Nuremberg Institute for Market Decisions’ Post

While many have been amazed by the abilities of Open AI’s chatbot, LLMs should “more appropriately be viewed as ‘stochastic parrots’ or eager-to-please interns”, according to David Schweidel, Martin Reisenbichler and Thomas Reutterer in the latest NIM Marketing Intelligence Review. Is #ChatGPT simply not good enough anymore? And if so, how can automated content creating improve the marketing of today? To properly use #LLMs’ capabilities, they need to be trained for the context they are going to be used in. If this is done right, these LLMs can filter previously developed content and use only that which has been deployed successfully for a particular task. The authors explain in their article how LLMs can be customized by adding context-specific information and human editing, creating a (semi)automated #SEO content writing machine: 👨🏫 Specification of keywords: should be provided by human experts 👩🏫 Content search: capturing of top-ranking search engine results, scraping of content from these links 👨🏫 AI-generated content: training of AI through scraped content, generating of contextually relevant content, measuring of content quality on multiple dimensions 👩🏫 Text selections: human editor provides ordered list of content (top ten texts) Schweidel, Reisenbichler and Reutterer emphasize how even with this more elegant approach, human editors still are an integral part of the content creation process. “While LLMs enable us to offload a good portion of the work, marketing still requires a human touch.” To find out more about the authors’ research, the feedback to their SEO content writing machine and the future of LLMs in marketing, read the article for free here: https://lnkd.in/g6Rx8KiB Schweidel, D., Reisenbichler, M., & Reutterer, T. (2024). Moving Beyond ChatGPT: Applying Large Language Models in Marketing Contexts. NIM Marketing Intelligence Review, 16(1) 24-29. #LargeLanguageModels #ContentMarketing #SearchEngineOptimization #HumanMachineCollaboration

Moving Beyond ChatGPT: Applying Large Language Models in Marketing Contexts

Moving Beyond ChatGPT: Applying Large Language Models in Marketing Contexts

nim.org

To view or add a comment, sign in

Explore topics