Psychology Of Customers and Digital Marketing assignment sample

Guide to the Psychology of Customers and Digital Marketing: Assignment Insights and Strategies

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Introduction OfAnalysis Of The Impact Of Big Data In Understanding The Online Psychology Of Customers & Digital Marketing

In this Era of the increasing of the participation in the data informatization the penetration in various levels of society could be observed in the increasing of the network economy (Darmody, 2020). Big data is important in the fulfillment of consumer demand and operations of the market economy of modern days (Gupta, 2021). There is a crucial significance in the understanding of the customer behavior to discuss the market trend and for the exploration of the background of the behavior of the consumers to get the research results for focusing on the behavioral model and for the exploration of the accuracy of the data which is affecting the diversification of the business analysis tools.

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Research Rationale

In the process of the collection of big data, There are various sources which are affecting the business and the for the formation of the traditional database tools which is for the fulfillment of the demand which is for the virtualization of the processing of the data and there are analysis, distribution, transfer and visualization of the business insights which is for the discovery and understanding of the behavior of the customers.

Through the customer analysis, the analysis of big data, and the prediction of the buying behavior of the customer (Hair, 2019). There is the process of market optimization, an increase in sales, planning of the inventory, and detection of fraud for the improvement of the sales. There are approaches that should be standing in the purpose of the visualization and the effective analysis of the organizational importance of the classification and the visualization of the aspects of data.

Research Gap

The primary purpose of the mining of big data for getting detailed insight regarding customer insights. There are various research gaps in the identification of the analysis of the shortcomings and adopting an approach of selection, analysis, and proper synthesis of the data (Camilleri, 2020). Through the extraction of the organizational implications of the effectiveness of the data for the understanding of the customers and analysis of the behavior which is defining the research exceptions and characterization of the dynamics and to understand the scopes of opportunities and for gaining the market success (Mogaji, 2020). Through the analysis of big data and effective business management, the future decision-making of business activities should be evaluated. For the future growth of any organization the analysis and advance understanding of big data for critical development of the data, which should be materialized in concerning the psychological and behavioral concepts.

Research Scope

In the evaluation of the business strategies and business analysis and the implication of the business data the increase in the operating margins and there are big data which is severely implicated for the improvement and efficiency for the quality improvement of the impact through the actualization of the management of the skill development and the embracing of the changes (Aceto, 2020). Through the implication of the outcomes from the effective management of the challenges which are being faced for the analysis of the organization. There are insights that could provide the scope of instigating newer technologies in the targeting of the challenges, which is for the specific achievement of effective management for credit management and effective pricing.

Figure1: Diagram of the Big Data in Understanding of the Market Behavior

Diagram of the Big Data in Understanding of the Market Behavior

(Sources: https://www.semanticscholar.org/)

Research Aim & Objectives

The analysis of the impacts of big data will help in the understanding of customer behavior in the market, there is a primary objective for the business evaluation of the businesses and the storage of the customer data (Bragazzi, 2020), which is for the improvement of the business activities. There are objectives that could be evaluated in the achievement of the desired goals of the organization.

These objectives are

  • To evaluate the accuracy of personalized marketing to boost the sales of e-commerce for segmentation of the market and highlighting profitable groups according to customer behavior.
  • To understand the purchase trends and to take better decision-making in the aggregation of the pricing according to the betterment of the objective of the demand.
  • To allocate resources for the achievement of the segmentation of the resources and to manage large data for tracking the planning of the strategies.
  • To use data on customer behavior in future forecasting and sales for sales budgeting and the evaluation of the performance reports as a recommendation.

Theory & literature review

In the analysis of the impact of big data, on the understanding of the online psychology of the customers (Romero, 2020). Through the understanding of customer behavior, an effective database management system is developed in the process of standardizing the fundamentals of the programs for the evaluation of the business. For the emerging realms of big data, the organization of U.K. sectors has been embracing the dramatic challenges understanding of the behavior of the customers.

There are some theories that are mainly focused on the betterment of accuracy and the insights of the variety of techniques. These theories will be effective in the betterment of the approaches.

  • Confirmatory analysis of data

Through the designing and the familiarization of the developments of the statistical methods and the approaches of the analysis the formulation of the research design and the concepts of the statistical discipline (Shamim, 2021). In the evaluation of the understanding of the purchase and market behavior, the market will help in the understanding of the concepts of the information of the estimated knowledge.

  • Grounded theory of data analysis

There is the involvement of data analysis, which is for the betterment of the approach of the utilization of the data, and the analysis of the data mining and the collection of the accordance with the insights (Wang, 2022). For the understanding of the purchase and customer, consumption behavior the research analysis should be understood.

Through the implication of these models and theories, various authors argue differently in the perspective of market understanding and business evaluation. There are principles of management and effective analysis of the markets through which the business accuracy and proper usage of the insights and techniques of marketing could be instigated in the effective management of business activities and evaluation of the business could be assessed. These are the key points for the arguments of the authors.

