Clickstream model reveals online customers’ usage patterns and opportunities to customize website experiences.

Cross-channel response model identifies retail customers likely to enter delivery channels without decreasing retail spending.

Customer churn model retains the costs of attriting customers whose results can be improved via an early intervention based on customer behavior.

Customer segmentation model Identifies segments by behaviors and generates business insights through appropriate customer tracking.

Lead monetization model hands off specific leads through keyword search-terms to the partner paying the most.

LTV model captures the profits over a future time window, helps to decide investment in a single customer and identifies key levers.

Multi-touch attribution model measures the partial value of interactive marketing channels which contribute to a desired outcome.

Predictive Model is the origin of many models, which could meet different business functional usage combined with domain expertise.

Product recommendation list model measures likelihood of customers to make repurchases of familiar items and the expansion of purchases in new categories.

Reinforcement learning model provides a holistic view and synergistic effect which is active in interactive marketing, especially tracking customer journey.

Revenue per click model allocates spends across search engines wisely and Maximizes spend within engines on keywords with the most elasticity.

Search ranking model reduces search complexity of a search engine for many applications, improves search efficiency and optimizes business metrics.

Uplift model predicts the incremental impact of a treatment (such as a direct marketing action) on an individual's behaviour.