Market Analysis of Australian Healthcare Industry
Discuss about the Principles of Business Analytics Solution.
The residential Australian unvarying (correlative) healthcare industry is energetic and huge. Statistical surveying demonstrates that the ubiquity of normal natural healthcare items is expanding with a development rate of seven for each penny year on year. 75% of Australians, including 92 for each percentage of female aged 20-24; take no less than one dietary supplement and a fourth of the populace visit fundamental healthcare services experts every year (Bagstad et al. 2013).
The Australian business keeps on developing to meet these necessities. As of now sensitive to elective ways to deal with wellbeing, perceiving children of post war America (Australia's biggest populace gathering) progressively request more noteworthy decision and receive a deterrent medicinal services way to deal with keeping up more beneficial lives. In Australia, the speediest development zones are personal care, Pharmaceuticals and Nutrition. In the previous two decades, the pharmaceutical, individual care, and nutritious enterprises have merged to address developing requests in the beauty, wellbeing and health advertise.
This merging has brought about the development of new industry fragments Nutraceuticals, Cosmeceuticals and Nutricosmetics. While, the market in China, Japan or USA is properly established for these new segments, the Australian market is still in the early stages of development. Thus, understanding these industry segments, consumers, the potential markets and opportunities are imperative. This particular report is therefore exploring effective marketing strategies (market opportunities, targeted customers, channels for campaigns, etc.) for a potential client intending to enter these new industry segments in Australia.
As mentioned in the given case study, an end user survey has been already conducted and the data is available for analysis. This section of the study is exploring the appropriateness of this survey (Hazen et al. 2014). Since, the aim was to identify market opportunities in this new filed; it was obvious choice to collect information from those respondents, who have the interest in these products. In other words, this survey must had to consider one such question, which can classify respondents into two categories; one who know something about these products and ready to purchase and one who have no such idea. It has seen that the survey started with the question, “Are you a regular consumer of beauty, health & wellness products?” and the data was collected from regular consumers of beauty, health & wellness products. Hence, it can be said that the survey questionnaire designed for this survey set proper tone for this market. A survey is termed as an effective one provided it supports the analyst to explore both demographic profile as well as awareness about the subject of study. From this point of view too, it can be argued that this survey questionnaire has considered a list of demographic variable started from state to income, age band and gender. These variables are critical for identifying market opportunities, targeted customers and associate strategies (Jaworska et al. 2015). Again, this survey questionnaire has also included questions that are required to understand the new product launch strategies. Hence, it can be concluded that the data collected using this survey questionnaire surely give insights about the Australian beauty, healthcare and wellbeing market.
End-User Survey and Its Appropriateness
The survey question overall seemed good to collect necessary information for Australian beauty, healthcare and wellbeing market, however, questions related to promotional strategies, whether giving offer and discount will influence the purchase decision or not are necessary to portray the market properly. These questions are missing here.
In this section of the report, the analyst has presented two different set of analytical solutions designed with the help of SAP Lumira and Microsoft Excel analytical tool. While deigning the models, the analyst tried to display the possible market segments, target customers, marketing channel necessary and easiness of spreading information about the product and finally product form. The analytical model designed with the help of SAP Lumira visualize the data collected through this survey questionnaire (Duan and Xiong, 2015). On the other hand, the pivot tables designed with the help of excel demonstrates numerical figures.
Market Segment
Figure 1: Possible Market Segments (using SAP Lumira)
Customer segment
Figure 2: Possible Customer Segments (using SAP Lumira)
Marketing Channel
Figure 3: Possible marketing channel (using SAP Lumira)
Customer view about product
Figure 4: Market readiness of product (using SAP Lumira)
Analytics solution 2
Figure 5: Market segments
Figure 6: Customer segments
Figure 7: State wise customer segments
Figure 8: Age wise market demand
Figure 9: Spending level
Figure 10: Recommendation to friend
Figure 11: Product effectiveness
Figure 12: Form of product
Recommendations
This section of the report is important as the analyst has explained the results found from both analytical model. Further, a list of recommendations have been given by the analyst. The first aim of developing these two model was to identify which market segment is in the priority list of Australian customer. Refer to figure 1 as well as figure 5, it can be said that Nutricosmetics product is in high demand in the Australian market. According to figure 5, there is almost 41% respondents shown interest about this kind of products. The analytical model 1 (figure 1) further investigated the market segments with respect to gender and age. While 20% male shown interest for this product, almost 22% women also keen to use this product. Again, from this figure, it can be said that people with age up to 40 years are majorly showing interest for this product. Hence, it can be recommended that the target market should be Nutricosmetics for women with maximum 40 years old. Further, it can also be recommended that Victoria and Queensland would the first priority to launch such products.
