Analysis Essay on Conventional Content

Published: 2021-07-21
1648 words
6 pages
14 min to read
Carnegie Mellon University
Type of paper: 
Dissertation methodology
This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

This study aimed at finding the best and most effective method to improve the customer base and promote products in the digital marketing. In this study, the method of conventional content analysis was applied to gather marketing data from the consumers and musicians, regarding the products that they offer in the market. Content analysis is a systematic, replicable techniques for compressing many words of text into fewer content categories based on explicit rules of coding. In other words, the methodology has been used to summarise a large content into a small and easy to analyse text. The researcher used the content analysis in identifying patterns in products and customers responses on the digitally advertised products by musicians. The aim was to identify how effective the musicians can be in marketing. The main platforms used for these data was from the Facebook and Twitter. It should be noted that musicians with a large number followers and fans easily reach the market than any other media; simply because of their influence on the fan base. In this study, conventional data analysis method used aimed at relating data from 20 musicians from the year 2016 and the effects this had of their fans. This method relates to the collection of qualitative data that can be coded depending on the issues that the author wants to analyse in order to find the relationship or make inferences on related data. For this study, our main aim was to discuss the effect of that musicians posting have on the people. The main aim of this method was to collect data that can be used to make inferences on the issue relating to digital marketing. Conventional content analysis focusses on a certain issues that can be analysed from a series of text or data collected. In conventional content analysis, coding categories were derived directly from the text data that was collected.

The conventional content analysis was chosen in this study because it has numerous advantages, such as lack of contact with people in the study. In addition, this method is inexpensive, and achieved information can be used while analysing trends in in time difference for the issue in discussion. The conventional content analysis focusses on the use of or availability of some words in the text, then quantify the data for inferences and conclusions. In other words, the method takes qualitative data, and quantifies it to end up with qualitative data. This means that a text that was purely written as a qualitative study can be used and be transformed to qualitative data. The reason for making such kind of data is that the quantified information is more appealing to the readers and also more relevant in assisting solve the problem in the research. The information that is found while analysing and collecting data from the study is put or fed in the computers for codding.

The conventional content analysis method was has been utilised in different fields of study since early 1940s. initially, researcher were only concerned with word count, until in late 50s that researcher began to think of a more complex analysis of the work rather than just looking at word count. The modern conventional content analysis utilises the word count as well as the sematic relationship between texts. The method determines the quantity or the number of certain words in a series of texts for easier analysis. In this study, however, our main focus is on the way that people consume the social media relation to the digital marketing.

Digital marketing is a data driven marketing that which utilises digital technologies on the internet, such as Facebook, Twitter, and YouTube, to mention just a few. In this methods, the study used data information from people that have enough influence; and the people who can be able to reach the highest number of people in the world. For example, the data we managed to collect for the analysis of this study was found from 20 great musicians of this age, and they all happen to have a very large number of followers in on social media. The numerous followers on social media means that the information found from this analysis is almost very accurate, as it comes from people who respond willingly and unconsciously.

The data collected using this methodology is essential in the in addressing the study question and objectives in various ways. For example, digital marketing depends on the technologies so as to reach the targeted market, while that conventional content analysis analyses information that is posted by people who uses the digital media in their daily operations. This means that whatever data that we find for the study from the group of individuals selected is relevant for quantifying and answering the study questions. In addition, the methodology was relevant to the study, in that it analyses peoples reactions and on the brands and products that they get on the modern technology via social media consumption. Most of the people around the globe consume and utilise the digital media in most of their day to day operations (Ruane and Cerulo, 2012). Also, this method fits the overall design of the study in that it acknowledges the quantitative data in relation to qualitative data. In other words, instead of using the quantitative method also, or the qualitative method, this study used a conventional methodology; which derives quantitative context of qualitative methods.

There are two procedures that were used in obtaining data for analysis in this research; deductive and inductive. In inductive analysis, the study concentrated on condensing data from various sources, in this case, 20 musicians and their Facebook posting habit. The aim of using this kind of analysis was to develop theories and relationship between different people and the reactions that their followers have. After collecting information using the inductive approach, the study then focused on the deductive approach. This approach involve reasoning, and making conclusions and inferences from the data that was collected in the inductive part. It was from this deductive approach that the research was able to create hypothesis and theories. The focus of data collection and analysis, however, was to find the relationship between musicians postings and finding a suitable posting pattern.

The methodology involved an utilisation of a statistical finding certain words in the popular posts, so as the data could be analysed using statistical methods (de Graaf and van der Vossen, 2013). The appropriateness the results of the data could only be found once we have quantified and analysed using a statistical method. The use of parameters in statistical method, such as the measures of central tendencies is a sure way to ensure effective analysis. In addition, the study focused on the frequencies that each musician posted for a whole year 2016.

In addition, the 20 musicians were selected in this study for obvious reasons; first, they are people who have a majority followers in the fans on social media. The availability of a large number of followers on Facebook and Twitter allows this study to have a wide range of data from many different parts of the world. Other than having many followers, the musicians social media sites are easily accessible to all. Also, these are the people who frequently use social media in conducting most of their businesses, and advertising their music. These reasons made the study to choose these musicians collection of data for the analysis purpose. There are many celebrities who could have been selected for the purpose of this study, however, choosing twenty musicians made the study to be more general and all inclusive (Ali and Bhaskar, 2016). Also, music seems to have more fans than any other field. Lastly, the twenty musicians were selected from a list of the most popular musicians. This means that only the best and those with the highest number of followers were selected. The reason for choosing people with many followers on social media is because digital marketing depends on the availability, reachability, and accessibility of information to the consumers. In other word, the study requires that a higher number of people have to be accessible for the market to be consistent and effective.

Limitations of the Methodology

Content analysis strong and very good method for analysing data because it focuses on the text directly form people and thus gets to the central of social communication. It also allows for both qualitative and quantitative research, but it also has its limitations. Some of the disadvantages related to the method includes; it can be a very tedious method in terms of consuming time. The method is also prone to errors especially when making higher levels of interpretation. Also, the method lacks theoretical background in making the conclusions and inferences to the issues in question, this is because it is very difficult to automate and quantify. In other words, despite the fact that this method is a superb techniques of transforming qualitative data to quantities data, it is method which cannot be describe as a very accurate one (Bock, 1989). The limitation in this method is related to the issue of lack of both theoretical and description perspectives. Sampling and analysis procedure procedures make the theoretical relationship between concepts difficult to infer from findings. In many cases, therefore the results may be difficult to use in any analysis other than in modelling of the issues that have been discussed in the paper. However, this method was utilised in this study because none of the limitations could affect the results of this research in a negative way.


Ali, Z. and Bhaskar, S. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia, 60(9), p.662.

Bock, R. (1989). Multilevel analysis of educational data. San Diego: Academic Press.

de Graaf, R. and van der Vossen, R. (2013). Bits versus brains in content analysis. Comparing the advantages and disadvantages of manual and automated methods for content analysis. Communications, 38(4).

Ruane, J. and Cerulo, K. (2012). Second thoughts. Thousand Oaks, Calif.: Pine Forge Press.

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