Quotation Reisenbichler, Martin, Reutterer, Thomas, Schweidel, David, Dan, Daniel. 2021. Supporting Content Marketing with Natural Language Generation. 43rd ISMS Marketing Science Conference, New York, United States/USA, 03.06.-05.06.




Advances in natural language generation (NLG) have facilitated technologies such as digital voice assistants and chatbots. In this research, we demonstrate how NLG can support content marketing by using it to draft content for search engine optimization (SEO). Traditional SEO projects rely on hand-crafted content that is both time consuming and costly to produce. To address the costs associated with producing SEO content, we propose a semi-automated methodology using state-of-the-art NLG and demonstrate that the “content writing machine” can create unique, human-like SEO content. Comparing the resulting content with human refinement to traditional human-written SEO texts, we find that the revised, machine-generated texts are virtually indistinguishable from those created by SEO experts. We conduct field experiments in two industries to demonstrate our approach and show that the resulting SEO content outperforms that created by human writers (including real SEO experts) in search engine rankings and website engagement. Additionally, we illustrate how our approach can substantially reduce the production costs associated with content marketing, increasing their return on investment.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title Supporting Content Marketing with Natural Language Generation
Event 43rd ISMS Marketing Science Conference
Year 2021
Date 03.06.-05.06
Country United States/USA
Location New York
URL https://www.abstractsonline.com/pp8/#!/9305/presentation/520


Reisenbichler, Martin (Details)
Reutterer, Thomas (Details)
Dan, Daniel (Details)
Schweidel, David (Emory University Goizueta Business School, United States/USA)
Institute for Marketing and Customer Analytics IN (Details)
Google Scholar: Search