MUMBAI, India, Oct. 26 -- Intellectual Property India has published a patent application (202621106049 A) filed by Lakshmi Narain College Of Technology on September 03, 2026, for System And Method For Confidence-Gated Causal Optimization And Deployment Of Digital Marketing Interventions.
Inventors include Dr. Satish Mewada; Dr. Pankaj Sharma; Dr. Abhishek Jain; and Dr. Satish Manwani.
The application for the patent was published on October 23, 2026, under issue no. 43/2026.
Abstract: ABSTRACT SYSTEM AND METHOD FOR CONFIDENCE-GATED CAUSAL OPTIMIZATION AND DEPLOYMENT OF DIGITAL MARKETING INTERVENTIONS The present invention relates to a system and a method for confidence gated causal optimization and deployment of digital marketing interventions. Heterogeneous data relating to customers, transactions, campaigns, channels, and markets are obtained and analyzed to derive confidence scores at a field level, using factors such as the reliability, recency, completeness, and consistency of the sources. Unreliable fields are either suppressed or down-weighted in order to produce confidence qualified feature vectors. The causal optimization model determines the incremental outcome and its uncertainty, for each possible intervention as compared to a reference intervention. Feature vectors of a possible campaign are evaluated together, taking into consideration the data-confidence, uncertainty and operational constraints. The selected vector is then deployed to the treatment group while keeping the control group unchanged. Incremental outcomes observed are compared to incremental outcomes predicted. Data-drift, causal effect-drift, or degradation in the model prompts shadow-model training, validation gated promotion, and automatic roll-back on post-deployment degradation of model performance, thus ensuring that unreliable inputs do not affect interventions. Fig-3
Disclaimer: Curated by HT Syndication.
