Artifical Intelligence and CRM

2022 ◽  
pp. 92-114
Author(s):  
Shailja Dixit
Keyword(s):  
Customer Service ◽  
Data Analytics ◽  
Business Models ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Disruptive Technologies ◽  
Artifical Intelligence ◽  
Customer Lifetime ◽  
Customer Care ◽  
Transformation Potential

Disruptive technologies such as IoT, big data analytics, blockchain, and AI have changed the ways businesses operate, with AI holding immense marketing transformation potential. AI is influencing marketing strategies, business models, sales processes, customer service options, and customer behaviors. AI-CRM's improving ability to predict customer lifetime value will generate an inevitable rise in implementing adapted treatment of customers, leading to greater customer prioritization and service discrimination in markets. CSPs are working through the challenging process of digital transformation, driven by the need to compete with fast-moving OTT and consumer tech players. CSPs need to move quickly and can advance digital transformation with solutions that leverage AI which can drive value across the business from network optimization and data analytics through to customer care and marketing engagement. The chapter tries to identify how AI is impacting the CRM in the telecom industry and leveraging the benefits of this technology for better customer management and growth.

scholarly journals IMPACT OF DISRUPTIVE TECHNOLOGY ON THE PERFORMANCE OF INSURANCE FIRMS IN KENYA

2018 ◽  
Vol 3 (1) ◽  
pp. 72
Author(s):  
Ezekiel Owuor
Keyword(s):  
Big Data ◽  
Financial Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Disruptive Technology ◽  
Regulatory Body ◽  
Disruptive Technologies ◽  
Insurance Firms ◽  
Pdf Format ◽  
The Impact

Purpose:  The purpose of this paper was to explore the impact of disruptive technology on the performance of insurance firms in Kenya.Methods: The study utilized desktop literature review and focused on previously published journals in PDF format that address technology and the performance of insurance firms.  A total of 13 journals was found relating to technology and the performance of insurance firms. The study utilized a sample of 12 journals which were randomly selected from a list of published journals in PDF format relating to disruptive technology and performance of insurance firms. The theories underpinning of the study entailed Christensen's Theory of Disruptive Technology, the Diffusion of Innovation Theory and Schumpeterian Theory of Creative Destruction.Results: The review of literature revealed that various aspects of disruptive technology have a significant impact on organizational performance. The review showed that mobile phone technology has a significant influence and explains to a large extent the growth of micro insurance in Kenya. It was also found that the increase in industrial convergence, technological innovation and social digital trends increases the financial performance of financial institutions including insurance firms. The study also established that there is a strong and positive relationship between insurance innovation strategies and a firm’s performance. In addition, it was found out that real-time business evaluation through big data analytics boosts overall performance and profitability, thus thrusting the organization further into the growth cycle.Unique Contribution to theory, practice and policy: The leadership and management of insurance companies should put greater emphasis on the adoption of disruptive technologies to improve on both financial and non-financial performance as well as their competitiveness within the industry. These include Big Data, Analytics, Artificial Intelligence Systems, Cloud Computing and Digital Currency Technologies. Processes in the organizations should be refined to ensure that they are efficient and effective as this serves to increase market share and to reduce on operational costs. Moreover, explorations in disruptive technology should continue in the insurance industry as these would play a significant role in ensuring that efficiencies and effectiveness of business processes are achieved. The Insurance Regulatory Authority (IRA) should also develop policies that encourage innovation and the adoption of technology. The authority whilst exercising due diligence in its mandate to protect consumers should ensure policies do not stifle the growth and creativity of insurers. The regulatory body should also strive to create a favourable environment for the adoption of disruptive technologies.

Improving Forecasting for Customer Service Supply Chain Using Big Data Analytics

2018 ◽  
pp. 25-41 ◽  
Author(s):  
Kedareshwaran Subramanian ◽  
Kedar Pandurang Joshi ◽  
Sourabh Deshmukh
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Customer Service ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Resource Planning ◽  
Road Map ◽  
Service Supply Chain ◽  
Data Ecosystem ◽  
Manufacturing Organization

In this book chapter, the authors highlight the potential of big data analytics for improving the forecasting capabilities to support the after-sales customer service supply chain for a global manufacturing organization. The forecasting function in customer service drives the downstream resource planning processes to provide the best customer experience at optimal costs. For a mature, global organization, its existing systems and processes have evolved over time and become complex. These complexities result in informational silos that result in sub-optimal use of data thereby creating inaccurate forecasts that adversely affect the planning process in supporting the customer service function. For addressing this problem, the authors argue for the use of frameworks that are best suited for a big data ecosystem. Drawing from existing literature, the concept of data lakes and data value chain have been used as theoretical approaches to devise a road map to implement a better data architecture to improve the forecasting capabilities in the given organizational scenario.

