Get Instant Help From 5000+ Experts For
question

Writing: Get your essay and assignment written from scratch by PhD expert

Rewriting: Paraphrase or rewrite your friend's essay with similar meaning at reduced cost

Editing:Proofread your work by experts and improve grade at Lowest cost

And Improve Your Grades
myassignmenthelp.com
loader
Phone no. Missing!

Enter phone no. to receive critical updates and urgent messages !

Attach file

Error goes here

Files Missing!

Please upload all relevant files for quick & complete assistance.

Guaranteed Higher Grade!
Free Quote
wave
Context

Organizations collect data in order to perform various analysis through which the management of the respective organizations are able to take an informed decision. This further helps the organizations is achieving a better position in the industry (Sedkaoui, 2018).

  • Data Visualization: It is a method of representing the data. Statistical charts and graphs are used in data analytics in order to get insightful idea about the data. With the help of data visualization techniques meaningful data can be presented that cannot be seen in data tables (Wilke, 2019).
  • Artificial Intelligence: When a situation arises where the data collected for analysis is very huge, artificial intelligence comes to play. With the help of AI techniques, organizations can not only analyse the data at a much higher rate but also analyse huge amount of data in very less time (Picareta, Weissheim and Klöhn, 2021).
  • Data Fabric: It is a place where data is managed and stored in an efficient manner. Data fabric promotes an unified environment and scalability. Apart from that data fabric helps in easy access of data presented in multiple locations (Agrawal, Paprzycki and Gupta, 2020).
  • Data Size: Small and wide data always has an advantage over big data since handling the former is much easier than the later.
  • Decision making on the basis of decision: The most important aspect of an organization is decision making. Informed decisions are taken with the help of correct data analysis (Delen, 2019).
  • Decision testing: Before taking a decision through evidence, understanding the importance of the decision is also essential and further understanding the utility if the decision.

Wood From The Trees of WFTT is a consultancy that was built 10 years ago. The purpose of this consultancy is to provide its clients with the results of analysis done on the data provided by the clients which help the client companies in business decision making. The primary aim of this paper is to analyse the data of the clients of WFTT consultancy. Here, the data for Bangles International Jewellery will be analysed, which is a major client of WFTT consultancy. The performance observed in the sales of Bangles International Company from the year 2018 to 2020 has been examined and discussed in this paper in three countries - USA, Japan and United Kingdom. In New York, Mumbai and London, Bangles International Jewellery owns a few number of stores that increases the sells with the help of distributor’s networks. In order to check the level of impact of marketing campaign on the sales, the product director and marketing lead at Bangles international Jewellery has asked WFTT to analyse the data so as to come up with a decision. The director wants to know if the impact of marketing campaign on the sales is positive or negative. Historic sales data for the years 2018, 2019 and 2020 have been collected. Bangles International Jewellery wants to WTTF provide recommendations on how BIJ should operate their business in order to increase their sales performance. Calculating the risk in a business is a very crucial aspect. The executives or managers of a company tend to take business decisions based on the result generated from analysing the data. Analysis of data helps in planning wants to WTTF provide recommendations on how BIJ should operate their business in order to increase their sales performance.

We will look at the data provided by Bangles in this investigation. Bangles' dataset covers sales statistics for its products in the three markets where they operate: the United Kingdom, the United States, and Japan.

The impact of Bangles' marketing effort in the UK in month 5 on product sales is investigated in this study.

The information would be analysed using the PPDAC framework (Spiegelhalter, 2019). The framework lays out the steps for analysing information that include numerical data. As a result, the issue has been defined: "evaluate the impact of a marketing effort." In this section, a plan is envisioned. The analytical procedure is covered in the next section. Data cleansing and analysis are the two parts of the analysis process. Finally, the results from the analysis are used to form a conclusion. Bangles has published a dataset that comprises statistics on the company's sales volume and value for various goods. The dataset covers sales data for its products in three countries — the United Kingdom, Japan, and the United States – from 2018 to 2020. The initial stage in the analysis would be to look for missing values in the dataset. The findings of an analysis can be harmed by missing values in a dataset (Camm, 2020). The dataset would also be double-checked for typographical problems. A cursory look at the dataset reveals a number of typographical problems. Because typographical errors lead to analytical errors, they must be addressed. We discover that the collection contains negative values. Because the dataset comprises data on sales volume and value, a negative number implies either product return or clerical errors. As a result, a decision must be made in the event of such an error.

