Leveraging Large Language Models for Navigating Brand Territory

There is huge untapped potential for the application of Large Language Models in the fields of marketing and advertising. In this work, we describe an approach to automate the generation of brand territory maps, a visualization used by advertising strategists to understand how a brand is perceived by consumers and differentiated from its competitors. We collect a Household Item data set with product reviews to exemplify our approach. We elicit customer perceptions from ChatGPT with regards to certain dimensions, viz., esteem, reliability, modernity, quality and relevance. By analyzing customer reviews using this Large Language Model, we show that it is possible to get a broader view of how consumers perceive specific aspects of certain products or brands in an automated fashion. We perform an empirical evaluation to compare the brand territory maps generated using our approach and those generated by humans. We find that (1) Human responses have significantly more variation than those by ChatGPT; (2) Making small adjustments to the ChatGPT prompt can result in stark differences in results; (3) Our approach is extremely cost effective compared to that of using humans to generate brand territory maps; and that (4) The brand territory maps generated using our approach are comparable to those generated by humans.