
Jetlore's patent pending “learning-to-rank” technology learns customer preferences from each customer’s interaction and dynamically adapts to each customer in real time. Jetlore tracks each piece of content it displays and ensures that no two customers see the same content, and no customer ever sees the same content twice.
Semantic understanding of content
Focus on the individual attributes of each piece of content, and each customer's reaction to them.
Jetlore's ranking engine automatically scores content for relevance based on every customer impression.
Adapt to each user's response
We learn from each customer's reaction to displayed content, and adapt the following experiences accordingly; we amplify the content a customer expresses interest in, and mute the content they do not.