You know you need to collect customer feedback. You send out surveys and read reviews.
But once you have customer feedback in-hand, what do you do with it?
How do you identify common themes in customer responses — and turn that into actionable business insights?
But this takes precious headcount and a ton of manual effort.
Or you could spend hundreds of thousands of dollars to buy expensive text analysis software that requires a lot of specialist work on the backend — without much actionable output.
What if there was a more efficient, less expensive way to learn from your customer feedback?
Enter thematic analysis software.
In this article, we’ll cover:
- The definition of thematic analysis
- How thematic analysis software works
- Why you need thematic analysis software
What is thematic analysis?
Thematic analysis is a form of qualitative data analysis (QDA) that extracts themes from text by analyzing the word and sentence structure.
When you use thematic analysis to analyze your customer feedback, you can quantify the common themes in customer language.
This helps you measure customer satisfaction in an accurate, actionable way.
Thematic analysis vs. sentiment analysis
Sentiment analysis is a similar form of qualitative data analysis.
Rather than focusing on themes, sentiment analysis focuses on how positive or negative the language used in customer feedback is.
Sentiment analysis helps you identify emotionally charged themes, which are more likely to trigger positive and negative word of mouth among customers and prospects.
By identifying themes across customer feedback, thematic analysis gives you more specific insight into your customer.
Thematic analysis is more nuanced and actionable than sentiment analysis.
To learn more about how thematic analysis compares to sentiment analysis, check out this post.
What is thematic analysis software?
Thematic analysis software automatically breaks text — in our case, customer feedback — up into themes.
Identifying these themes help you figure out not only how your customers feel about your brand, product, and/or service, but also how important different factors of the customer experience are to them.
Do they prioritize comfort over affordability? Would they rather pay more for faster service? Thematic analysis software can help you find (and act on) those answers.
Thematic analysis software is autonomous, meaning:
- You don’t need to set up themes or categories in advance
- You don’t need to train the algorithm — it learns on its own
- You can easily capture the “unknown unknowns” to identify themes you may not have spotted on your own
How does thematic analysis software work?
Here’s how thematic analysis software automatically analyzes customer feedback to identify and extract themes.
Natural language processing (NLP)
Natural language processing (NLP) is a subcategory of linguistics and AI.
NLP focuses on programming computers to process and analyze large amounts of natural language data, aka text.
Thematic analysis software uses NLP (Natural language processing) to analyze large amounts of free text, then displays that analysis in analytic tools and dashboards.
When a computer understands the meaning of words, sentences, and text, we call it natural language understanding, or NLU.
NLU is a subcategory of NLP and AI.
Thematic analysis software uses NLU to go beyond simply categorizing customer feedback: NLU helps derive the meaning of your customer feedback.
By understanding the specific themes that emerge from customer feedback and which themes have the biggest impact on customer experience, you gain access to more actionable insights to improve the customer experience.
Verbatim analysis or text analytics
Text analytics involves using NLP and machine learning to extract meaning from text.
With thematic analysis software, this can involve analyzing customer survey responses to find common themes.
Thematic analysis software uses text analytics to analyze free-text feedback to the open-ended questions in customer surveys and feedback forms.
Verbatim analysis helps us find “unknown unknowns:” hidden, recurrent customer pain points that you may not have ever considered.
By tracking these trends and issues over time, you can address the feedback head-on and measure the success of your customer experience initiatives.
Text analytics can sometimes have a difficult time parsing negation.
For example, imagine a customer responds to your survey with, “There’s nothing I did not like!”
Many text analysis systems will see “did not like” and automatically categorize the feedback as negative.
The best thematic analysis software has the AI and deep learning capabilities to recognize positive feedback — even if it’s couched in negative language or phrases.
Thematic analysis software can also use word embedding to organize similar phrases into themes that are easy for you to review, edit, and prioritize.
Word embedding refers to the machine learning models that learn to map a collection of words and phrases to vectors of numerical values.
This helps computers process, understand, and categorize text more accurately and efficiently.
To put it simply, word embedding translates our language (a vocabulary) to a computer’s language (vectors).
Let’s say you work for an airline, and you’re trying to analyze customer feedback.
One customer writes, “The flight attendant was helpful when I asked to set up a baby cot.”
Thematic analysis software would extract themes such as “flight attendant”, “flight attendant was helpful”, “helpful”, “asked to set up a baby cot”, and “baby cot.”
Here’s how Thematic’s custom word embeddings implementation breaks down and categorizes that feedback:
Word embedding translates these words and phrases into language that a computer can understand, categorize, and analyze.
This helps thematic analysis software recognize these as meaningful themes when the entire dataset is analyzed.
Why you need thematic analysis software
Now that you know what thematic analysis software does, what about the why?