Figure2: Diagram of the Big Data Theory in Understanding of the Market Behavior

Diagram of the Big Data Theory in Understanding of the Market Behavior

(Sources: https://www.semanticscholar.org/)

Methodology

In this research on the understanding of the impact of big data on the understanding of customer behavior and data marketing the research of the data collection (Liu, 2021). In the secondary data analysis (Veleva,2020), the secondary research is conducted according to the existing data and from gaining insight from those data the knowledge and expertise for the recognition of the limitations of the data should be the potential existence of the knowledge and the cost-effectiveness for the gathering of the data and the advantages of the cost-effectiveness the leverage of the selection of the information is needed for the collection of the data and research of the expenses.

In this analysis, it is observed that through the usage of this methodology, the detailed analysis of the market and understanding of customer behavior could help businesses with extensive growth in the future. This secondary analysis of existing data, the proper understanding of the customer needs, and evaluation of the strategy for business expansion could be assessed.

Evidence

In the analysis of the junction of consumer behavior and big data. In 2014, there is the exploitation of consumer data observed in the revolution of the market (Indatalabs. com, 2021). There are capital farming and appropriate benefit in the reflection of knowledge and the understanding of the requirements. There are competitiveness and the valuation of the resources for the expansion of the market and the availability of the understanding of the customer behavior.

Summary

In the summarization of the implication of customer behavior the upcoming and unexplored markets have advanced in the potential of the business organizations which is transforming customer behavior, there are insights and proper decision-making in the reduction of the algorithms and the system data visualization for the analysis of the data-driven analysis of the customer data graphics

Recommendation

In the recommendation here it is described that how this research will be helped in future for the market. In future, this research will help for an industry to understand the trending market that will help to produce more preferable things and also the materials what public wants. This also helps to grow economically and help to fix the pricing of things. Also it provides the information what people wants presently, and what will the upcoming designs materials. The data on customer behaviors and sales budgeting reports can help to take any future decisions about to grow of the market strategies.

References

Book

  • Hair,(2019) Essentials of business research methods available at https://pdfuni.com/sample/Business/BZ201-300/BZ263/sample%EF%BC%8DEssentials%20of%20Business%20Research% [Accessed on 3.5.2023]

Journals

  • Aceto, G., Persico, V. and Pescapé, A., 2020. Industry 4.0 and health: Internet of things, big data, and cloud computing for Healthcare 4.0.Journal of Industrial Information Integration,18, p.100129.
  • Bragazzi, N.L., Dai, H., Damiani, G., Behzadifar, M., Martini, M. and Wu, J., 2020. How big data and artificial intelligence can help better manage the COVID-19 pandemic.International journal of environmental research and public health,17(9), p.3176.
  • Romero, C. and Ventura, S., 2020. Educational data mining and learning analytics: An updated survey.Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery,10(3), p.e1355.
  • Gupta, S., Justy, T., Kamboj, S., Kumar, A. and Kristoffersen, E., 2021. Big data and firm marketing performance: Findings from knowledge-based view.Technological Forecasting and Social Change,171, p.120986.
  • Darmody, A. and Zwick, D., 2020. Manipulate to empower: Hyper-relevance and the contradictions of marketing in the age of surveillance capitalism.Big Data & Society,7(1), p.2053951720904112.
  • Camilleri, M.A., 2020. The use of data-driven technologies for customer-centric marketing.International Journal of Big Data Management,1(1), pp.50-63.
  • Mogaji, E., Olaleye, S. and Ukpabi, D., 2020. Using AI to personalize emotionally appealing advertisements.Digital and Social Media Marketing: Emerging Applications and Theoretical Development, pp.137-150.
  • Shamim, S., Yang, Y., Zia, N.U. and Shah, M.H., 2021. Big data management capabilities in the hospitality sector: Service innovation and customer-generated online quality ratings.Computers in Human Behavior,121, p.106777.
  • Liu, X., Shin, H. and Burns, A.C., 2021. Examining the impact of luxury brand's social media marketing on customer engagement: Using big data analytics and natural language processing.Journal of Business Research,125, pp.815-826.
  • Veleva, S.S. and Tsvetanova, A.I., 2020, September. Characteristics of digital marketing advantages and disadvantages. InIOP Conference Series: Materials Science and Engineering(Vol. 940, No. 1, p. 012065). IOP Publishing.
  • Ardito, L., Cerchione, R., Del Vecchio, P. and Raguseo, E., 2019. Big data in smart tourism: challenges, issues, and opportunities.Current Issues in Tourism,22(15), pp.1805-1809.
  • Hajli, N., Shirazi, F., Tajvidi, M. and Huda, N., 2021. Towards an understanding of privacy management architecture in big data: experimental research.British Journal of Management,32(2), pp.548-565.

Article

  • Wang,(2022) Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud available at ieeexplore.ieee.org/abstract/document/8822503[Accessed on 3.5.2023]

Website

  • Indatalabs.com,(2021) Big Data: Revolution To Transform Business Models available at indatalabs.com/blog/impact-of-big-data-on-business [Accessed on 3.5.2023]
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