arXiv:2606. 00169v1 Announce Type: cross Abstract: Increased competition and the growing similarity of products and services offered by retailers have lowered the barriers for customers to switch to competitors.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2606. 06776v1 Announce Type: new Abstract: Customer churn prediction is a central task in customer analytics, particularly in non-contractual, pay-per-use service environments where disengagement is not explicitly observed and must be inferred from behavioral inactivity.
arXiv:2606. 07582v1 Announce Type: cross Abstract: Customer churn prediction is essential across data-driven industries such as insurance, digital banking, eCommerce, and subscription platforms, where retaining existing customers is typically more cost-effective than acquiring new ones.
arXiv:2607. 10260v1 Announce Type: new Abstract: Customer churn is a major challenge for telecommunication companies, directly eroding revenue and long term customer relationships.
arXiv:2606. 17931v1 Announce Type: new Abstract: In recent years, electronic (E) commerce services have rapidly increased in the daily lives of people, which helpsthem to purchase products online.
arXiv:2608. 12007v1 Announce Type: cross Abstract: Consumer reviews play an important role in shaping brand perception and business strategies, particularly in service-driven industries such as retail coffee.
Consumer reviews play an important role in shaping brand perception and business strategies, particularly in service-driven industries such as retail coffee. This study presents a comparative sentiment analysis framework for Starbucks customer reviews using classical machine learning and deep learning approaches.