Big data in marketing literature

Pınarbaşı, Fatih; Canbolat, Zehra Nur

doi:10.36096/ijbes.v1i2.107

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Benzer şekilde pazarlama alanında da çalışmalar artmaktadır. (Pinarbasi & Canbolat, 2019) akademik anlamdaki bu ilgi, dolaylı veya doğrudan alanın yansımalarını göstermektedir.…”

Section: İşletmelerde Büyük Verinin Kullanımıunclassified

Turizm İşletmelerinde Marka Kişiliğinin Duygu Analizi Yöntemiyle Belirlenmesi

SEREN

Altıntaş

2023

International Journal of Social Inquiry

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Bilişim teknolojilerindeki hızlı gelişmeler, insanların işletmelere karşı fikirlerini sınırsızca ve hızlı bir şekilde yayabildiği internet ortamını insanların hizmetine çok geniş bir çerçevede sunmaktadır. İşletmelerin bakış açısından incelendiğinde ise, müşterilerin bu hızlı geri bildirimlerine verilecek tepkilerin de hızlı olması gerekliliğini ortaya koymaktadır. İşletme ile tüketici arasında oluşan bu hızlı etkileşim kanalı, anlam ifade eder hale geldiği noktada yeni bir çalışmayı tetiklemektedir. İşletmeler hakkında neler düşünüldüğü, internet üzerindeki yorumlardan hatta bazen sanal ortamdaki davranışlardan tespit edilmeye çalışılmaktadır. Verinin değerini artıran tüm bu olgular, işletmeler içinde sahip oldukları verileri nasıl işleyecekleri ve işledikten sonra bunları nasıl anlamlandırmaları gerektiği konularında yepyeni çalışma başlıkları açmaktadır. Müşterilerin işletmeler hakkındaki düşüncelerini eski yöntemlere göre daha hızlı toplayıp, daha hızlı işleyip daha hızlı kararlar verebilirlerse rakiplerine göre önemli avantajlar elde edebileceğini göstermektedir. Bu çalışmada, son yıllarda sıkça başvurulan duygu analizi yöntemi, farklı bir bakış açısıyla, şimdiye kadar yapılmış analiz boyutlarından daha farklı şekilde alt boyutlara ayrılarak yapılmaktadır. Çalışmada denetimli öğrenme yapabilen bir veri seti, turizm işletmelerine hizmet edebilecek alt boyutlar kapsamında, olumsuz yorumlar bir kenara ayrılarak sadece olumlu yorumlar içerisinde, müşterilerin onlara hangi marka kişiliğini atfettiğini söyleyebilmeyi hedeflemektedir.

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Section: İşletmelerde Büyük Verinin Kullanımıunclassified

Turizm İşletmelerinde Marka Kişiliğinin Duygu Analizi Yöntemiyle Belirlenmesi

SEREN

Altıntaş

2023

International Journal of Social Inquiry

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“…Big data has become one of the important tools in the field of e-commerce [1]. In recent years, the country's e-commerce has ushered in a period of rapid development, and the transaction volume and scale of e-commerce have expanded rapidly [2]. On the other hand, the huge user and product base of e-commerce requires e-commerce companies to build precision marketing systems based on user needs and potential needs.…”

Section: Introductionmentioning

confidence: 99%

Interactive Marketing E-Commerce Recommendation System Driven by Big Data Technology

Yang

Han³

2021

Scientific Programming

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This study combs through relevant literature, adopts a combination of typical sampling and random sampling, collects three big data technology-driven interactive marketing e-commerce companies in a specific period of Sina Weibo sample data for research, obtains historical information and data, and constructs a model. Through relevant analysis to eliminate invalid variables, we creatively selected three variables of Internet hot words, activities, and microtopics as independent variables and used marketing effects as dependent variables to carry out empirical analysis and study the marketing innovation of three representative companies based on big data technology. We discussed the use of self-media in interactive marketing e-commerce and the situation of marketing innovation based on self-media, focusing on the interactive relationship between marketing innovation and Internet word-of-mouth (brand image). Through research, we have derived the three-force model, which is the biggest result of this research, and provided a reference model for interactive marketing e-commerce companies to carry out follow-up marketing innovation based on the media. Limited to the level of research and ability, there are some deficiencies in the research, such as barrage marketing, big data marketing, and emotional computing, that have not been analyzed in depth. This article fully considers the dependence of small and medium e-commerce companies on e-commerce platforms in the era of big data and conducted detailed market research on their precision marketing strategies in the era of big data. This will be a new field that does not come from media marketing. This article intends to summarize a series of experiences and laws from special to general, from individuality to generality, so as to give full play to the role of personalized marketing in increasing website traffic and order conversion, in order to personalize the use of data by other e-commerce companies with marketing provides some valuable experiences and methods for reference.