Analytical Models Designed for Exploring Market Opportunities and Targeted Customers
While talking about target customer, both the analytical models have shown different view point and on the basis of these figures and visualizations (figure 2, 6, 7), it can be said that female with income level 70000 – 90000 should be targeted. In case of marketing channel, it has seen that use of social media will be the primary choice like other major industry. The analytical model 1 has shown that 30% of the target customers are preferring social media as an effective way to reach them. They also like to get update about the product through this marketing channel as they mostly spent their spare time in using social media. Hence it can be recommended that social media marketing should be the first priority for branding this product. At the same time, emailing is another important way through which targeted customer want regular update about the new product. Hence, it is recommended to maintain a customer database and organizations operates in this industry needs to send mail update to all of their existing customers. The table 6 deigned in model 2 has shown that 43.85% of respondents mentioned that they will refer to their friend about this product. Hence, emailing would be next important way of doing branding.
From the analytical model 1, it has seen that they will ready to spend 50-100 dollar in a month for this kind of product. Hence, it is necessary to adjust pricing of these product according to their expectation. Finally, it is seen that all most 16% of the respondents have mentioned either as food or pill form would be the best for such product. So, it is recommended to consider these two form while introducing new products in the market.
Bagstad, K.J., Semmens, D.J., Waage, S. and Winthrop, R., 2013. A comparative assessment of decision-support tools for ecosystem services quantification and valuation. Ecosystem Services, 5, pp.27-39.
Banerjee, A., Bandyopadhyay, T. and Acharya, P., 2013. Data analytics: Hyped up aspirations or true potential?. Vikalpa, 38(4), pp.1-12.
Choi, T.M., Chan, H.K. and Yue, X., 2017. Recent development in big data analytics for business operations and risk management. IEEE transactions on cybernetics, 47(1), pp.81-92.
Duan, L. and Xiong, Y., 2015. Big data analytics and business analytics. Journal of Management Analytics, 2(1), pp.1-21.
Fan, S., Lau, R.Y. and Zhao, J.L., 2015. Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), pp.28-32.
Ghazal, A., Rabl, T., Hu, M., Raab, F., Poess, M., Crolotte, A. and Jacobsen, H.A., 2013, June. BigBench: towards an industry standard benchmark for big data analytics. In Proceedings of the 2013 ACM SIGMOD international conference on Management of data (pp. 1197-1208). ACM.
Hazen, B.T., Boone, C.A., Ezell, J.D. and Jones-Farmer, L.A., 2014. Data quality for data science, predictive analytics, and big data in supply chain : An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, pp.72-80.
Janssen, S., Porter, C.H., Moore, A.D., Athanasiadis, I.N., Foster, I., Jones, J.W. and Antle, J.M., 2015. Towards a New Generation of Agricultural System Models, Data, and Knowledge Products: Building an Open Web-Based Approach to Agricultural Data, System Modeling and Decision Support. AgMIP. Towards a New Generation of Agricultural System Models, Data, and Knowledge Products, p.91.
Jaworska, J.S., Natsch, A., Ryan, C., Strickland, J., Ashikaga, T. and Miyazawa, M., 2015. Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy. Archives of toxicology, 89(12), pp.2355-2383.
Klinkenberg, R. ed., 2013. RapidMiner: Data mining use cases and business analytics applications. Chapman and Hall/CRC.
Kohavi, R., Rothleder, N.J. and Simoudis, E., 2002. Emerging trends in business analytics. Communications of the ACM, 45(8), pp.45-48.
Kwon, O., Lee, N. and Shin, B., 2014. Data quality management, data usage experience and acquisition intention of big data analytics. International Journal of Information Management, 34(3), pp.387-394.
Loebbecke, C. and Picot, A., 2015. Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. The Journal of Strategic Information Systems, 24(3), pp.149-157.
Raghupathi, W. and Raghupathi, V., 2014. Big data analytics in healthcare: promise and potential. Health Information Science and Systems, 2(1), p.3.
Salam, M.A. and Khan, S.A., 2016. Simulation based decision support system for optimization: a case of thai logistics service provider. Industrial Management & Data Systems, 116(2), pp.236-254.
Sauter, V.L., 2014. Decision support systems for business intelligence. John Wiley & Sons.
Serrano-Cinca, C. and Gutiérrez-Nieto, B., 2013. A decision support system for financial and social investment. Applied Economics, 45(28), pp.4060-4070.
Sharda, R., Delen, D. and Turban, E., 2013. Business Intelligence: A managerial perspective on analytics. Prentice Hall Press.
Shmueli, G., Patel, N.R. and Bruce, P.C., 2016. Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner. John Wiley & Sons.
Vera-Baquero, A., Colomo-Palacios, R. and Molloy, O., 2013. Business process analytics using a big data approach. IT Professional, 15(6), pp.29-35.
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