Currently there is a rapid change in the way businesses carry out their activities in order to achieve greater competitive advantage. What people have perceived as dreams is currently becoming into reality and this has led to greater improvement into the way companies carry out their activities (Oakshott, 2001). This is due to the fact that many people have entered into the business and many companies nowadays produce perfect substitute products. It is therefore important for every company to create awareness about their products so that they can be viewed differently by customers. As a result, it has become a demand for every company to create awareness about its behavior and products. In the current market, the customers have put pressure on businesses to implement necessary changes in their products in order to gain larger market share. Customers are currently very cautious and keen when making buying decision because they want they expect efficient and cost effective services. For the company to understand market potential, customer demand, product quality, determination of consumer behavior and others, it is important to conduct market research to find solutions to these problems.

Statistics for business and economics

In this research we used both qualitative and quantitative data to ensure that we find more accurate solution to the problem of this company. This research was being done to determine customer’s preference, taste and even their demand to help this company develop products that are able to meet the expectation of customers (Oakshott, 2001). It could only achieve this by obtaining customers feedback by collecting different information from them.

 In this research, there are a number of large files which include demographic data such as gender and age.  The data set collected also has information that reveals customers opinion and attitude towards the product. Such dataset were being used to ensure that the company understands the customer’s attitudes towards the products of this company in the market. They include variables such as like and hate. In this survey, 1000 samples were collected with a sample size of 100. The purpose of the use of 100 sample size was to remain with less data which is easy to analyze.

In this sample were able to collect data which relate to the version of the product which the customers most like. Under these, variables were divided into three namely version 1, version 2 and neither.

Row Labels	Count of Which version is the best?
neither	7
version 1	27
version 2	36
Grand Total	70

 All the variables in this case were grouped together in order to find determine the version which is most preferred by many customers. The variables were grouped into rows and columns for easy analysis. From the table, it is easy to observe at a glance the best version.

Opinion of customers was also categorized into different variables namely like and hate as shown in the table below. This ensures that the information collected is easy to understand and to analyze.

Ratio

Count of people that like product	Column Labels
Row Labels	like	hate	Grand Total
male	34	16	50
female	36	14	50
Grand Total	70	30	100

 In this table opinion of customers were categorized according to gender. This was important in easy interpretation of data collected. From the table one could easily understand that 34 of male respondents like the products while only 16 of them have a negative opinion towards the product. This is also not in the contrary with female which scored highly as compared to male.

Ratio

Proportion of people that like the product	Column Labels
Row Labels	like	hate	Grand Total
male	68.00%	32.00%	100.00%
female	72.00%	28.00%	100.00%
Grand Total	70.00%	30.00%	100.00%

 

To properly describe these variables, we also used ratios to ensure that proportion of each variable could be observed. Ratios were used to know the number of male or female that like or hate the product (Oakshott, 2001). From this the result can be converted into percentages to have an overall view of the behavior of each group of the population based on gender. From this we were also able to compare the number of people who like the product and those who hate it at a glance. Based on this, we could easily observe that 70% of the population likes the product while only 30% hate it. It therefore means that this company needs to explore other strategies in order to build their competitive advantage.

Some data were also categorized into frequency distribution table where there are frequencies, percentage frequencies and class. The purpose of this was to show the price of the same products that most customers are willing and able to pay. From this we could easily determine mean price, modal price, and median of the price. From this we were able to select the modal price as the price that should be used since most customers are able and willing to pay it.

Frequency Table
Value	Frequency	Frequency %
3	19	27.14
3.1	20	28.57
3.2	15	21.43
3.3	16	22.86

 

The dataset we had were also able to describe customer satisfaction. This could be described by using ratio where the respondents would be allowed to select YES or NO as their answers. From this we would be able to understand the number of satisfied customers against unsatisfied. From this we would also understand the characteristics of the variable we have in this survey.

Finally, age of customers was also considered in this research survey. The dataset about the age of customers were numerical because customers could only be classified as old and young.

Old	Young
52	48

From this it is easy to know the customer group that mostly uses this product. To analyze this, percentages can easily be used to ensure that the information therein could be understood easily.