What Are the Steps of Content Analysis?

Content Analysis is an effective tool used by researchers to identify patterns, themes, and relationships within a set of data. It is used to identify the presence of particular words, phrases, and other content elements. You will be surprised that there is so much information contained in your data when you start digging deeper. 

In a CX study where 102 CX experts were surveyed, Dan Gingiss, Chief Experience Officer at The Experience Maker, LLC, states the importance of content analysis,

"Collect feedback frequently across channels via surveys, ratings and reviews, customer service calls, focus groups, and one-on-one conversations. Analyze the responses and look for actionable insights. Listen for what you are doing well and do more of it! Then listen for what parts of the experience are missing the mark and try to fix the underlying issue."

It is easy for the researcher to get diverted into various directions if he/she is not following step-by-step content analysis. By following a set of steps, researchers can effectively analyze a set of data to uncover information, identify trends, and draw meaningful conclusions. 

The content analysis process can be broken down into 5 steps. 

Step 1: Identify and Collect Data  

There are numerous ways in which the data for qualitative content analysis can be collected. Both verbal and non-verbal methods can be used to collect the data from the participants of the study. Surveys, interviews, podcasts, social media comments, online feedback, web conversations, etc., are some of the ways in which the data can be collected.  

The seven major elements that are considered for performing content analysis are words, characters, themes, paragraphs, concepts, items, and semantics.

It is very important to capture the relevant information needed for the content analysis so that there is enough data for the intended content analysis. Just like any other research, content analysis also involves sampling, just that it is not the people or the products, the sample here is the content itself. The sample should be big enough to represent the entire population. Make sure to consider the appropriate time period for extracting the sample.  

Example: 

Content analysis using social media information about the destination image of a city or country. The aim of the content analysis is to find the destination image of the place. The analysis revolves around the ‘place’ that the tourists have visited and have expressed their opinions on social media. The goal of the content analysis is to collect a holistic view of the ‘place’ using social media data. The opinions are expressed by tourists who visited the ‘place’ and have expressed their experience on social media. 

For data collection, the data sources will range from social media pages, websites, blogs, online forums, travel websites, etc. So the data collection can be done by using the ‘place+’tourist’+‘Facebook’ search to identify the web pages where the data can be obtained. 

Step 2: Determine Coding Categories 

Measurement of content in content analysis is based on structured observation, which is a systematic observation based on certain written rules. These rules detail how the content should be categorized.  The categories defined for the analysis should be mutually exclusive. These written rules help to make replication easier and also to improve reliability.  

To be able to analyze the content, it is important to divide the entire content collected into categories so that it can be managed better. This is a process of selective reduction where the text is reduced to categories so that the research can be focused on the categories for specific words and patterns that answer the questions of the researcher.  

The categories or codes could be a word, a phrase, a sentence, an article, brand names, numbers, competitor names, countries, emotions, and much more. For example, ‘people in public life are coded as famous personalities, politicians, sportsmen, celebrities, etc.  

Step 3: Code the Content 

A code is a label that you assign to the text that has to be analyzed, and the text can be a word or a phrase.  For example, the code ‘politician’ is assigned when there is a mention of any political person in the text. 

During the coding process, a number should be assigned to each category. The code should be mutually exclusive.  

Coding is a set of rules that explain the method of observing the content in a given text. Coding will identify four important characteristics, frequency, direction, intensity, and space. 

• Frequency describes the number of times a particular code occurs.
• Direction is the way in which the content appears, positive, negative, opposite, support, etc.
• Intensity denotes the amount of strength toward a particular direction.
• Space refers to the amount of space assigned to the text or the size of the message. 

The list of words, phrases, images, videos, etc., is loaded to social media and other data sources to locate them in the source. Coding fetches highly reliable data as the word or phrase either exists or is absent. 

Example: 

Taking the above example, all the web pages that were shortlisted are combined into a master file. Coding software is used to identify the words/phrases/images from the web pages. There is lexical mapping software such as Leximancer that can identify various themes based on the cooccurrences of words/phrases/images across a text database. The frequency of the words/phrases/images is obtained and the frequency table is generated.  

Step 4: Check Validity and Reliability 

The next stage involves the testing of the codes that have been designed. The codes need to be validated for its reliability. The code has to be tested to check if it indeed measures what it purports to measure and to check if the results are consistent.  

Sampling validity refers to the examination and validation of the sample that was selected for the analysis. Semantic validity checks to see if the different phrases or words that are part of a category have a similar meaning and to make sure that they all belong to the same category. The correlation must also be checked to see if one measure can be substituted for another.  

A reliability check of the data is important to know if the data is reliable, which means that it should be constant throughout the measuring process. A reproducibility check is conducted by having numerous coders code sample data and compare the results. The data can also be checked for its stability, where a check is performed to assess the degree of content consistency over a period of time. An accuracy check should be performed to measure if the process conforms to the standard as expected and if it yields the results according to what it is designed for.  

The establishment of reliability is very critical in content analysis as any results without proper validation and reliability is considered useless.  

Step 5: Analyze and Present Results 

After completing the analysis, there will be several sets of information organized and available as files. This has to be presented in a report format that can be easily understood by the recipient.  

This involves a review of the final results, identifying patterns, arranging all the information in a sequence, and finally presenting it in the form of a report.   

The introductory sections of the report should address all basic information about the report such as: 

• The period of the study
• The location chosen for the study
• The aim and objective of the study
• Explain different tools and techniques used during the study
• Data sources and its composition 

The results section should contain detailed information about the various factors that were observed during the study. The results should be supported by data and presented in the form of graphs and matrices. A clear presentation of the information makes it easy for the reader to understand and interpret the report.

The results section should be able to offer a detailed analysis and summary of observations that were gathered during the study. It should be a straightforward commentary on the observations during the study. Include the important findings and avoid adding too much information that can bury the actual findings.  

The results should try to narrate the findings without adding too much of judgments or solutions. This section should give direction to the important stakeholders for further discussions and evaluations of the situation and encourage them to make decisions based on the report.