scholarly journals Digital transformations of logistics customer service business models

2020 ◽  
pp. 57-75
Author(s):  
Mariia Hryhorak ◽  
Natalia Trushkina ◽  
Tadeusz Popkowski ◽  
Kateryna Molchanova
Keyword(s):  
Information And Communication Technologies ◽  
Customer Service ◽  
Business Models ◽  
Customer Orientation ◽  
Synergetic Effect ◽  
Digital Transformation ◽  
Customer Relationship ◽  
Management Tool ◽  
Mutual Relations ◽  
Marketing Information

The article presents the results of expert surveys conducted by international organizations as a method of empirical research to identify current problems, features and trends of customer-oriented logistics services to consumers in the context of digital space. The statistical analysis of the indicators characterizing the level of use of information and communication technologies at management of mutual relations with consumers at the Ukrainian enterprises is executed. The key barriers that hinder the digital transformation of the logistics service have been identified, which are conditionally classified into 6 groups: trading, transport, marketing, information, organizational and financial and economic. The content structure of CRM-system implementation as a customer relationship management tool is proposed. The expediency of the complex approach application to digital transformation of consumers logistic service on the basis of customer orientation is substantiated and the formula of an estimation of synergetic effect from its realization is offered.

scholarly journals Artificial intelligence and machine learning: changing paradigm in diagnostics and imaging

2019 ◽  
Vol 8 (1) ◽  
pp. 382
Author(s):  
Rahul Badwaik
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Setting ◽  
Digital Transformation ◽  
Current Status ◽  
Healthcare Industry ◽  
Review Of The Literature

Healthcare industry is currently undergoing a digital transformation, and Artificial Intelligence (AI) is the latest buzzword in the healthcare domain. The accuracy and efficiency of AI-based decisions are already been heard across countries. Moreover, the increasing availability of electronic clinical data can be combined with big data analytics to harness the power of AI applications in healthcare. Like other countries, the Indian healthcare industry has also witnessed the growth of AI-based applications. A review of the literature for data on AI and machine learning was conducted. In this article, we discuss AI, the need for AI in healthcare, and its current status. An overview of AI in the Indian healthcare setting has also been discussed.

Big data analytics for investigating Taiwan Line sticker social media marketing

2019 ◽  
Vol 32 (2) ◽  
pp. 589-606 ◽  
Author(s):  
Shu-Hsien Liao ◽  
Szu-Yu Hsu
Keyword(s):  
Social Media ◽  
Big Data ◽  
Business Model ◽  
Data Analytics ◽  
Business Models ◽  
Model Development ◽  
Big Data Analytics ◽  
Social Media Marketing ◽  
Content Type ◽  
Purchase Behaviors

Purpose Line sticker, a social media, it allows users to exchange multimedia files and engage in one-to-one and one-to-many communication with text, pictures, animation and sound. The purpose of this paper is to examine various Taiwan user experiences in the Line sticker use behaviors. Further, this research looks at how the situations of Line sticker proprietors and their affiliates are disseminated for formulating social media marketing (SMM) in its business model concerns. Design/methodology/approach This study examines the experience of various Taiwanese Line stickers users utilizing a market survey, a total of 1,164 valid questionnaire data, and the questionnaire is divided into five sections with 30 items in terms of the database design. All questions use nominal and order scales. This study develops a big data analytics approach, including cluster analysis and association rules, based on a big data structure and a relational database. Findings The authors divide Taiwan Line sticker users into three clusters by their profiles and then find each group’s social media utilization and online purchase behaviors for investigating the Line sticker SMM and business models. Originality/value This is the first study to offer a big data analytics to investigate and analyze the varieties in the use of Line sticker by exploring users’ behaviors for further SMM and business model development.