Key Trends in Data Analytics

The dataset would be analysed using descriptive as well as inferential statistics. The dataset's descriptive statistics would be investigated using both tabular and graphical analysis (Sharpe, 2010). Initially, all three years' worth of data would be examined. Later data for the United Kingdom, on the other hand, would be examined. The purpose of the data analysis for the United Kingdom is to determine the impact of a marketing effort in the United Kingdom. To address the research topic, inferential statistics would be utilised.PPDAC Cycle

Figure 1: PPDAC Cycle

Section I – Data Cleaning

Figure 2: Missing Data

Figure 2 depicts information on data that is missing. According to the table, the sales volume for Accessory in JAPAN for 2018 is blank. Similarly, the sales volume and value for 2020 in the United Kingdom are blank. Furthermore, the sales volume of Accessory in the United States in 2018 and 2019 is negative. Furthermore, the sales value is a negative number. We can take this as a typing error and change the values to positive figures because the sales volume and value cannot be negative.

 Incorrect Spelling and Missing Data

Figure 3: Incorrect Spelling and Missing Data

The information about the United Kingdom for 2020 is shown in Figure 3. According to the data, the sales volume for the sixth month is 0. Furthermore, there is no information for the seventh and eighth months. The lack of a sales figure is interpreted as missing data, and "Hair Band" is thus ruled out of the study.Duplicate information

Figure 4: Duplicate information

Figure 4 depicts the product subtypes. Bracelet has also been referred to as Ankle Bracelet in the diagram. Ankle bracelet will now be referred to as Bracelet. Hair Band can also be referred to as Hairband. For the sake of clarity, this is referred to as Hair Band.

Figure 5: Total Sales Volume

Figure 5 shows the total amount of Bangles sold in each of the three markets over three years. Japan was the greatest market for Bangles in 2018-19. Bangles' total volume sales in 2018-19 were 4168 and 4085, respectively. However, the volume of Japanese Bangles sold in 2020 fell dramatically. The United Kingdom is the smallest of Bangles' three markets in terms of overall volume.

Total Sales Volume to Value

Figure 6: Total Sales Volume to Value

The United States accounted for 39% of overall Bangles sales as seen in Figure 6. However, Japan accounts for 46% of the entire sales value. The United Kingdom's overall sales volume and value were 24 percent and 17 percent, respectively.

Total Sales Volume across product Subtypes and Market

Table 1: Total Sales Volume across product Subtypes and Market

 Total Sales Volume across different Markets

Figure 7: Total Sales Volume across different Markets

The total sales volume for various product subtypes throughout the three markets is shown in Figure 7. According to the graph, sales of Accessory in all three markets began to increase in 2020. In the same way, Bracelet sales have surged in 2020. However, as compared to the United Kingdom and the United States, the Bracelet market in Japan is quite small. Ring's sales volume in all three markets has decreased in 2020 compared to 2018. Necklace sales have decreased in the United Kingdom and the United States, but have climbed in Japan.Sales Volume in the 5th month in UK Market

Value Addition by Data Analytics

Figure 8: Sales Volume in the 5th month in UK Market

The sales data for various Bangles goods in the fifth month in the United Kingdom are shown in the graph above. According to the graph, there were no Accessory sales in 2018 and 2019. From 2018 to 2020, the number of Bangles sold has consistently increased. Necklace, on the other hand, had 52 sales in 2018, but just 21 and 22 in 2019 and 2020, respectively. From 2018 to 2020, the sales volume will remain steady.Sales Volume (Month-on-Month Change in UK)

Table 2: Sales Volume (Month-on-Month Change in UK)

The table above depicts the change in sales volume in the United Kingdom from April to June 2020. The sales volume of Bracelets and Necklaces grew from April to May, according to the analysis. From April to May, the sales volume of all types of products increased even more. Sales Value (Month-on-Month Change in UK)

Table 3: Sales Value (Month-on-Month Change in UK)

The sales value of Bangles in the United Kingdom from April to June 2020 is depicted in the table above. The sales value of Bracelet, Necklace, and Ring grew from April to May, according to the values. During the same time period, however, the sales value of Accessory and Hair Band declined. In addition, from May to June, the sales value of all the products increased.

Conclusions

The description of the analysis of the data set provided by Bangles is presented in this section. We discovered several typographical issues before to analysing the data set, which we fixed. The country USA, as well as the product hairband, were misspelt. Similarly, the volume and value of sales were wrongly negative amounts, which we corrected.

