Email Suggestor System for Retail Transaction Efficiency

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Solution Overview

Problem

Current systems for capturing consumer email addresses in retail environments are inefficient and prone to errors due to cumbersome data capture methods and poorly designed applications, leading to increased transaction time and inaccuracies.

Innovation Solution

The email suggestor system uses statistical models to generate and rank suggested email usernames and domain names based on consumer identity data, allowing for efficient and accurate capture of email addresses by providing a list of probable combinations for user selection, which can be updated and refined through feedback and click-stream information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the consumer manually inputs the email address, then the merchant can obtain the email address, but the transaction time increases and the consumer experience deteriorates

Engineering Contradiction:

Improveemail address capture accuracyVSAvoidtransaction time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by automatically generating suggested email addresses using statistical models based on consumer identity data (name, phone number, etc.) before the consumer needs to provide the email address. This eliminates the need for manual input during the transaction, reducing transaction time while maintaining accuracy through user confirmation of the suggested address.

Inventive Principle:

Principle #10Preliminary action

2Productivity

If the merchant manually inputs the email address, then the email address can be captured, but spelling errors occur and accuracy decreases

Engineering Contradiction:

Improveemail capture speedVSAvoidemail address accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system enables self-service by automatically generating email address suggestions using statistical models that process consumer identity data. The system serves itself by performing the data processing and suggestion generation without requiring merchant intervention, thereby eliminating spelling errors while maintaining high capture speed. The consumer then confirms the suggested address, ensuring accuracy.

Inventive Principle:

Principle #25Self-service

3Device complexity

If traditional data capture methods are used, then the system is simple, but the user interface is cumbersome and transaction time increases

Engineering Contradiction:

Improvesystem complexityVSAvoiduser interface convenience

Core Design Contradiction:

Device complexityVSEase of operation

Solution Approach 1:

The system replaces the mechanical interaction of manual typing and form filling with an automated computational process. Statistical models automatically generate email address suggestions based on consumer identity data, substituting the cumbersome mechanical data entry process with an efficient automated system that presents pre-generated suggestions to the consumer for confirmation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Reliability

If manual email input methods are used, then no additional technology is required, but errors and delays in capturing consumer information occur

Engineering Contradiction:

Improvedata capture reliabilityVSAvoidautomation level

Core Design Contradiction:

ReliabilityVSExtent of automation

Solution Approach 1:

The system implements feedback by using statistical models that analyze consumer identity data and generate email address suggestions, then presenting these suggestions to the consumer for confirmation. The consumer's selection or correction of the suggested address provides feedback that can be used to refine future suggestions, thereby improving reliability while maintaining a high level of automation throughout the process.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11651155B2System for determining consumer identification information at a point-of-sale

Publication Date: 2023.05.16 BYTEDANCE INC

AI summary

The email suggestor system and method provide an efficient and effective way to capture a user identifier, such as an email address of a consumer in a retail environment. The email suggestor system generates one or more suggested first text portions based on input data, outputs at least one of the suggested first text portions, and receives a selection of a first text portion. The email suggestor system generates one or more suggested second text portions of a user identifier based on the input data, outputs at least one of the suggested second text portions, and receives a selection of a second text portion. The email suggestor system generates a user identifier including the selected first text portion and the selected second text portion. The email suggestor system uses received feedback response to refine and/or train one or more models with which it generates the suggested text portions.