Promotional Offer Recommendation System Using Linear Programming
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Solution Overview
Problem
Retailers face challenges in identifying the best combination of promotional offers in real-time for shoppers with multiple items in their cart, due to complex eligibility rules and frequent introduction of new offers, leading to sub-optimal value realization and dissatisfaction.
Innovation Solution
A method and system using linear programming (LP) algorithms to optimize promotional offers in real-time, considering business rules and objective functions, with automatic or manual assignment of new offers based on dynamic thresholds and centroids, to recommend ideal promotional offers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple promotional offers are provided for cart items, then shopper benefit and sales volume are maximized, but the complexity of identifying the best combination of offers increases
Solution Approach 1:
The system performs self-service by automatically evaluating all promotional offer combinations against business rules and objective functions, eliminating the need for manual analysis and instantly identifying the optimal offer combination for each cart
Solution Approach 2:
The patent replaces manual offer evaluation with an automated computational system that uses objective functions and algorithms to evaluate offer combinations, substituting human decision-making with a systematic mechanical process
2Adaptability or versatility
If new promotional offers are frequently introduced, then customer benefit is enhanced, but the difficulty of real-time offer management increases
Solution Approach 1:
The system is designed to be dynamic, automatically adapting to new promotional offers as they are introduced. The objective functions and business rules are evaluated in real-time against the current offer portfolio, allowing the system to dynamically adjust recommendations without manual reconfiguration
Solution Approach 2:
The patent changes parameters by introducing objective functions that quantify offer quality based on multiple criteria. These parameter-based evaluations allow the system to automatically assess and compare offers with different characteristics, making the management of diverse offer portfolios tractable
3Measurement precision
If manual evaluation of promotional offers is performed, then offer accuracy can be ensured, but real-time recommendation capability is lost
Solution Approach 1:
The patent substitutes manual evaluation with an automated computational system that applies objective functions and business rules algorithmically, maintaining evaluation accuracy through systematic computation while achieving real-time performance
Solution Approach 2:
The system enables continuous real-time evaluation of promotional offers as carts are updated or new offers are introduced, eliminating the interruption between manual evaluation steps and providing continuous optimal recommendations
Data Source
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AI summary
This disclosure relates generally to a method and system for assigning an ideal promotional offer on the plurality of items in a cart in real-time. Retailers have huge number of promotional offers and complex eligibility rules leading to explored number of combination of offers eligible to cart items in real time. It becomes challenging to identify the ideal offers that need to be assigned to cart items in real time. In addition, retailers introduce new promotional offers at frequent intervals and leading to adjust analytical framework every time as per the new promotional offer added. The disclosed method provides a mechanism wherein existing promotional offers are mapped with the cart items that maximize benefit to the shopper and also handles new promotional offers by assigning a suitable objective function automatically. Therefore, ideal combination of offers is provided to the shopper seamlessly.