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Features of Big Data market risk identification

Шандрівська¹,

Kyrylenko²

2021

SMEU

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The paper hypothesizes that the dynamic digitalization of the economy, based on the benefits of using Big data, accelerates the use in management and production processes of technologies offered by this market. However, it is noted that the acquisitions of the Big data market also exacerbate the socio- economic contradictions between countries with developed market economies and institutionally underdeveloped countries, which include Ukraine. The authors of the study proposed to identify the Big data market with such key indicators as total revenue, number of Internet users, losses of Big Data market participants from data leakage. Thus, the high rates of development of the Big data market in terms of growth of total market income in 8,03 times during 2011 — 2020 were witnessed. The main segments of the Big Data market (service segment, software segment and service segment) were identified. It is established that the largest share of the Big Data market is occupied by the services segment (37,5% in 2020). From 2021, the growth rate of the software segment is expected to exceed other segments of this market — hardware and services. The results of the analysis of the Big Data market by M. Porter’s five forces model show that the most important of the competitive forces in the market is a high level of competition, in which market participants are encouraged to focus on potential needs and expectations of their customers to strengthen bases of differentiation and clear positioning of the services. According to the results of the SWOT-analysis of the Big Data market, the following strengths were identified: business expansion due to the increase in the amount of information it owns; increasing the number of customer reviews through social networks; establishing strategic partnerships with suppliers, dealers and other stakeholders through the use of Big Data; permanent training of employees to maintain the competitiveness of organizations; established IT system of the enterprise, which promotes faster adoption of effective management decisions; high incomes due to effective management decisions, possession of market research results through Big Data technologies. The identified market opportunities are: population growth, which means an increase in the number of potential consumers and the amount of data collected; growth in the number of enterprises that implement e-commerce in their activities; growth of active consumers due to the integration of Big Data into social networks; increasing the share of automated processes, which helps reduce costs; growing popularity of IT specialization in universities; globalization of the economy, which allows companies to expand their activities to other countries. On the basis of identified strengths of the market and its capabilities, the following strategic directions of development are proposed: entry of enterprises into new markets due to market globalization and effective implementation of Big Data technologies; use of social networks to collect consumer data and involve them in Big Data processes; improvement of the e-commerce system of enterprises due to the capabilities of well-established IT systems of the enterprise with the capabilities of Big Data; reduction of product prices due to cost optimization and effective interaction with contractors. The results of the research allowed to identify the following main risks of the industry: destruction of data confidentiality; collection of false data, infringement of intellectual property of a third party, etc. The formed risk matrix indicates that the most significant risks of this market are the reduction of information security of the entity due to hacker attacks (probability of 50%, significant damage) and the destruction of data confidentiality (probability of 25%, significant damage). Qualitative interpretation of risks in the Big Data market allowed to characterize the impact of adverse factors of internal and external environments, namely: insufficient unreliability of cloud storage for data storage; high level of distrust of data carriers to companies using Big Data; high staff turnover in the market, etc. Assessing the risk of data loss due to hacker attacks allowed to identify it as a risk of a high level of importance (6 p.). Based on the obtained result, it is concluded that the activities of Big Data market participants are vulnerable to possible hacker intrusions and require more effective measures to ensure reliable data protection of enterprises and their customers.

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Big data in marketing literature

Cited by 3 publications

References 25 publications

Turizm İşletmelerinde Marka Kişiliğinin Duygu Analizi Yöntemiyle Belirlenmesi

Turizm İşletmelerinde Marka Kişiliğinin Duygu Analizi Yöntemiyle Belirlenmesi

Interactive Marketing E-Commerce Recommendation System Driven by Big Data Technology

Features of Big Data market risk identification

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