Thursday, December 12, 2019

Data Science Worldwide E-Business

Question: Discuss about the Data Science for Worldwide E-Business. Answer: Introduction The company is looking to enhance their business and move on to e-business as they are inspired by the worldwide e-business and their growth. They are looking forward to transferring their present business scenario to online business so as to increase the sales figure and accessibility. The overall idea is to have online shopping system for their customer so that their business is entirely customer-centric business, as well as data, was driven. The essential requirements of the company are to have a system that will help their clients to have a customization option so that they can select what they want and moreover the system can suggest them some different cookies based on their previous shopping and profile. The report that has been presented here discusses the benefits of new technologies that can help Cookie Limited to meet their objectives and goals. Data Collection and Storage Data Collection System First of all, let us understand about data collection, data collection refers to a systematic approach to collect and measure the data or information from different sources to get an accurate and a complete scenario of an area of interest (Bryman and Bell 2015). To have an online business presence it is critical to have a proper data collection system, so an appropriate data collected system is required and implemented in Cookie Limited to make the data or information they collect to be much more accurate and complete. Looking at the data types we can describe that there are two kinds of data they are: Quantitative Data This refers to any data or information that is in numerical forms such as percentage or statistics, etc (Treiman 2014). Qualitative Data This relates to any data or information that is in a narrative form such as quality, appearance, etc (Haberman 2014). Apart from these, the Cookie Company can use some secondary data (typically quantitative) and which has already been gathered by the third party for a different purpose. For an example, the Census data of U.S might be used by a company to make decisions about their marketing campaigns. But the question stands that how can we collect the Quantitative and Qualitative data. Storage System It is the most critical part of any business that the data or information that has been collected needs to be stored properly. Many vendors are offering the best online data storage system for both personal and business usage. The best option for Cookie is to adopt the Cloud system service (Kamat et al. 2016). Both the quantitative and qualitative data needs to be collected and stored in the system for that we need two different memories to distribute properly and collect the right information for each data type. Moreover, the company has to ensure that the systems that they have at present needs to be upgraded to make sure that they do support the new storage system (Anandarajan et al. 2012). Cloud computing system that has different advantages such as it has an enhanced data protection and availability, setting up the online storage system is relatively very easy compared to another offline storage system, and last but not the least the cloud computing system has a secure backup an d disaster recovery abilities, and moreover the system can remotely access from anywhere in this world (Melody and Mooney 2013). There is no need for that heavy hardwares for operation purpose because everything will be done using a virtual interface. Data in Action Consumer-Centric Product Design The designing research attempts to question and understand rather than to answer and predict. The Cookie Limited Company has to ensure that the goods they are producing have to be consumer centric which means that the wants, needs, and restrictions of the end user of a product or service are given extensive attention at every stage of the designing process (Tsimiklis et al. 2015). The Cookie Company has to use the customer data for better understanding of their customer requirements as well as the demand products so that they can manufacture to fulfill the customer satisfaction and to increase their business growth. So customer-centric product design is all about it and they need to do researches and surveys about their products and understand what exactly most of their consumers are looking for regarding taste and flavor (Bogers 2016). Once the feedback is reviewed, and the changes are made in their products then it help them to increase their sales rate and improve their sales reve nue as well. Moreover, the Cookie Limited Company has to focus towards the clients needs and then design the product so as to make sure that they are reaching to the point of customer satisfaction. Figure 1: Customer Centricity (Source: Bedarkar et al. 2016, pp.21) The company can perform two tasks to meet the above criteria; they need to implement software that will help them with a proper analyzing their profit for every flavor of cookies they have sold. This will contribute to having a clear idea about which product is doing well in the market and which is not. So the product which has the highest demand in the market must produce a bit extra then the order to increase the sales which will also improve the customer satisfaction as well as will gain revenue (Jaeger et al. 2013). So the company has to ensure that the products they are production have to increase the client's attraction. The company has to add that extra flavor let say as an example of fruits and nuts as a flavor in the cookies so as to gain more commercial sales. Recommendation System Customer lifetime value and churn rates are two critical or important customer centric measurements that need to be properly reviewed. These two CCM (Customer-Centric Measurement) are important because every company has their way of measuring the customer centricity. Likewise, the above two are the most important critical aspects that need to be correctly observed and reviewed as well. Customer Lifetime Value For any business, the most important thing is a customer because without them not business can stand or run. The primary purpose of it is that it will assess the financial value of each client or customer. It is important because it represents a higher limit of spending to get hold of a new customer (Di Benedetto and Kim 2016). The advantage or