Here’s how companies across industries can benefit from adding thematic analysis software to their tech stack.
Save time and increase accuracy
When you’re running a business, time is a scarce resource. Thematic analysis software can save your team hundreds of hours a year.
Imagine you have to read each individual piece of customer feedback you receive, then code themes and sentiments into an Excel spreadsheet.
Analyzing customer feedback can be an incredibly time-consuming task, even for small businesses.
With thematic analysis software, you no longer need to go through each comment manually.
You can spend less time compiling and coding the data, and more time acting on the insights you gain.
Thematic analysis software can also help you avoid human error. Even the best human coders make mistakes, especially when analyzing hundreds and hundreds of customer responses.
For example, we once tested Thematic against a human coder, Kate, when analyzing student feedback at a university.
Thematic identified food quality as one of the key things students would like to see improved. Kate found the same issue, but at a much lower frequency.
Why? When Kate looked at the student feedback, she tagged only the key issues in each comment.
When Thematic’s software analyzed the feedback, it tagged every issue mentioned in each student comment.
As a result, the university could take action to increase student satisfaction simply by improving the quality of the food.
By using thematic analysis software, human coders like Kate no longer have to analyze and code each piece of feedback.
Instead, they can use their expertise to interpret the results that thematic analysis software provides.
They can help figure out what the most important results are and how to act on them, adding a human touch to the way you use thematic analysis.
Plus, using thematic analysis software can help you find themes and pain points you may not have found manually — because you weren’t looking for them.
When people look at a dataset, we tend to view it through the lens of our own experience and biases.
Thematic analysis software can help avoid bias in your results; software tools don’t over-emphasize or ignore specific comments or come to unquantified conclusions.
Quantify customer feedback
When we talk about quantitative customer feedback, NPS scores often come to mind.
And while NPS scores can be useful snapshots of customer sentiment, they don’t always tell the whole story.
Why did one of your most loyal customers rate you an 8 instead of a 10? Why did one promoter churn, while a detractor doubled their orders per month?
On the other hand, qualitative feedback — customer surveys and comments — can be hard to quantify.
How can you tell if your customer experience has improved if you’re only dealing with text?
Thematic analysis software helps you quantify customer sentiment on specific things. In turn, this gives you the hard data you need to measure the success of an initiative.
You can also quantify the NPS impact of taking action to address a specific customer pain point.
“This has made it much easier to get projects across the line, with hard data that we can use to measure success of an initiative.”says one Thematic user on G2 Crowd.
“Better yet, we can see how specific themes impact NPS scores!”shared another.
Make data-driven decisions and track results
Quantifying customer feedback helps you understand the business impact of each customer’s feedback — and the impact on feedback when you make a change.
Good thematic analysis should provide information that’s easy to act on.
Going back to our university example above, knowing that so many students feel negatively about the quality of food highlights a clear pain point with a pretty straightforward solution: Improve the quality of the food.
Once the university puts initiatives in place to address the complaints about food quality, they can measure whether or not student satisfaction increases by re-surveying students.
Thematic analysis will show whether that theme continues to come up, plus how sentiment around that theme has (or hasn’t!) changed.
Thematic analysis software
Many traditional NLP APIs are designed to work on any type of text.
This may make them versatile, but it also means they’re less equipped to accurately analyze the nuances of customer feedback.
At Thematic, we built our thematic analysis software with a focus on customer feedback analysis.
We use complex negation algorithms that separate positive from negative themes.
And this feedback-focused approach works: 87% of our customers increase their NPS by at least 8 points after using Thematic.
How Thematic works: Combining AI with a human touch
We know that every business is different, which is why Thematic lets you combine your unique expertise with powerful AI.
Thematic pulls customer feedback from every channel into one place, then uses NLP to analyze each dataset individually.
We provide a unique set of themes for each dataset that gives insight into your customer feedback.
These theme lists are organized in a way that makes them easy to edit and customize, first by human data scientists at Thematic, and then by your team.
In the Themes Editor, you can adjust themes to make results more relevant to your business’s goals and priorities.
This combination of AI, NLP, and a human touch provides you with a list of themes that is:
- Contextually accurate
- Varied enough to cover all of the topics in your dataset
- Meaningful for you and your priorities and goals
Once you have your themes list, Thematic displays your analysis through customizable dashboards and analytic tools. These tools let you:
- Measure the importance of each theme
- Compare each theme across different segments of your customer data, such as demographics or tenure
- Calculate each theme’s impact is on customer satisfaction, loyalty, churn, and spend
Here’s what our process looks like:
At the end of the day, Thematic is all about helping your business become more customer-centric.
We take the manual, time-consuming analysis out of collecting customer feedback, giving you the time and tools to focus on what you do best: Creating a great experience for your customers.