Big Data In Banking: A Bird’s Eye View

GIS Business ◽  
2020 ◽  
Vol 14 (6) ◽  
pp. 1129-1139
Author(s):  
C. RADHA PRIYA ◽  
KANNIGA PRASHANTH
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Banking Industry ◽  
Big Data Analytics ◽  
Customer Segmentation ◽  
Customer Relationship ◽  
Risk Modeling ◽  
Customer Data ◽  
Customer Lifetime ◽  
Big Data Application

Banking industry is the backbone of any economy. It plays a very significant role in leading the country towards the growth path by improving the gross capital formation, which consecutively improves the GDP. Success of the banking industry depends on its ability to serve its customers efficiently and expeditiously. The functionality of the CRM (Customer Relationship Management) can be effectuated by felicitous use of customer data. Banks have voluminous data about their customers, which most of the banks failed to utilize in a well-timed manner. Banks can fortuitously satisfy their customers by offering much personalized and focused services by pursuing big data analytics and other hi-tech tools or applications. Big data analytics can be actuated in key areas like customer segmentation, offering customer lifetime value, fraud detection, risk modeling, etc. Preeminent banks in the industry are utilizing big data to leverage the accumulated customer data for improvising their services. Big data offers a promising scope of ventures to banks which consider it strategically. This article is attempts to present an overview of the big data application in the banking industry.

Positioning big data analytics capabilities towards financial service agility

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abeeku Sam Edu
Keyword(s):  
Big Data ◽  
Financial Services ◽  
Data Analytics ◽  
Business Models ◽  
Empirical Test ◽  
Big Data Analytics ◽  
Predictive Modelling ◽  
Financial Service ◽  
Content Type ◽  
It Capability

PurposeEnterprises are increasingly taking actionable steps to transform existing business models through digital technologies for service transformation such as big data analytics (BDA). BDA capabilities offer financial institutions to source financial data, analyse data, insight and store such data and information on collaborative platforms for a quick decision-making process. Accordingly, this study identifies how BDA capabilities can be deployed to provide significant improvement for financial services agility.Design/methodology/approachThe study relied on survey data from 485 banking professionals' perspectives with BDA usage, IT capability development and financial service agility. The PLS-SEM technique was used to evaluate the underlying relationship and the applicability of the research framework proposed.FindingsBased on the empirical test from this study, distinctive BDA usage grounded on the concept of IT capability viewpoint proof that financial service agility could be enhanced provided enterprises develop technical capabilities alongside other relevant resources.Practical implicationsThe study further highlights the need for financial service managers to identify BDA technologies such as data mining, query and reporting, data visualisation, predictive modelling, streaming analytics, video analytics and voice analytics to focus on financial knowledge gathering and market observation. Financial managers can also deploy BDA tools to develop a strategic road map for data management, data transferability and knowledge discovery for customised financial products.Originality/valueThis study is a useful contribution to the burgeoning discussion with emerging technologies such as BDA implication to improving enterprises operations.

Much- needed business digital transformation through big data, internet of things and blockchain capabilities: implications for strategic performance in telecommunication sector

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anam Bhatti ◽  
Haider Malik ◽  
Ahtisham Zahid Kamal ◽  
Alamzeb Aamir ◽  
Lamya Abdulrahman Alaali ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Quality ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Equation Modeling ◽  
Content Type ◽  
Strategic Performance ◽  
Dependent Variables

PurposeIn the field of business, digital transformation is the integration of digital technology into all areas of business, from generating to deliver value to customers. This concept is essential for sustainable growth of a company and its overall economy. Based on this fact, this authentic and informative research is conducted whose major aim is to examine the importance of digital transformation within a business through big data, the Internet of things and blockchain-based capabilities for overall strategic performance within the telecom sector in China.Design/methodology/approachFor that aim, data quality and technology competence are considered as independent variables, strategic performance as dependent variable and big data analytics capabilities, Internet of things capabilities and blockchain capabilities routinization acted as mediators within this paper. In its data collection mechanism, an online survey was conducted in which questionnaires are randomly distributed to the telecom sector's professionals in which only 343 of them gave their valid outcomes. After collecting primary data, confirmatory factor analysis (CFA) and structural equation modeling (SEM)–based statistical outcomes have been generated.FindingsResults indicate that there is a significant relationship between data quality and strategic performance and between technological competence and strategic performance. Also, the big data analytics and Internet of Things capabilities acted as significant mediating role between both independent and dependent variables. But blockchain capabilities routinization is that variable that acts as an insignificant mediator between independent and dependent variables' relationship.Originality/valueOverall, this study is an informative and attractive source for the Chinese government, its telecom industry, administrative body and related ones to understand the importance of such IT capabilities' implications within their operating activities for their strategic performance management. Also, related field scholars can utilize its reliable data in their research analysis. Its major limitations are (1) lack of qualitative/ mixed method of research and (2) lack of comparative analysis that may impact the acceptability factor of this paper, and this weakness can be overcome by upcoming scholars in their research.

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