Dynamic Email Recipient Grouping via Content Analysis
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Solution Overview
Problem
Existing email applications are restrictive in how recipients can be selected and grouped, requiring users to either enter each recipient manually or select from preformed groups, which is time-consuming and prone to errors, and do not allow for dynamic grouping based on user-specific email content or relationships.
Innovation Solution
A method and system that dynamically groups email recipients by analyzing previous emails to discover associations based on content, keywords, and patterns, suggesting associated recipients and allowing users to create groups dynamically, with the ability to modify and refine these associations over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually select or expand predefined recipient groups, then email can be sent to multiple recipients, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system automatically identifies and suggests recipient groups based on the email content, subject line, and previously sent emails. The recipient group selection is performed autonomously by the system without requiring manual user input for each recipient, thereby reducing time loss and improving productivity
Solution Approach 2:
The system pre-identifies and pre-sorts potential recipient groups before the user needs to send the email. By analyzing past communication patterns and email content in advance, the system prepares suggested recipient groups that can be quickly selected or modified, eliminating the need for manual scanning and selection during email composition
2Measurement precision
If users manually add or eliminate recipients from groups, then precise recipient selection is achieved, but the process is repetitive and cumbersome
Solution Approach 1:
The system continuously learns from user feedback by observing which suggested recipient groups are accepted or modified. This feedback loop allows the system to refine its recipient group identification algorithms over time, improving accuracy while reducing the need for manual adjustment. Users provide implicit feedback through their selection behavior, which the system uses to optimize future suggestions
Solution Approach 2:
The system changes the parameters for recipient group identification by analyzing different aspects of email content such as subject lines, body text, attachments, and communication history. By dynamically adjusting these analysis parameters based on the specific email context, the system achieves precise recipient selection without requiring manual recipient management
3Ease of operation
If predefined recipient groups are used, then email distribution is simplified, but the groups are too broad and include unwanted recipients
Solution Approach 1:
Instead of using uniform predefined groups, the system creates localized recipient suggestions based on the specific characteristics of each email. By analyzing the content, subject line, and context of each individual email, the system identifies which recipient subgroups are most relevant, providing precise targeting while maintaining ease of operation through automated selection
4Measurement precision
If users create custom recipient groups, then precise targeting is achieved, but the process is repetitive and time-consuming
Solution Approach 1:
The system performs the recipient group creation and selection process autonomously by analyzing email content and communication history. Instead of requiring users to manually create and manage custom groups, the system self-services the recipient identification task, achieving precise targeting while significantly improving email composition efficiency
Solution Approach 2:
The system replaces the mechanical process of manual recipient selection and group creation with automated content-based analysis. By substituting manual operations with algorithmic analysis of email content, subject lines, and communication patterns, the system achieves precise recipient targeting without the repetitive mechanical effort of manual group management
Data Source
AI summary
A method, system, and computer usable program product for dynamic grouping of email recipients are provided in the illustrative embodiments. A first recipient and a second recipient of a first email are identified and an association is formed between them. A selection of the first recipient is detected in a second email. Using the association, the second recipient is suggested as a recipient of the second email. The first email may be a previously sent email, and the second email may be an email being composed. A characteristic of the first email is identified and the characteristic may be used as a basis for the association in forming the association. The characteristic may be a phrase in, a type of content in, an attachment in, or a periodicity of the first email. Strength of the association may be modified based on the third email.