benefit the company has made by any given client is measured using CLV (Customer Lifetime Value). The primary usage of customer lifetime value is customer segmentation where it started with an understanding that all the customers are not equally critical (Groeger and Buttle 2014). This model allows the Cookie Company to guess the most profitable group of clients, understand those customer's common characteristics and concentrate more on them when to compare to other customers with less lucrative. Churn Rate To get the churn rate, the quantity of the clients has to be measured who have left recently lets say 12 months that have been divided by the basic amount of collected customers. It measures the amount of items or individuals shifting out of the gathered group over a certain time span. It refers to one of the two major factors that defines the stable state level of consumers of a company will help. It is a valuable input to Customer Lifetime Value modeling and which can be a part of an application that is used to calculate the Return on Marketing Investment (ROMI) using the MMM (Marketing Mix Modeling). It is when applied to a client base which refers to the proportion of contractual subscribers or clients who leaves a vendor during a given span of time (Zhang et al. 2015). It is closely related to the idea of average customer lifetime. The possible locator of client is not satisfied, better and cheaper deals from the contest or competition, more successful marketing and sales by the competition. Business Continuity: Survival of Online Business in Case of Power Failure and Another Disaster The business continuity and disaster recovery planning are stages that help the companies prepare for disruptive happenings and whether those events or happenings might involve simply power failure caused by something or natural disaster. The company does need a disaster recovery regardless of industry or size because whenever an unwanted event occurs in our daily operations then it does halt everything in an online business is a concern and moreover we have to make sure that the user is not suffered during this stage. The disaster recovery plan in the company refers that the company can protect of saving itself from several risks which include cost expenses, data and reputation loss and the negative impact on the customers (Snedaker 2013). Now creating, integrating and maintaining are the three things that a business recovery plan and it is important to make sure that implementing the DR (Disaster Recovery) plan in the company we are making sure for business survival and continuity. As far as the power outage is a concern it does not matter if we have a large business or small one. We only understand that the power outages give a bigger challenge to our businesses. The power failures are a bigger concern as far as the online business is a concern. So the best way to overcome the issue is to have a backup power system for an example UPS. For the survival there has to be a proper survival planning, let's say a power generation unit to help to overcome the power outage issue. So there always has to be back up plan for such disasters are mention disaster recovery, UPS or we can trust in cloud based systems, which are help as far as the consumer data or information, and it can be accessed by anywhere in this world and it does not depend if the physical operation system is in work or not. Conclusion The report finally concludes that how the data is important for any business and its role in the market production. The data collection system importance has been learned and what kind of information is there and as well as how it can be collected. The consumer-centric product design is discussed in brief and how it has been done is mentioned too. The recommendation system is also said on the consumer-centric product design. The overall report discusses how the technology will be beneficial for Cookie Limited Company if they are moving online to do their business. References Anandarajan, M., Anandarajan, A. and Srinivasan, C.A. eds., 2012. Business intelligence techniques: a perspective from accounting and finance. Springer Science Business Media. Bedarkar, M., Pandita, D., Agarwal, R. and Saini, R., 2016. Examining the Impact of Organizational Culture on Customer Centricity in Organizations: An Analysis. Prabandhan: Indian Journal of Management, 9(2), pp.19-28. Bogers, M., Hadar, R. and Bilberg, A., 2016. Additive manufacturing for consumer-centric business models: Implications for supply chains in consumer goods manufacturing. Technological Forecasting and Social Change, 102, pp.225-239. Bryman, A. and Bell, E., 2015. Business research methods. Oxford University Press, USA. Di Benedetto, C.A. and Kim, K.H., 2016. Customer equity and value management of global brands: Bridging theory and practice from financial and marketing perspectives: Introduction to a Journal of Business Research Special Section. Journal of Business Research, 69(9), pp.3721-3724. Groeger, L. and Buttle, F., 2014. Customer Lifetime Value.Wiley Encyclopedia of Management. Haberman, S.J., 2014. Analysis of qualitative data: Introductory topics. Academic Press. Jaeger, S.R., Cardello, A.V. and Schutz, H.G., 2013. Emotion questionnaires: A consumer-centric perspective. Food Quality and Preference, 30(2), pp.229-241. Kamat, M. and Liang, S., Emc Corporation, 2016. Online replacement of physical storage in a virtual storage system. U.S. Patent 9,250,823. Melody, E. and Mooney, R., International Business Machines Corporation, 2013. System and method for assigning data to columnar storage in an online transactional system. U.S. Patent Application 13/743,663. Snedaker, S., 2013. Business continuity and disaster recovery planning for IT professionals. Newnes. Treiman, D.J., 2014. Quantitative data analysis: Doing social research to test ideas. John Wiley Sons. Tsimiklis, P., Ceschin, F., Green, S., Qin, S.F., Song, J., Baurley, S., Rodden, T. and Makatsoris, C., 2015. A Consumer-Centric Open Innovation Framework for Food and Packaging Manufacturing. Zhang, Z., Wang, R., Zheng, W., Lan, S., Liang, D. and Jin, H., 2015, November. Profit Maximization Analysis Based on Data Mining and the Exponential Retention Model Assumption with Respect to Customer Churn Problems. In 2015 IEEE International Conference on Data Mining Workshop (ICDMW) (pp. 1093-1097). IEEE.

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