Customer relationship management and big data enabled: Personalization &amp; customization of services

Anshari, Muhammad; Almunawar, Mohammad Nabil; Lim, Syamimi Ariff; Al‐Mudimigh, Abdullah S.

doi:10.1016/j.aci.2018.05.004

Cited by 299 publications

(200 citation statements)

References 27 publications

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“…In education, especially higher education, most of them adopted it to support the learning and teaching process. Regarding integral part of teaching and learning activities by the use of technologies, the current educational development ensures the student-centered teaching practices to enable them to get improve in supporting active students' learning [11]. Moreover, integrating technology in education can facilitate the performance of learning and teaching through improving the technological application with its management and skills [12].…”

Section: Introductionmentioning

confidence: 99%

Exploring Adaptive Teaching Competencies in Big Data Era

Huda¹,

Maseleno

Shahrill³

et al. 2017

Int. J. Emerg. Technol. Learn.

122

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Abstract-in the last decade, the adoption of digital tool to support educational process has been emerged among the universities around the world. In big data era, the demand to utilize it in adaptive teaching should be considered to enable the teaching performance especially in accessing the resources. This paper aims to explore the framework model as a way for teachers in adapting big data to help their teaching performance especially in accessing the resources. The literature review was conducted from peer review journals, books and conferences. The findings reveal that process and management skills should be engaged into adaptive teachings competencies. It included commitment in planning, time management, and technology skills. This study is expected to contribute in strengthening teaching performances in the application guideline in the big data era to support assessing the multi-channels of sources of knowledge to extract new insights of value in exploring the adaptive teaching competencies.Keywords-Adaptive teaching competency, big data, Process and management skills 68

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Section: Introductionmentioning

confidence: 99%

Exploring Adaptive Teaching Competencies in Big Data Era

Huda¹,

Maseleno

Shahrill³

et al. 2017

Int. J. Emerg. Technol. Learn.

122

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“…"Customers voluntarily generate a huge amount of data daily by detailing their interest and preference about products or services to the public through various channels." [62] Profiling for customers becomes important for business to make sure that the whole CRM life cycle (sales, marketing, and customer service) is offering personalized and customized services, so that each customer will have a different experience according to their needs and interest. [62] Lifecycle marketing is also known as a field of action in CRM.…”

Section: ) Marketing Intelligence As Customized Lifecycle Marketingmentioning

confidence: 99%

“…[62] Profiling for customers becomes important for business to make sure that the whole CRM life cycle (sales, marketing, and customer service) is offering personalized and customized services, so that each customer will have a different experience according to their needs and interest. [62] Lifecycle marketing is also known as a field of action in CRM. Its goal is to build long-term customer loyalty to the company and its employees by considering the various specific life situations and phases of the customers.…”

Section: ) Marketing Intelligence As Customized Lifecycle Marketingmentioning

confidence: 99%

Marketing Intelligence and Big Data: Digital Marketing Techniques on their Way to Becoming Social Engineering Techniques in Marketing

Lies¹

2019

IJIMAI

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This section introduces marketing from a digital-technological point view, following the popular digitalization processes of corporations. This review thus also describes the current landscape of digital marketing. Digitalization is supposed to be "unavoidable" [2], i.e. it becomes the foundation of applied marketing. With regards to digital marketing in combination with web-based services, marketers are experiencing an epoch "(…) of technology explosion and easy access to it by consumers (…)." [3] 1) Marketing Intelligence as IT-marketing and Big Data Marketing The introductory part of this paper concentrates on the term "marketing intelligence" in order to trace the path from digital data techniques to social engineering. The term "intelligence" is anything but new. As early as the 1960s, Kelley formulated the significance of marketing intelligence for management in the age of the information revolution. Even then, an increase in data volumes had been diagnosed [4]: Market information can be compared with that of military intelligence services. Top management staff must set up information channels at all data collection points. He proposes to create a novel position of "vice

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“…Socialinių tinklų generuojami duomenys gali būti naudojami sudarant vartotojų profilius, nes suteikia galimybę sekti vartotojo viešai reiškiamą nuomonę bei elgseną internetinėje erdvėje (Pennacchiotti ir Popescu, 2011). Remdamasi vartotojų profiliu, įmonė gali personalizuoti reklaminius pranešimus potencialiems klientams (Anshari et al, 2018). Vartotojų profiliai taip pat gali būti naudojami reklaminėms žinutėms pritaikyti (angl.…”

Section: Socialinių Medijų Generuojamų Didžiųjų Duomenų Panaudojimo Gunclassified

Didžiųjų Duomenų Panaudojimas Socialinėje Medijoje / the Big Data Use in Social Media

Karpovičiūtė

Sabaitytė

2019

Science - Future of Lithuania

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The digital revolution and the communication platforms provided by the web 2.0 virtual space era, such as social media, social networks, other tools and channels, create new opportunities for better marketing decisions based on user-generated data analysis. Every day customers of social media and other virtual tools are creating huge amounts of their actions caused data, and business lack management tools for the support of this process, which could create knowledge in the area of customer profiles and preferences deeper cognition. Growing numbers of social media users indicate the popularity of these communication tools among the information society, but science today lacks a deeper knowledge of social media generated data and other algorithms for this data usage. Therefore, the purpose of the article is defined as the development of the conceptual model of big data generated by social media usage in business. The formation of the conceptual model is based on the analysis of big data assumptions and application possibilities, social media classification peculiarities and different channel specifics, identification of big data analysis methods and analysis of large data applications generated by social media. The conceptual model creates preconditions for deeper knowledge of user-generated big data in nowadays widely used communication platforms, as well as creation of the decision support tool for marketing specialists in order to use big data from social media in deeper customer profile and preferences cognition. Methods employed in this research are: literature and other references analysis, synthesis and logical analysis of information, comparison of information, systemization and visualization.

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Customer relationship management and big data enabled: Personalization & customization of services

Cited by 299 publications

References 27 publications

Exploring Adaptive Teaching Competencies in Big Data Era

Exploring Adaptive Teaching Competencies in Big Data Era

Marketing Intelligence and Big Data: Digital Marketing Techniques on their Way to Becoming Social Engineering Techniques in Marketing

Didžiųjų Duomenų Panaudojimas Socialinėje Medijoje / the Big Data Use in Social Media

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