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What is Content Analysis? 

Content analysis is a qualitative research tool or technique widely used to analyze content and its features.  It is an approach used to quantify qualitative information by sorting data and comparing different pieces of information to summarize it into useful information. 

The content can vary from simple words, text, and pictures to social media data, books, journals, and websites. Content analysis has been used increasingly by organizations to surpass surface-level analysis by using computers and machine learning for the automatic labeling and coding of text. 

In a study where 102 CX experts participated and spoke about the challenges they faced, Marlanges Simar, Senior Director of Customer Experience at Walgreen, highlighted the use of content analysis "Capturing the voice of the customer only in surveys and not investing in a qualitative study of the customer" as one of the biggest CX challenges. 

Example of Content Analysis

Research (Cruz and Lee 2014) was conducted to recognize the challenges that many companies are facing in developing Twitter campaigns. Content analysis was conducted to analyze the Twitter feeds of internationally recognized companies.

Various terms were grouped based on Aaker’s five brand personality dimensions framework, which is used to describe the traits of a given brand into five dimensions:

Sincerity, excitement, competence, sophistication, and ruggedness.

Sentiment analysis was also conducted using the Lexicoder Sentiment Dictionary, which performs the simple content analysis. 

The results of the content analysis highlighted two essential factors, word choice, and media type, for the success of a marketing campaign on Twitter.  These two factors should be considered while developing a social media marketing plan. 

Content analysis has seen rapid growth and acceptance due to computer-aided text analysis. It has become easier to perform content analysis due to the easy availability of electronic messages, thereby making it easier to analyze with precision and speed.

Development of Content Analysis 

Content analysis can be dated back to the 1920s in the United States of America, where a large quantity of data from mass media such as radio and newspapers was analyzed.

For example, the number of times a text, such as the name of a political party, was repeated in the newspaper was counted and analyzed. However, this was not foolproof as it could not identify the latent meaning, and it just counted the number of times a word was repeated.

Later in 1972, Jurgen Ritsert developed a process that could identify the latent meaning and ideological contents by applying quantitative analysis.  Ever since then, content analysis has been used to interpret the text and to arrive at a valid conclusion

With the advent of the internet and technological advancement, content analysis has gained particular significance. Over the years, many things have changed, and a few have remained constant. Computers are now used to gather, analyze, and present a massive amount of data with lightning speed and accuracy.

Content analysis of the big data produced by social media, online content, and mobile devices has taken higher significance. Content analysis has taken over as the most popular method compared to surveys, interviews, and other forms of analysis.

Never has content analysis received more considerable attention in many research fields than at present. It has been embraced and is extending far and wide into many disciplines.

Goals/Objectives of Content Analysis

The purpose of content analysis is to ‘read between the lines.’  It aims to determine answers to questions where the text implies something and is not necessarily explicit.

Content analysis is research that can analyze human communications, how people plan their lives, what people know about something, and how people react to something. 

Content analysis has become an alternative to the traditional inquiries of the mass media, which was then used for public opinion research. The content analysis employs methods to examine the data, images, printed text, sounds, social media, articles, books, journals and the web – mainly to understand what people mean, what people enable and what does the information conveyed by them say to the business or the society at large. 


The content analysis helped Nescafé Dolce Gusto to improve its campaign performance by 400%.  The goal of content analysis was to find and create a multi-channel marketing strategy that can attract coffee lovers.


They started by conducting content analysis. They rolled out market research into the coffee lover community online. They collected insights from the coffee lovers and used the information to design a suitable marketing campaign that considered factors such as the taste and needs of the coffee lovers.

As a result of this content analysis, Nescafé Dolce Gusto increased its Facebook engagement by 400%.

The objective of content analysis:

  • To Identify the implied aspects of the content
  • To sketch the characteristics of the content
  • To analyze and present significant findings of content clearly and effectively
  • To simplify unstructured content
  • To identify trends and relationships
  • To spot the intentions of individuals or groups of people or an institution
  • To describe attitudinal and behavioral responses to communications
  • To determine the psychological or emotional state of a group of people
  • To justify an argument

To summarize, content analysis is conducted to yield inferences from different kinds of content, such as text, pictures, and social media data.

