Customers have a natural rhythm that manifests in their activities and behavior. They tend to visit a retailer store according to specific temporal patterns that are inherent in their purchase history. And these patterns are the ultimate key to the customers' hidden intents.
Intent Recognition unveils when the next purchase most likely appears and makes targeting more efficient, drives product recommendations for time delayed cross-selling and detects loyalty states to take action in due time when customers tend to terminate their relationship and much more.
Intent Recognition describes observable activities as probabilistic processes and uncovers what customers motivates and what they tend to do next or in the future.
It uses a well-established scientific algorithm that has found widespread use in artificial intelligence, language translation, speech recognition, medical diagnosis, to name a few.