Essays about: "CRM#"

Showing result 1 - 5 of 214 essays containing the word CRM#.

  1. 1. SIMULATION TRAINING: FROM THE STUDENTS' POINT OF VIEW

    University essay from

    Author : Hygrell Sandra; Alexandra Jernstedt; [2023-03-16]
    Keywords : ;

    Abstract : Background: Simulation training is a well-grounded concept that is used to increase and maintain safety in various industries such as aviation, military, and health care. Simulation training is today an integrated part of the Bachelor programme in nursing. READ MORE

  3. 2. "How can tech startups enhance their customer retention and acquisition

    University essay from Högskolan i Gävle/Avdelningen för ekonomi

    Author : Danut Avram; Oluwadamilola Olaitan; [2023]
    Keywords : Customer retention; Customer acquisition; Social media marketing; User engagement; Brand awareness; Tech startups; Customer relationship management CRM ; Trust; Targeted advertisement.;

    Abstract : This  research  emphasizes  the role  of  social  media  in  customer  acquisition  retention.Furthermore, it investigates insights that have the potential to benefit tech startups inshaping  their  strategies  and  effectively  allocating  resources  to  achieve  consistentcommunication with their customer base. READ MORE

  4. 3. eCRM PERSONALIZATION STRATEGIES : Influence of content personalization on consumer engagement performance of email marketing campaigns

    University essay from Jönköping University/Internationella Handelshögskolan

    Author : Daniela Rodriguez; [2023]
    Keywords : CRM; email marketing; content personalization;

    Abstract : Background: As personalization has become a common CRM strategy for companies to create valuable relationships with customers, users are receiving an increased amount of personalized communication, further research is needed on the influence of content personalization in specific channels, to improve customer engagement.  Purpose: This paper seeks to analyse the influence of eCRM content personalization strategies on the consumer engagement performance of email marketing campaigns building upon existing knowledge about the benefits and opportunities of personalization strategies. READ MORE

  5. 4. Prediction Models for TV Case Resolution Times with Machine Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Borja Javierre I Moyano; [2023]
    Keywords : Datasets; Machine Learning ML ; Prediction; Resolution Time RT ; Solve Time; TV Cases; Trouble Tickets TT ; Customer-Related Trouble Tickets Resolution Time; CRM system; BI system; Telecommunications; Dataset; Machine Learning ML ; Prediction; Resolution Time; Solve Time; TV Cases; Trouble Tickets TT ; Kundrelaterade problem Tickets Resolution tid; CRM-system; BI-system; Telekommunikationer.;

    Abstract : TV distribution and stream content delivery of video over the Internet, since is made up of complex networks including Content Delivery Networks (CDNs), cables and end-point user devices, that is very prone to issues appearing in different levels of the network ending up affecting the final customer’s TV services. When a problem affects the customer, and this prevents from having a proper TV delivery service in devices used for stream purposes, the issue is reported through a call, a TV case is opened and the company’s customer handling agents start supervising it to solve the problem as soon as possible. READ MORE

  6. 5. A Predictive Analysis of Customer Churn

    University essay from KTH/Matematisk statistik

    Author : Olivia Eskils; Anna Backman; [2023]
    Keywords : Churn prediction; CRM; optimization; applied mathematics; machine learning; gradient boosting; random forest; logistic regression; insurance industry; Kundbortfall; CRM; optimering; tillämpad matematik; maskininlärning; gradient boosting; random forest; logistisk regression; försäkringsbranschen;

    Abstract : Churn refers to the discontinuation of a contract; consequently, customer churn occurs when existing customers stop being customers. Predicting customer churn is a challenging task in customer retention, but with the advancements made in the field of artificial intelligence and machine learning, the feasibility to predict customer churn has increased. READ MORE