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Data Insights For Business Decision Assignment Sample

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Slide 1: Introduction 

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  • This study aims to focus on the data insight for the business decisions 
  • The chosen organisation is Sainsbury
  • Quantitative and qualitative approaches in modern marketing research will be identified
  • Correlation, Regression, and Time Series analyses along with issue identification
  • Data collection and use of data

It can be depicted the fact that this study aims to focus on the data insight for the business decisions of the chosen organisation of the retail organisation Sainsbury. The entire study will discuss the quantitative approaches that are important to develop the entire research in modern business market research. After that, the major focus of this study will be developed on the basis of the qualitative research approach in modern marketing research of the chosen company. Later the description of the correlation and regression along with diverse examples relating to the company will be described. The time series data analysis is also going to be evaluated here which can depict the importance of time series within a research. After that, the issues within the correlation, regression and time series with respect to big data will be identified in this study. Lastly, the steps of the data collection method in effective decision making are also going to be depicted here.

Slide 2: Quantitative approach to research in modern marketing research 

  • "Quantitative research approach" can be a potential tool for data collection in Sainsbury (Troisi et al. 2020).
  • It allows one to gain trustworthy objectives, data and an obvious understanding 
  • This method can ask questions to the targeted audience 
  • The data collection processes are data interviews, surveys, questionnaires and a few others

"Quantitative research approach" is a potential tool to analyse the market and customers of an organisation. Hence this type of research approach allows one to gain trustworthy objectives, data and an obvious understanding of the trends and patterns. It can be depicted that, "Quantitative Market Research" is a method that can ask questions to the targeted audience of an organisation also in a methodical manner by using the data collection process of polls, interviews, surveys, questionnaires and a few others. After that, the received answers can be investigated to make proper decisions for future improvement of the company's products and services.

Slide 3: CONTD...

  • It is the method of gathering and interpreting numerical data (Kushwaha et al. 2021).
  • The major data was collected from the review of customers of Sainsbury.
  • It can gain authentic and correct information from people's own opinions. 
  • It is difficult to comprehend the context of a phenomenon
  • The collected data do not become enough to explain the issues.

The "Quantitative research approach" is the method of gathering and interpreting numerical data. In the case of Sainsbury, the major data was collected from the review of customers of this organisation. The qualitative and primary research method has been used because they can gain authentic and correct information from the people's own opinions. This process can be utilised as a process of market research because it can be operated to find out the customer's preferences and try to understand how consumers feel about the products that Sainsbury sells. Apart from all the positive activities, there are some drawbacks to the quantitative approach in modern marketing research and that is including it is difficult to comprehend the context of a phenomenon and sometimes the collected data do not become enough to explain the issues.

Slide 4: Qualitative approach to research in modern marketing research 

  • This is approaches that can analysis of the elements that affect people's behaviour.
  • It has a possibility to understand the need and demands of the consumers
  • The "content analysis" and "thematic analysis" are major techniques of the qualitative approach (Kachaoui and Belangour, 2020).

"Qualitative market research" is the analysis of the elements that affect people's behaviour within a distinct business market. Hence, in a retail market, the purpose of "qualitative research" might be to comprehend the inspirations of the customers when they buy things from an organisation. Hence, by conducting qualitative market research most of the global organisations or brands have a possibility to understand the need and demands of the consumers. The two major techniques that are used for qualitative market research analysis are "content analysis" and "thematic analysis".

Slide 5: CONTD...

  • Qualitative market research analysis (Akter et al. 2019).
  • Diverse approaches are including "grounded theory", "ethnography", "action research", "phenomenological research" and "narrative research".
  • The major drawback is that it does not support statistical representation
  • It is a time-consuming process.

The diverse approaches of "Qualitative market research analysis" include "grounded theory", "ethnography", "action research", "phenomenological research" and "narrative research". In this regard, Sainsbury can share resemblances of the data collection process but highlight various purposes and perspectives. On the contrary, there are a few drawbacks of this market research process because it does not support statistical representation and it is a time-consuming process.

Slide 6: Correlation analysis 

  • Sainsbury has been using "trading using pair correlations" (Jansen et al. 2020).
  • The net income of this company was GBP 207 million
  • The correlation of Sainsbury is considered as strong
  • The "hedging techniques" over random equities.

