Social media and customer behavior analytics for personalized customer engagements

摘要: Companies in various industries, including travel, hospitality, and retail, increasingly focus on improving customer relationships loyalty. In this paper, we propose a new systems architecture that combines the textual content social media messages with product information, such as descriptions summarized catalogs, order to provide marketing campaign recommendations. commonly build user profiles based purchase histories other customer-specific information; however, when dealing media, often cannot match users customers. regard, address problem of targeting individual for which no personalized profile information can be retrieved. Our solution two disparate computational toolboxes text analytics—natural language processing machine learning—in select whom target topic-specific advertisements. Natural is used analyze context messages, learning goal being products ranking potential To demonstrate framework, detail real-world application travel tourism industry using Twitter® platform.