Nowadays, a relationship with a customer is established and developed mostly online. This provides additional potential but also poses many challenges to organizations. Every day, a customer performs transactions, leaves likes, comments, reviews on various portals. Tremendous amount of customer data is stored in cookies when websites are visited, calls to helpdesk and chats with online assistants are recorded, etc. The data on customer is available in various information systems, in website logs, in cookies, in emails, on the company’s Facebook profile. It is, however, often not used properly. Companies are missing out on potential to build long lasting relations with him. This data is often marginally analyzed or used for the needs of sending personalized newsletters. During the workshop, we would like to explore this topic with a special emphasis on challenges and technologies that may help to address these challenges in the context of building loyalty, i.e. expanding business possibilities. Therefore, the communities that are expected to attend the workshop are twofold: on one hand this is marketing community dealing with the topic of building customer loyalty and on the other hand information systems/computer science experts processing the data of customers for the needs of profiling (based on various sources and applying diverse methods). The workshop is to establish a venue for discussion and future collaboration on the topic. Such a mix of attendees is also assured by members of the Organizing Committee who represent these communities. The geographical distribution of both Organizing Committee and Programme Committee members will assure that the session will have international flavor, representing not only different communities but also diverse geographical locations.
Topics include but are not limited to:
Profiling of customers based on their presence on Social Media. Inferring personality traits and customer behavior.
Profiling of customers in omnichannel commerce. Smart environments: modelling people, things and their relations.
Modelling relations between people on the Web. Identification of influencers and weak ties.
Discovering communities in social networks.
Social data mining. Social networks intelligence. Value of social network data.
Loyalty building. Migration of customers.
Building and maintaining loyalty of purchasing algorithms.
Loyalty of automated customers.
Big Data for analyzing of customers’ activities.
Linking data sources on customer.
Sentiment analysis of posts, reviews, ratings, etc.
Personalization for search and service/product design and development.
Tools for profiling, analytics in e-Marketing.
Privacy and trust in e-Marketing.
Profiling customers in autonomous shopping agents.
Marketing to machines: Device as a Customer.
08月23日
2017
08月26日
2017
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