Developing Personalized Marketing Service Using Generative AI

Gun Ho Lee

doi:10.1109/ACCESS.2024.3361946

2024-01-01

DOI：10.1109/ACCESS.2024.3361946

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摘要

En 中文

In today's world, the development of social network services (SNS) like Facebook and Instagram has enabled consumers to acquire information about products through various channels. The acquisition of diverse information has led to a diversification in consumer preferences and requirements. As consumer preferences diversify and online channels expand, there is an increasing need for companies to provide personalized marketing. Among the means of personalized marketing, personalized marketing messages are a key tool that can enhance customer engagement. However, a limitation of personalized marketing message services is the cost issue associated with manually writing individual marketing messages for personalization. To solve this problem, when developing automated technology for personalized marketing messages, there were concerns about the complexity of model development and the quality of messages generated automatically. In this study, we propose the Persuasive Message Intelligence (PMI) service, which utilizes the recently prominent Large Language Model for automated individual personalized marketing messages. PMI generates marketing messages through prompt engineering based on the theory of persuasion in marketing and prior research on AI-generated messages, and validates the elements of prompts through surveys. The trial and error of researchers presented in this study, along with the know-how and rules of prompt engineering, will serve as guidelines for those who wish to develop services through prompts in the future.

Keyword:

Generative AI

Business

Generative adversarial networks

Artificial intelligence

personalized marketing message

persuasion theory

prompt engineering