MARKETING REEVALUATED-PROPOSING COMPUTER ASSISTED GENERATION OF ONLINE SELLER MARKETING CONTENT

Abstract

The rapidly advancing online marketplace necessitates adaptation from sellers and consumers alike. Oftentimes in established markets,  sellers without grand funding or an extremely experienced marketing team will struggle despite offering products of equal or greater value than established competitors. This research paper presents a complete methodology, harnessing data mining, AI, and statistical techniques, for inexperienced sellers to augment their marketing copy and produce high-level, competitive marketing content. With the aid of existing materials and research, this paper’s proposed model can offer a balancing factor between new and established sellers in the constantly evolving  online market.