It can be noted the fact that Sainsbury has been using "trading using pair correlations" for their financial advancement. The Net income of this company was GBP 207 million in 2021. Thus the type of correlation has a high impact on the organisational financial activities and development. The correlation of this retail company is greater than 0.8 and that is considered as strong. The correlation of Sainsbury has also developed the fact that it is using "hedging techniques" over random equities.

Slide 7: Regression Analyses

  • It can increase the respondent and satisfaction levels of consumers (Li et al. 2019).
  • It can generalize the outcomes to broader populations
  • Regression is totally different from the Correlation analysis

In the case of Sainsbury, this method of market research can be helpful in increasing the respondent and satisfaction levels. Hence, it can be employed to discover ways and standards, make predictions, experiment on employee and consumer relationships, and finally generalize the outcomes to broader populations. Regression is totally different from the Correlation analysis. The regression determines the outcome of the difference in the division in the known variable (p) and the estimated variable (q). On the contrary, correlation allows forming a relationship between two chosen variables.

Slide 8: Time Series 

  • A "time series" is a data set that can track a sampling over time (Shamim et al. 2019). 
  • Sainsbury uses "predictive analytics" and "machine learning" strategies 
  • It can detect new grocery trends within a specific selected time within the time series.

A "time series" is a data set that can track a sampling over time. In this regard, a time series permits one to notice what aspects affect individual variables from time to time. Time series analysis can be helpful to notice how a disseminated investment, safety, or financial variable changes over time. In this regard, Sainsbury uses "predictive analytics" and "machine learning" strategies to detect new grocery trends as they happen within a specific selected time within the time series. 

Slide 9: Correlation, Regression, and Time Series Analyses 

  • Issues regarding big data analytics
  • The problem in measuring the capacity (Rawat et al. 2021).
  • Issues in validation data and the data quality of the big data analytics

It can be depicted the fact that Correlation directs to the "statistical relationship" between any of the two entities. The major issue that this company has been facing is its problem in measuring the capacity to which two variables are linearly connected. After that, the issues in validation data and the data quality of the big data analytics of Sainsbury have been increasing along with its regression process. Along with that, this company has been facing major time series-related issues including "seasonality", "trends", "cycles", and "irregular components".

Slide 10: Collection and use of data 

  • Qualitative type of market research can help Sainsbury
  • It can maintain the proper relationship between the brand-consumer (Zamani et al. 2021).
  • Identified issues can be mitigated via technological advancement adaptation within the organisation.

The qualitative type of market research can help Sainsbury to fulfil the needs of their consumers as well. As a result, it can maintain the proper relationship between the brand-consumer. The issues within the Correlation, Regression, and Time Series Analyses can be mitigated via technological advancement adaptation within the organisation.

References

  • Akter, S., Bandara, R., Hani, U., Wamba, S.F., Foropon, C. and Papadopoulos, T., 2019. Analytics-based decision-making for service systems: A qualitative study and agenda for future research. International Journal of Information Management48, pp.85-95.
  • Jansen, B.J., Salminen, J.O. and Jung, S.G., 2020. Data-driven personas for enhanced user understanding: Combining empathy with rationality for better insights to analytics. Data and Information Management4(1), pp.1-17.
  • Kachaoui, J. and Belangour, A., 2020. From single architectural design to a reference conceptual meta-model: an intelligent data lake for new data insights. International Journal8(4), pp.1460-1465.
  • Kushwaha, A.K., Kar, A.K. and Dwivedi, Y.K., 2021. Applications of big data in emerging management disciplines: A literature review using text mining. International Journal of Information Management Data Insights1(2), p.100017.
  • Li, S., Peng, G.C. and Xing, F., 2019. Barriers of embedding big data solutions in smart factories: insights from SAP consultants. Industrial Management & Data Systems.
  • Rawat, S., Rawat, A., Kumar, D. and Sabitha, A.S., 2021. Application of machine learning and data visualization techniques for decision support in the insurance sector. International Journal of Information Management Data Insights1(2), p.100012.
  • Shamim, S., Zeng, J., Shariq, S.M. and Khan, Z., 2019. Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Information & Management56(6), p.103135.
  • Troisi, O., Maione, G., Grimaldi, M. and Loia, F., 2020. Growth hacking: Insights on data-driven decision-making from three firms. Industrial Marketing Management90, pp.538-557.
  • Zamani, E.D., Griva, A., Spanaki, K., O'Raghallaigh, P. and Sammon, D., 2021. Making sense of business analytics in project selection and prioritisation: Insights from the start-up trenches. Information Technology & People, (ahead-of-print).
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