According to the data, Japan was a particularly profitable market for Bangles between 2018 and 2019. However, sales volume is expected to decrease in 2020. Furthermore, the United States is a better market than the United Kingdom. In reality, for the year 2018-2020, the UK's total sales volume was the lowest. Furthermore, during the year 2018–2020, the overall volume and value of sales in the UK is the lowest.

The sales volume of Accessory has just begun to increase in 2020, according to the product subtype / market vis-à-vis year study. The sales volume of Accessory in 2018 was quite low prior to 2020.

From 2018 to 2020, the amount of Bracelets sold in each of the three markets climbed steadily. From 2018 to 2020, the total sales volume of Necklace rose in Japan. However, between 2018 and 2020, the total amount of Necklace sales in the United Kingdom declined. It also dropped in the United States. From 2018 to 2020, the volume of rings sold in Japan and the United States declined.

We also compared the sales volume of several Bangles goods in the UK during the fifth month. Prior to 2020, there were no sales of Accessory in the fifth month in the United Kingdom, according to the data. Bracelet sales in the fifth month in the United Kingdom had steadily increased from 2018 to 2020. There was a reduction in Necklace sales volume from 2018 to 2020, according to a comparison. However, for the fifth month in each of the three years – 2018 – 2020 – the sales figures for Rings remained quite steady.

Plan

We conducted a month-by-month change analysis to evaluate the marketing campaign's effectiveness. According to our findings, Bracelet sales volume and value increased in May 2020 as compared to April. Similarly, Bracelet's sales volume climbed even more in June. The sales value chart also shows that the sales value of Bracelets increased from 2018 to 2020.

Rings saw an initial uptick in sales volume in the UK market from April to May 2020. From April to May, the value of ring sales increased by the same amount. However, during the months of May and June, despite a one-unit decline in sales, the sales value increased. As a result, more research is required.

From April to May, accessory sales declined by one unit, but increased from May to June. The sales value showed a similar downward tendency from April to May, but an upward trend from May to June.

As a result of the whole analysis, we can see that sales volume for Bracelets and Rings has increased. As a result, it appears that the marketing campaign had an impact on Bracelet and Ring sales. Furthermore, since sales volume and value increased from April to May, we can conclude that the marketing campaign was successful. However, it is difficult to say definitively whether the marketing campaign had any effect on Accessory.

We can conclude from the foregoing analysis that the information available within the data set was insufficient to determine if the marketing campaign had a beneficial impact. In truth, we don't know the cost of the marketing effort based on the information provided by Bangles. We also have no information on when the campaign began and finished. Furthermore, we lack information on whether discounts were shared across items and, if so, what percentage of discounts were granted. As a result, Bangles' data appears to be lacking in information. As a result, more information on the daily number of customers who visit can be included. Aside from the marketing campaign's expense, a discount on each product might also be measured.

Furthermore, we discovered that the dataset contained mistakes. Missing data, misspelt products, and erroneously evaluated sales volume and value were among the mistakes found in the dataset. These can be adjusted to improve the data set's evaluation.

We examined the statistics supplied by Bangles in the preceding section. We looked at whether the marketing campaign had had any effect on sales in the fifth month of 2020 in the United Kingdom. Month, sales volume, and value were the variables that were taken into account. In fact, there were no factors in the data set that took the marketing campaign into account.

As a result, we recognise that improved models may be utilised to assess the impact of marketing campaigns.

The RACE framework can be used to assess a marketing campaign's effectiveness. The framework's steps (Chaffey and Ellis-Chadwick, 2019):

REACH aims to raise awareness of Bangles' products. This step entails using various paid media advertisements to reach the greatest number of clients possible.

ACT This stage entails interacting with consumers in order to increase the number of people that visit the store.

CONVERT This phase entails converting potential customers into customers and persuading them into completing a purchase.

Create long-term client engagement with ENGAGE.

For the investigation, an econometric model could be used. Other factors that may have an impact on sales volume can be investigated in this model. Thus, factors such as the number of customers who visit the branches on a daily basis, the cost of advertising, the discount offered, and thus sales volume can be used to develop a better model (Gribanova, Shirenkov and Katasonova, 2017).

The cost-benefit analysis can also be used to assess the marketing campaign's effectiveness. Thus, the cost of the marketing campaign in relation to the profit earned over the period can be examined in order to determine the marketing campaign's impact. (Mitik et al., 2017)

Sales ValueSales ValueSales ValueSales ValueSales ValueReferences

Agrawal, R., Paprzycki, M. and Gupta, N. eds., 2020. Big Data, IoT, and Machine Learning: Tools and Applications. CRC Press.

