MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202621096950 A) filed by Archana Ganeshrao Mohokar on August 11, 2026, for A Dynamic Pricing Optimization Method Using Real-Time Consumer Behaviour Data And Predictive Machine Learning Models.

Inventor includes Archana Ganeshrao Mohokar.

The application for the patent was published on September 25, 2026, under issue no. 39/2026.

Abstract: ABSTRACT The present invention discloses a computer-implemented dynamic pricing optimization method using real-time consumer behaviour data and predictive machine learning models. The method collects behavioural events from commercial platforms, including product searches, page views, clicks, comparison activities, cart additions, cart abandonment, purchases, discount responses, session duration, geographic information, and device information. The collected data is validated, anonymized, organized, and converted into behavioural variables representing consumer interest, purchase intention, engagement, demand, and price sensitivity. Contextual information comprising inventory availability, product cost, competitor prices, seasonal conditions, supply changes, promotional schedules, and business requirements is integrated with the behavioural variables. One or more predictive models estimate purchase probability, expected demand, revenue, and consumer response at multiple candidate prices. A pricing optimization engine selects a candidate price according to a predefined objective, including revenue improvement, profit maximization, conversion enhancement, demand balancing, or inventory clearance. A validation module verifies the selected price against price boundaries, margin requirements, fluctuation limits, fairness policies, and regulatory constraints. An approved price is automatically deployed through a connected sales platform. Consumer responses following deployment are monitored and supplied to a feedback-learning module for model adjustment and performance improvement. The method thereby provides responsive, controlled, explainable, and adaptive price optimization across multiple commercial channels.

Disclaimer: Curated by HT Syndication.