Narrative analysis serves as a text-analytical tool that breaks down the story structure of a narrative to identify the underlying meanings and themes. Humans are built to construct and follow narratives, making them invaluable tools for businesses of all kinds. For business professionals, narrative analysis allows you to gain insights about consumer behaviors, uncover production flaws, and boost sales.
In this detailed guide developed by our team of experts at Business2Community, we’ll walk you through everything you need to know about narrative analysis. From real-life examples to its limitations, you can nurture your business growth and prepare yourself for more lucrative opportunities.
Narrative Analysis – Key Takeaways
- Narrative analysis is a qualitative research method that studies human narratives to build a story structure to analyze human behavior.
- The two main types of narrative analysis are inductive narrative analysis and deductive narrative analysis.
- This qualitative research method can be affected by personal bias so incorporate other techniques to compensate for its weaknesses and generate comprehensive results.
What is a Narrative Analysis?
Narrative analysis is a qualitative research method that analyzes the human experience to gain a deeper understanding of the underlying meanings and themes behind a study group’s personal stories. For business professionals, this method allows you to delve into consumers’ minds and get a good idea of their expectations and preferences.
To carry out a narrative analysis, research participants will first have to document their personal narratives through qualitative data collection methods like narrative interviews, journals, reviews, recordings, etc. Then, as the researcher, you need to examine the narrative structure to identify patterns and the core narratives expressed.
By evaluating individual narratives, you can construct the complete story of the theme you are interested in.
This qualitative research method is a crucial tool in the business world in facilitating product improvements and production flow. In a business context, narrative analysis aims to help you analyze your audience’s experience and feelings so you can improve and refine the user experience.
Who Needs to Do a Narrative Analysis?
Narrative analysis benefits a wide range of stakeholders. To demonstrate its value, here are its applications in various roles:
- HR managers use narrative analysis to delve deeper into any existing work problems such as gender pay gap, unequal work treatment, and age discrimination. By collecting different narratives from employees, HR managers can target obstacles in the operation and address them accordingly.
- Business owners use this social science research method to dissect employee morale and opinions about the company to curate a more intimate work environment that fosters growth and harmony.
- Product managers use narrative research to analyze comments and reviews left by customers to improve product quality and enhance customer satisfaction.
- Corporate trainers use this narrative data analysis method to gain a broader understanding of the human behavior at the company to formulate suitable corporate training strategies to bring up performance.
How to Perform a Narrative Analysis
Before we show you how to conduct narrative analysis, let’s take a look at the two main narrative methods.
Types of Narrative Data Analysis
There are two main types of narrative methodologies, namely the inductive narrative method and the deductive narrative analysis method.
The inductive narrative method is about analyzing narratives through observation to discover the broader themes shared by the research participants. You are here to observe their story and identify key themes like the meaning and the conclusion. There’s no assumption involved when using this technique.
With deductive narrative analysis, you’re testing an existing theory against the narrative blocks. Through a narrative inquiry, you can either prove or disprove your theory.
Now that we’ve covered the two main narrative forms, it’s time to dive into conducting narrative research.
Step 1: Code Narrative Blocks
First, find the objective of your study and code your narrative blocks. The coding process ensures your topical stories are easily readable and understandable.
For example, imagine you’re a home sound system merchant and you’re interested in finding out how someone decides to have a home stereo system. Your narrative blocks are about the human experience of those who have a home sound system and their journey.
The code for this narrative analysis example would be “narratives about decisions on having a home stereo system”.
Step 2: Group Narratives By Life Event
You can gather the research participants’ stories about this particular life event by conducting in-depth interviews and transcribing narrative data.
Your narrative research explores the different reasons leading up to the purchase of a home sound system, continuing with the example. The reasons may include growing social media trends on the home stereo and the pressure of having a luxurious entertainment unit as a professional worker.
Step 3: Build a Story Structure
Once you’ve gathered all of the personal narratives from research participants about this life event, it’s time to analyze data and build a story structure. Structural analysis focuses on constructing a complete story. With your coded narrative blocks, you can build the story from start to finish.
Using the same example above, this structural analysis may reveal that most customers feel the need to upgrade their sound systems due to the growing demand for premium entertainment quality.
Then, the middle of the story focuses on the challenges they faced, which included the expensive price tags and complicated installation methods.
Finally, the story structure reveals customers’ excitement about finally having a premium sound system that could deliver a cinematic experience at home.
Step 4: Analyze the Story Structure
Oral histories presented by different research participants may vary. Narrative analysis presents different perceptions from different people, allowing you to identify similarities and differences.
At this stage, you need to analyze the narrative data of all your participants to understand where the patterns emerge and the differences between their stories.
Step 5: Compare the Story Structure
Capturing narrative data from your audience provides a holistic look into your audience’s behavior. Now, you can compare the story structure of your research participants to find out the core narrative of the study.
For example, you find similarities among entrepreneurs, who perceive having a home sound system as a symbol of their social status when having business guests over. On the other hand, most workers wanted a sound system as a premium entertainment unit for their own pleasure.
These elements contribute to consumers’ initial feelings about installing a sound system at home.