Chaffey, D. and Ellis-Chadwick, F., 2019. Digital marketing. Pearson uk.

Delen, D., 2019. Prescriptive Analytics: The Final Frontier for Evidence-Based Management and Optimal Decision Making. FT Press.

Ge, M. and Dohnal, V., 2018, June. Quality management in big data. In Informatics (Vol. 5, No. 2, p. 19). Multidisciplinary Digital Publishing Institute.

Gribanova, E.B., Shirenkov, I.V. and Katasonova, A.V., 2017, June. Econometric models for evaluation of marketing activitiesindicators of social network. In Proceedings of the conference «Trends of Technologies and Innovations in Economic and Social Studies (pp. 227-233).

Heinrich, B., Hristova, D., Klier, M., Schiller, A. and Szubartowicz, M., 2018. Requirements for data quality metrics. Journal of Data and Information Quality (JDIQ), 9(2), pp.1-32.

Hepworth, K., 2017. Big data visualization: promises & pitfalls. Communication Design Quarterly Review, 4(4), pp.7-19.

Mirzaie, M., Behkamal, B. and Paydar, S., 2019. Big Data Quality: A systematic literature review and future research directions. arXiv preprint arXiv:1904.05353.

Mitik, M., Korkmaz, O., Karagoz, P., Toroslu, I.H. and Yucel, F., 2017. Data mining approach for direct marketing of banking products with profit/cost analysis. The Review of Socionetwork Strategies, 11(1), pp.17-31.

Picareta, G., Weissheim, E. and Klöhn, M., 2021. Intelligent Applications in the Modern Sales Organization. In The Machine Age of Customer Insight. Emerald Publishing Limited.

Sedkaoui, S., 2018. Data analytics and big data. John Wiley & Sons.

Sharpe, N.R., De Veaux, R.D., Velleman, P.F., Wright, D. and Bock, D.E., 2010. Business statistics. Boston, MA: Addison Wesley.

Spiegelhalter, D., 2019. The art of statistics: Learning from data. Penguin UK.

Wilke, C.O., 2019. Fundamentals of data visualization: a primer on making informative and compelling figures. O'Reilly Media.

Cite This Work

To export a reference to this article please select a referencing stye below:

My Assignment Help. (2022). Data Analysis On Sales Performance Of Bangles International Jewellery, Essay.. Retrieved from https://myassignmenthelp.com/free-samples/nchnap690-data-driven-decision-making/apprenticeships-and-workforce-planning-file-A1B605B.html.

"Data Analysis On Sales Performance Of Bangles International Jewellery, Essay.." My Assignment Help, 2022, https://myassignmenthelp.com/free-samples/nchnap690-data-driven-decision-making/apprenticeships-and-workforce-planning-file-A1B605B.html.

My Assignment Help (2022) Data Analysis On Sales Performance Of Bangles International Jewellery, Essay. [Online]. Available from: https://myassignmenthelp.com/free-samples/nchnap690-data-driven-decision-making/apprenticeships-and-workforce-planning-file-A1B605B.html
[Accessed 20 July 2024].

My Assignment Help. 'Data Analysis On Sales Performance Of Bangles International Jewellery, Essay.' (My Assignment Help, 2022) <https://myassignmenthelp.com/free-samples/nchnap690-data-driven-decision-making/apprenticeships-and-workforce-planning-file-A1B605B.html> accessed 20 July 2024.

My Assignment Help. Data Analysis On Sales Performance Of Bangles International Jewellery, Essay. [Internet]. My Assignment Help. 2022 [cited 20 July 2024]. Available from: https://myassignmenthelp.com/free-samples/nchnap690-data-driven-decision-making/apprenticeships-and-workforce-planning-file-A1B605B.html.

Get instant help from 5000+ experts for
question

Writing: Get your essay and assignment written from scratch by PhD expert

Rewriting: Paraphrase or rewrite your friend's essay with similar meaning at reduced cost

Editing: Proofread your work by experts and improve grade at Lowest cost

loader
250 words
Phone no. Missing!

Enter phone no. to receive critical updates and urgent messages !

Attach file

Error goes here

Files Missing!

Please upload all relevant files for quick & complete assistance.

Plagiarism checker
Verify originality of an essay
essay
Generate unique essays in a jiffy
Plagiarism checker
Cite sources with ease
support
Whatsapp
callback
sales
sales chat
Whatsapp
callback
sales chat
close