Applications of Text Generation in Digital Marketing: a review

Abstract

Billions of dollars are spent each year on different aspects of digital marketing. Automating some of its processes has become crucial to keep up with the volume of offers put online every day. With that being said, textual advertising content plays a major role in attracting converting customers; that is why integrating Text Generation could have high impact benefits on the entire marketing activity. Marketing text could be produced quicker and with a higher quality that is modeled after content that has already demonstrated good results. This paper focuses on Text Generation under Artificial Intelligence, and contains a summarization of the different types of Text Generation, such as Text-to-Text that covers Text Summarization, Dialogue Systems and Machine Translation, Visual-to-Text, and Data-to-Text. This paper also discusses the different techniques used in Text Generation, including Word2vec, GloVe and fastText, RNNs, CNNS, VAEs, and GANs. In addition, it encloses a review on research that's been previously conducted on the matter in Digital Marketing, along with the results, and a comparison of it all.