Customer Service: We can set a strong customer service through getting help from any published Journal on the sector of customer service. Local Competitive Set: This can be found on articles, Journals, local magazines, research papers indicating the competition in the seafood field. 1 1 1 Presenting survey Methodology Ana sampling Trade uses The survey methodology is presented below: Random sampling The selection of a random sample, each element of the population has an equal chance of been selected.
In general we do not assume that the underlying data follows a normal distribution, but in order to calculate bounds and confidence intervals from single samples it may be useful to assume that the estimates follow a normal distribution. This assumption will be appropriate for large sample sizes but will be problematic for small sample sizes drawn from highly skewed data. Example: At first, we assume that there are 30 companies in 3 markets. Moreover, the first market has 12 companies, second and third has 9 companies respectively. If we take 12 companies to investigate then we need to calculate the percentage of each group.
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Calculate market share: First, % of companies that are in the first market are = 40%. So the rest woo markets’ percentage will be 30% for each. Now, our sample companies will be distributed in the 3 markets in the following way: First market: = around 5 companies. So, second and third market will get 4 and 3 companies respectively. Now, we can choose 5 companies from first market, 4 from second market and 3 from third market to conduct our survey methods. Then we need to choose companies based on our requirement. As The Shark Spin survey on reduction in sales, the companies which have increased their sales in this sector must be selected.
Thus we can conduct a survey on the selected companies Black, 2009). 1. 2 Designing a Questionnaire for a given business problem Our next task is to design a questionnaire. Precise information can be found through questionnaire. In order to do so, targeting respondent should be identified. Our focus should be on the causes of decrease in sales and profit forecasting. So, we need to know about the cost structure, profit margin, and quality, market price, sales offer, sale service, complain of customers, probability of dissatisfaction etc.
Through this questionnaire we are going to find out about the causes in decrease of sales in firm. Normally some of the questions are MAC types and some are open ended types. In this case, we should follow MAC and open ended questions as well. So, Macs will be asked very precisely to get the targeted response and open ended types of questions need to be asked to get the views of the customers. As we need primary data for the given problem of the business, the structure of questionnaire may look like below: The Questionnaire for Shark Spin Do you work with any restaurant or retail shop? 1. Yes 2.
NO Do you like seafood? Are you a vegetarian or non-Vega? 1. Vegetarian 2. Non-vegetarian How often do you shop seafood in a week 1. Once 2. Twice 3. Thrice 4. More than 3 times Are there all types of sea foods available in your local shops? 1 . Yes Do you prefer frozen or fresh fish? 2. No Have you shopped at Shark Spin? 3. If yes, when did you shop last time Open ended types of questions: What are the types of foods do you eat in daily basis? What are the types of fish you expect to see in a shop? How do you think the customers can be satisfied more? If you have visited shark spin, what changes do you expect to see? . 1 Relating information for decision making by summarizing data using preventative values The representative values include mean, mode and median. We have conducted a survey on expected sales of Shark Spin. By using formula in Excel we have this histogram: Sales of Shark Spin in previous Year: Mean EYE,OHO Average expected sales In can year Mode Most occurring sales in previous years Median EYE,OHO Average occurring sale. First Quartile ?¬30,000 25% of sales were less or equal to EYE,OHO/year Third Quartile EYE,OHO 75% of sales were less or equal to EYE,OHO/year Result 8. 6 It is negative indicating that distribution is negatively slopped From the above table, we see that the mode and median are same but the mean is different. Mean is the mid value and is considered as the base value. It is the average of all the values. The problem arises when there are extreme values which we call outlier. If there is extreme value in the data set, the mean is affected by the extreme values. As a result, the founded result becomes biased and inappropriate. So, in that situation we prefer to use mode or median.
In case of quantitative data, it is use to find out the mean, mode or median. But in case of qualitative data, it cannot be possible. We can only conclude about the most occurring events from those qualitative data. For Shark Spin, this data will help to know the actual average sale and the most occurring sales in the past years. From this they can analyze the strategy they have taken in those years when the sale was at high point. Although the mean and median differs from each other, we can use this data to predict the actual amount of sale, average sale and the most occurring sale.
This can help in building future strategies, because they can easily follow the same strategy they followed when the sales where boosting upward. 2. Analyzing data using measures of dispersion to inform a given business scenario Distribution of data is given in the following table: Sales expected Targeted sales sector(in thousands/month) Range of sales expected c Other 10 2 TOTAL 26 35 18 17 3 7 15 The overall targeted sale scenario can be depicted from the above table. Sales in the sector are more at less range. Area B is expected to have the maximum sales then all other sector.
Whereas area B and C are expected to makes same amount of sale. From the above data we can predict that the area B might be highly populated place with more income. On the other hand, some of the areas are expected to make very low sales as they might me remote areas or may be high competition area. So Due to higher dispersion there doesn’t exist that much relationship between the variables. From the above given data, we can see the sales distribution of shark spin around its local areas. The above table shows us the extreme and small values.
To improve the sales we should work on balancing the big numbers with small numbers. In the case of sales, the extreme values above the average range doesn’t affect the business in fact it is a positive aspect for the business. But the small numbers shows that Shark Spin are lagging behind in those areas and need to improve their sales by any mean. Some of the sales are below the average range and this should be improved to increase the sale of shark spin. 2. 2 Use of correlation to predict future outcomes with present data.
If any sample of data is divided into hundred parts, each part is called percentile (McCollum, 2010). Percentile is normally expressed in per level form. For example, we may say that 40% of the teachers’ expected salary lies below the 40th percentile. Correlation co-efficient helps to measure how close the data is to being along a trait line (Kop, 2006). It is helpful to measure the spread of data set. It is calculated as dividing the sample standard deviation by the sample mean. It is sometimes expressed in percentage form, sometimes in the decimal form (Kop, 2006).