Statistical analysis is an integral part of the business, allowing to analyze the current situation and make decisions based on the collected data. However, as the amount of information generated and processed grows, it is necessary to use specialized techniques that make it easier to interact with data (Cote, 2021). Using the proper data collection method, correctly assessing the level of data measurement, and determining the type of data can significantly improve the quality of the final decision. This paper aims to study the presented issue using statistical analysis and analyze the necessary data processing procedures.
First of all, it is necessary to determine the most appropriate data collection method. Since the company needs to get its customers’ opinions, the best approach is the use of focus groups, which represent a sample of people from the company’s target audience. This method of collecting information allows receiving feedback regarding any qualities of the product (Cote, 2021). Besides, recruiting people for a real-time meeting in this context is more likely than using online surveys. Although the latter method is cheaper, getting clients to interact with questionnaires will be much more problematic since this requires a specific communication platform.
On the other hand, posting ads and recruiting people into focus groups for a fee, despite the high cost, will be much more effective. To apply this method, it is possible to place announcements about the need for feedback directly on the company’s current products and various advertising platforms. In addition, special research centers can be contacted, which will conduct an organized investigation on behalf of the company (Cote, 2021). The data obtained in this way can be professionally processed, which increases its value and relevance.
However, two parameters need to be specified for processing information: evaluation level and data type. In this case, it is necessary to use nominal scales since scales do not need to be heavily loaded with details (“Level of measurement,” n.d.). The received data should be classified only by the type of customer preferences, and there are no relationships between them. Therefore, a simple designation of groups of buyers by code names will be sufficient. Part of the reason for this is that the information collected is inherently qualitative. The data received from buyers contain contextual information that cannot be calculated. The non-numeric nature makes the information qualitative and, as a result, requires the use of the most superficial level of measurement.
References
Cote, C. (2021). 7 data collection methods in business analytics. Harvard Business School.
Level of measurement. (n.d.). Corporate Finance Institute.