Promotional Email Image Validation for E-Commerce Stock Checks

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Solution Overview

Problem

The manual process of validating promotional emails for product availability on e-commerce websites is time-consuming and prone to oversight, particularly when dealing with multiple products in images, lacking sufficient automation support.

Innovation Solution

A method and system utilizing Computer Vision (CV) techniques and deep learning algorithms to automatically validate promotional emails by calculating similarity scores and determining stock availability status of products, including image transformation, product identification, and classification into predefined categories.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual validation process is used to validate promotional emails and check product availability, then testers can carefully examine each product detail, but the process becomes time-consuming and prone to oversight

Engineering Contradiction:

Improvevalidation accuracyVSAvoidtesting time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical validation process with an automated Computer Vision system. The CV algorithm automatically extracts products from promotional email images, retrieves corresponding website images, and performs validation without human intervention, thereby reducing testing time while maintaining accuracy through systematic automated comparison of product features.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system creates digital copies of products from promotional emails and compares them against website product images. By using image processing and feature extraction, the system replicates the manual validation process in an automated manner, enabling simultaneous validation of multiple products without the time constraints of manual examination.

Inventive Principle:

Principle #26Copying

2Reliability

If testers manually validate multiple products in promotional email images, then comprehensive validation can be achieved, but the complexity and time required increase significantly

Engineering Contradiction:

Improvevalidation completenessVSAvoidprocess complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the validation process into distinct automated stages: extracting products from promotional email images, retrieving corresponding images from the e-commerce website, extracting product features from both sets of images, and comparing features to validate matches. This segmentation transforms a complex manual process into manageable automated steps that can be executed systematically.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system replaces complex manual validation operations with automated Computer Vision algorithms that handle image processing, feature extraction, and comparison. This substitution reduces process complexity by eliminating the need for testers to manually examine each product while maintaining comprehensive validation through automated feature-based matching.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automated frameworks are used to validate promotional emails, then processing speed increases, but the ability to accurately identify and validate multiple products in images decreases

Engineering Contradiction:

Improvevalidation speedVSAvoidproduct identification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent employs advanced Computer Vision algorithms that automatically identify and extract multiple products from promotional email images with high accuracy. The system uses feature extraction techniques to capture essential product characteristics and compares them against website product images, achieving both high processing speed and accurate product identification without manual intervention.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the approach from pixel-level image comparison to feature-based parameter comparison. By extracting key product features such as color, shape, and distinctive characteristics, the system enables accurate product identification and validation while processing multiple products efficiently, overcoming the limitations of traditional automated image matching.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12597239B2Method and system for validating promotional emails and product availability from E-commerce websites

Publication Date: 2026.04.07 HCL TECH LTD

AI summary

A method and system for validating promotional emails and product availability from E-commerce websites is disclosed. In one embodiment, the method includes retrieving a first set of images corresponding to an image strip and a second set of images corresponding to a promotional email from a database. The first set of images and the second set of images may be associated with one or more products. The method further includes calculating a similarity score between each of the first set of images and each of the second set of images using a first Computer Vision (CV) technique. The method further includes selecting one or more valid images from the second set of images based on the similarity score. The method further includes determining a stock availability status of at least one product presented in the one or more valid images from at least one website using a deep learning algorithm.