LLM Prompt Generation for Personalized Customer Messaging
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Solution Overview
Problem
Companies face challenges in creating effective marketing tools that drive user engagement, as mass marketing campaigns often fail to resonate with individual customers, leading to low responsiveness due to a lack of personalization.
Innovation Solution
The use of artificial intelligence and machine learning, specifically Large Language Models, to generate customized customer messages by aggregating customer data, grouping customers based on profiles, and creating tailored prompts for personalized communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If mass marketing campaigns are used to reach customers, then the coverage and reach are improved, but the personalization and customer engagement deteriorate
Solution Approach 1:
The patent segments customers into different groups based on their profiles, behaviors, and preferences. By dividing the broad customer base into smaller segments, the system can apply personalized messaging strategies to each segment while maintaining the scalability of mass marketing campaigns.
Solution Approach 2:
The patent applies local quality by customizing message content, tone, and style according to specific customer segments' characteristics. Each customer group receives tailored communications that match their preferences, while the overall campaign structure remains consistent and scalable.
2Adaptability or versatility
If customized customer messages are generated for individual customers, then the personalization and engagement are improved, but the complexity and resource requirements worsen
Solution Approach 1:
The patent employs a multi-functional system that performs customer data aggregation, profile analysis, segmentation, and message generation within a single integrated platform. This universal approach reduces the need for separate specialized systems and simplifies the overall architecture.
Solution Approach 2:
The patent uses templates and patterns for message generation that can be replicated across different customer segments. Once a personalized message structure is developed for one segment, it can be copied and adapted for other segments, reducing the complexity of creating unique messages from scratch for each customer.
3Productivity
If customized customer messages are generated for individual customers, then the customer engagement and responsiveness are improved, but the time and computational resources worsen
Solution Approach 1:
The patent performs preliminary actions by pre-aggregating customer data, pre-defining customer segments, and pre-configuring message templates before the actual marketing campaign launches. This preparation work is done in advance, so that during the campaign, messages can be generated quickly by simply filling in segment-specific parameters.
Solution Approach 2:
The patent uses template copying and pattern matching to rapidly generate personalized messages. Once a message template is created and validated for a particular customer segment, it can be efficiently replicated and customized for similar segments, dramatically reducing the time required for message generation at scale.
Data Source
AI summary
Systems, apparatus, articles of manufacture, and methods to generate customized customer messages are disclosed. An example method includes selecting a prompt template based on an intended purpose of the customized customer message and a type of communication of the customized customer message, generating a prompt based on the customer data for an identified customer and the prompt template, providing the prompt to a large language model to cause generation of the customized customer message, and causing transmission of the customized customer message.