Sources of Content Analysis

Content analysis forms the bridge between quantitative and qualitative research methods, where some of the organizational issues that are very difficult to study, such as the organization's behavior, human resources, and customer issues, can be considered.

By analyzing the presence of certain words and text within a given qualitative data, the relationship between words and pictures, the researchers can make inferences about many vital aspects such as the audience, behavior, culture, and level of satisfaction. 

The sources of data for content analysis are primarily two types:

1. Offline  

The offline content analysis is based on books, journals, essays, interviews, research notes, open-ended questions, and directories. The sample from offline sources will represent the whole universe. However, in many cases, offline data can be outdated. 

2. Online

With the rapid growth of the internet, online data sources have acquired significance. The online conversations, social media comments, product reviews, and customer feedback are collected from the most recent and updated references, thereby making the data source more relevant. 

Example of Source used for Content Analysis

Social media posts and conversations are a rich source of text data for content analysis. Data can be extracted using tools. The obtained data look


When the data is cleaned up to identify keywords, the result will be much more precise.


With the above information, it will be much easier to analyze the post and decide the next steps. 

Uses of Content Analysis

Content analysis can be applied to analyze any piece of content that is written or verbal. Content analysis involves various fields such as politics, human behavior, marketing, literature, health, psychology, and much more.

Content analysis also displays a close relation between linguistic factors and psychological aspects, thereby leading to the development of artificial intelligence. 

Examples of the Uses of Content Analysis

For example, a brand can discover emerging trends using content analysis. Content from online conversations is obtained from various sources such as news, feedback, blogs, tickets, online discussions, social media, and reviews.

Once the data is available, the data has to be sliced and diced using algorithms and proven mathematical models. Topics, relationships, and tone intensities are analyzed to identify patterns, correlations, and inferences at multiple levels.

Below is an example of an analysis of customer data relating to online cosmetics.



As content analysis deals with text, numbers, comments, statistics, and more measurable facts, it is used for forecasting, trend analysis, and drawing logical strategies. It is used widely to remove the ambiguity factor and eliminate opinions and guesswork.

Content that you gather is subjective, and hence using it to analyze and define it more quantitatively helps to arrive at decisions. Therefore, content analysis is essential. It has the following benefits:

  • Establishes proof of the reliability of the data
  • Allows both quantitative and qualitative analysis 
  • Offers valuable insights into history by analyzing information
  • Provides analytical insight into human thought and language
  • To Identify the trends and intentions of an individual or a group
  • Understands both human behavior and the use of language, and their relationship 

The use of content analysis depends on how you use it. For example, when you release an article on your blog page, content analysis will help you understand the journey.

How many people read it, how many liked it, how many shared it, how many people visited your website after reading your article, and how much sales increased after releasing it. 

When you look at the content analysis reports, you can identify several areas that are doing well and the specific regions where you will have to devote attention to their improvement. All this would not have happened without content analysis. 

Approaches to Content Analysis

Content analysis can be performed in three different methods: conventional, directed, and summative. Though there are three different approaches, they intend to understand and analyze the meaning of content. They do have specific differences, which are predominantly in the coding system.

1. Conventional Content Analysis

Also called inductive category development, this approach is used when the existing theory or research on any given subject is limited. Here data is used as a source to arrive at categories rather than using any of the pre-existing categories.  In this approach, the researchers rely entirely on the data for new insights. Most qualitative analysis methods use this approach to study and analyze.

2. Directed Content Analysis

In this approach, research is based on an existing theory.  This approach of content analysis is used to validate or further analyze the already existing theory.  This method can be done in two ways. One way is to start coding the data based on the predetermined codes from the earlier approach. Another way is to review the existing codes and assign new codes for the text that could not be categorized in the previous method.  The directed content analysis aims to focus on and extend the pre-existing theory to determine the key concepts.

3. Summative Content Analysis

In this approach, the words of text will be initially counted and compared, followed by further interpretation of the content. The summative content analysis aims at finding the underlying meanings of the text or words.  In this approach, the study starts by searching for a particular text and counting the number of times it appears and further tries to understand the fundamental context for using the words, either explicitly or in indirect terms. Summative content analysis is a nonreactive method of studying the phenomenon of interest.

The content analysis approaches depend on the research purposes that may need different research designs and various analysis techniques. The researcher should make the choice of using a conventional or summative, or directed approach after considering the purpose and the methods.