An Ontology Based Approach for Next Generation Customer Relationship Management Systems

Abstract

Customer relationship management -CRM systems aim to increase customer satisfaction and loyalty to the company through actions that can be performed by monitoring and analyzing customer behaviours for companies. In these systems, the data obtained from different sources such as sales process, service, and call center are interpreted by the CRM experts as a whole, and the necessary action is taken for the customer. With the rapid progress in information technologies, the diversity of channels that are used to collect data, the size and dynamism of the data have increased. This situation has made it impossible for experts to wholly interpret big-size data from a wide variety of sources in a short period of time. In the CRM area, there is a need for technologies that automatically integrate the data obtained from several sources and can interpret it semantically. In this study, an ontology-based approach is proposed, which allows automatic semantic interpretations on the data obtained from different sources. Based on the proposed approach, a tool has been developed that can unify data from different CRM systems in a common format and make customer-centric interpretations of this data. The tool continuously monitors the systems it is integrated with, and when it detects the conditions defined by the users on the data, it can automatically perform the actions determined by the users. The tool developed was experienced by integrating a CRM system of a company and the evaluation results obtained in this process were discussed.

Application of Semantic Web Technologies for Supporting Customer Relationship Management: a Systematic Literature Review

“…OWL, WSDL (Magro and Goy, 2012) O-CREAM-v2 ontology can find application in web-based repositories supporting the mediation of the supply and demand of CRM-related tools. OWL (Tiryaki and Atalay, 2020) CRM ontology enables automatic semantic interpretations of data received from various sources (such as sales process, service and call centre). OWL, SPARQL, SWRL (Fernández-Cejas et al, 2022) CRM ontology supports managers and information systems' specialists in the development and maintenance of applications.…”

“…(Picot-Clémente et al, 2010), (Liang et al, 2011), (Tiryaki and Atalay, 2020) From the data represented in Figure 3, Tables 2 and 3, it stands out that the main application of Semantic web technologies to support CRM consists in building appropriate ontologies. SPARQL queries, Linked data, SWRL are mainly used to browse and extract data from them.…”

“…Improved pricing 1 (Wang and Zhou, 2014) Improved sales force efficiency and effectiveness 1 (Hladky et al, 2014) Improved products and services 2 (Alfrjani et al, 2016), (Ali et al, 2020) Innovative products and services 1 (Kudryavtsev et al, 2020) Customer complaint management 2 (Jarrar et al, 2003), (Thakor and Sasi, 2015) Customer segmentation 1 (Yılmaz and Alptekin, 2013) Supporting users of CRM systems 11 (Osterwalder and Pigneur, 2002), (Gottgtroy and Gottgtroy, 2003), (Osterwalder and Pigneur, 2003), (Caliusco et al, 2004), (Damme et al, 2007), (Yan and Zha, 2010), , (Wu, 2012), (Tiryaki and Atalay, 2020), (Blankenberg et al, 2022), (Fernández-Cejas et al, 2022) Supporting CRM projects 1 (Lee et al, 2007) Integration of information in a CRM system 2 (Hladky and Maltseva, 2013), (Tiryaki and Atalay, 2020) Description of business processes 2 (Goy et al, 2008), (Magro and Goy, 2012) Personalization of business processes 1 (Liang et al, 2011) Social branding 1 (Zailskaitė-Jakštė and Damaševičius, 2014) From the data represented in Table 4, it can be concluded that each of the listed CRM benefits B1-B8 is addressed in at least one study selected for the systematic literature review.…”

“…Integration of information in a CRM system; In (Hladky and Maltseva, 2013), the integration of information needed for the purposes of the CRM process using linked data is proposed. Tiryaki and Atalay (2020) describe an ontological approach that enables automatic semantic interpretations of data obtained from different sources (such as sales process, service and call centre). Based on the proposed approach, a tool is developed that can combine data from different CRM systems in a common format and make customer-oriented interpretations of these data.…”