Question

Discuss one data collection and one data analysis technique that is frequently used in addressing marketing analytics problems. Provide current industry examples to illustrate your ideas.

Answer 1

Solution: Organizations of almost all sizes rely heavily on the process of data analysis to improve the decision-making process, forecast outcomes, evaluate the effectiveness of marketing campaigns, identify market opportunities and potential new audiences, and much more. But one important aspect of data analysis is that it can be easily overwhelming, not because of the massive volume of data that most companies have to work with but also because there are seemingly endless tools, techniques, methodologies, and practices to perform the data analysis in the field of marketing. Data collection is an initial and very important part of carrying out the data analysis in any domain be it marketing or non-marketing. Here I am discussing the most effective practices to carry out the data collection and data analysis in the field of marketing.

Data Collection: There are several methods to perform the Data Collection for the data analysis process and the most popular methods are Survey Method, Experimental Method, Observation Method, and Panel Method. Survey Method is the most effective and most widely used Data Collection Method when it comes to the process of Data Collection. Let us understand the survey method in detail.

Survey Method: In this method, the data is collected through the process of direct communication with the respondents. This communication can be face-to-face oral communication or by other means such as telephone, mails, etc. The most unique characteristic of the survey method is that it collects the data by asking direct questions from the respondents. It fits almost any kind of research problem. As mentioned earlier it is one of the most recognized and flexible data collection methods. It can be done in several ways such as asking questions to the respondents by conducting a face-to-face interview, or by conducting the same over the telephone call, or by sending the questionnaire to the respondents through the electronic mailing system. Although all three of them have their unique significance in different situations, however, the oral face-to-face interview is the most effective method of conducting the survey. It is considered as the most effective method because the chances of the forgery and the fake data are less in this survey method.

Data Analysis Methods: There are so many Data Analysis methods such as using the different data distributions such as chi-squared distribution, normal distribution, and other data distribution to understand the data, using the descriptive statistics such as mean, mode and median to perform the analysis, regression analysis, correlation analysis and many more. just like the Data Collection techniques the choice of the data analysis techniques actually depends upon the size and nature of the problem. For the sake of describing the most widely used and most effective Data analysis technique, I will go with the Descriptive Statistics technique.

Descriptive Statistics Technique: It involves the usage of different statistical tools to describe the data. These tools mainly include the measures of central tendency and the measures of the dispersion. The measures of central tendency include mean, mode and median while the measures of dispersion involve the standard deviation and range. We won't go in-depth to understand all of the above terms but we will skim through each one of them. Mean is the average value of the data and it is obtained by summing all the observational values and dividing them by the number of observations. Median refers to the central data value when the data is sorted in order. Mode refers to the most observed data value in a data distribution. Range is defined as the difference between the maximum and minimum values in a data distribution. Range and Standard Deviation are directly proportional to each other which means that higher the Range higher will be the Standard Deviation. These statistical tools help analysts to understand the exact nature of the data, this, in turn, helps them churning the meaningful insights from the data.

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