Step 6: Find the Core Narrative
After comparing the story structure, you can find the core narrative. In this case, the core narrative explains how the initial purpose of buying a home sound system can affect the subsequent feelings, satisfaction rates, and repurchase rates.
With the narrative analysis results, you can curate more personalized marketing campaigns that target different consumer groups to reap the more profits. You can also share the results with your team to formulate more effective production plans to offer the most appropriate services to your customers.
Examples of Narrative Analysis
Narrative analysis penetrates the business field as one of the most practical research methods in assisting professionals in gathering user reviews and opinions about a topic.
Below we have prepared two examples to further demonstrate the use of narrative analysis so you know how to find the core narratives easily.
Example 1: Use Narrative Analysis to Study Consumer Behavior
Narrative analysis is a fantastic tool for understanding why your best consumers prefer your products/services. Let’s take a brewery in New York as an example. Suppose you are the manager and want to learn about the main reasons that drive your customers back – this is coding your narrative blocks.
You group your narrative by life event, which in this case means you’re interested in visits to your location and reviews on your Google business profile.
Now you need to build a story structure, which could include why people decided to visit, why they had a good time – you can see from the samples that the dog-friendly atmosphere is a winner – and if there is any reasons people wouldn’t return. When you analyze the story structures you read deeper into each review in your sample and spot patterns, such as dogs, good drinks, lack of food availability.
Comparing story structures, you may notice that women enjoy the range of drinks whereas men enjoy the option to watch sports on-site. The core narrative from these reviews is that the pet-friendly policy works and people respond well to the setting so you could consider extra pet-friendly actions like free treats with drinks and also be sure to maintain your decor in the same style.
Example 2: Use Narrative Research to Identify Aftercare Problems
You run a big media subscription company and you are noticing a reduction in customer retention lately. You code your narrative blocks by choosing to look at narratives about your customers’ experience by looking at reviews left on Trustpilot.
By grouping narratives by life events, you gather negative reviews to try and better understand what are the drivers of dissatisfaction. Your story structure looks at the buying stage, delivery and setup, and post-sale aftercare. As you begin to analyze the story structure, you recognize complaints focused on supply chain issues and inaccurate resolution when a customer raises admin errors.
Looking into the story structure comparisons, you notice that there are specific products suffering from supply delays and that the digital customer service channel is most often noted as unreliable. In this case, your core narrative is that you need to improve the supply of spare parts for your products, which should increase customer lifetime value since they will use your product longer. You also choose to introduce a ticketing system in your digital customer service to ensure problems are trackable and resolvable.
How to Adjust a Narrative Analysis
Sometimes, the narrative analysis results may deviate from expectations. It can happen especially when you’re new to qualitative research methods and are unsure about the variables you can adjust to control the results.
There are several things you can do to adjust a narrative analysis to produce different core narratives to meet your business agenda:
- Update your data collection method. In qualitative research, there are often many ways to collect reliable information. Most of the time, they can lead to drastically different results as well. You can trial different narrative research methods like in-person interviews, online reviews, and recordings to examine the effectiveness of these methods in delivering quality results. There’s always more data out there to study and gain insights from.
- Increase your narrative study sample pool. To determine if your conclusion reflects reality, you can increase the sample size and interview more research participants. You can present your results with greater confidence if more research participants demonstrate the same patterns in the narrative analysis.
- Change your narrative research focus. Asking different focus questions allows you to see things from a different perceptive. For example, instead of asking “how” your consumers feel, you can ask them “why” they feel this way. Experiment with various narrative analysis focuses to determine the best one that matches your business goals.
Limitations of Narrative Analysis
Despite being a potent tool for offering a comprehensive understanding of emerging patterns in different focus groups, this narrative approach still has its limitations. When utilizing this technique, you should always be mindful of its disadvantages and conduct further analyses to complement your research.
The Results Can be Biased
Most qualitative analysis techniques face the same problem of generating biased results. As a text-based analytical tool, it can be challenging for narrative researchers to produce a coherent narrative due to the different interpretations of personal stories.
It Can Lead to Generalization
As noted, qualitative data analysis is often subjective. In the case of narrative analysis, you are analyzing the narratives of each individual research participant. Their testimonials may not represent the greater population.
The findings should not be generalized or used to represent your entire audience. You should incorporate other methods like discourse analysis to draw conclusions with greater confidence. Discourse analysis studies how communication affects social and cultural practices, which can consolidate your findings.
It is Time-Consuming
Gathering narrative interviews and organizing data can be time-consuming and challenging, especially if you’re collecting a large amount of data points. Although narrative analysis is simple to carry out in nature, the timeframe needed may be off-putting for small businesses without a ton of resources.
The Value of Narrative Analysis
Narrative analysis in qualitative research provides valuable insights for business owners about their company performance and brand image. With this technique, you can delve into the personal thoughts of your users and gather important information that can boost sales and enhance service quality.
Narrative analysis is a simple and effective tool for measuring consumer behavior and user experience. As a small business owner without any statistical background, this tool can serve as an excellent starting point in analyzing your business performance to refine product specifications and improve production flows.
However, no analytical tool is perfect. This narrative research tool can be biased due to the personal narratives involved. You should always utilize other techniques to ensure higher accuracy and produce meaningful results.