How to Use Natural Language Processing in Market Research: Sentiments, Thematic Analysis, and More
Savannah Trotter • 7 Mar 2024
Technology drives innovation and change.
The printing press drove the democratization of knowledge. The light bulb led to the first domestic electrical wiring, paving the way for countless in-home appliances. And now, we are watching as Artificial Intelligence (AI) transforms the way we live and work.
Within AI there are many branches, each suited for a specific use case. But one particularly interesting branch is Natural Language Processing (NLP), which has revolutionized the way we understand the written word. This is especially true within the market research field, where NLP has had a transformative impact on deciphering the wealth of textual data.
In this blog, we'll dive into the world of natural language processing, exploring its essence, applications, and the profound impact it has had on our ability to analyze text at scale.
What is Natural Language Processing?
Before we get too deep, let’s cover the basics.
Natural Language Processing is a subset of AI focused on the interaction between computers and human language. It enables machines to comprehend, interpret, and analyze text.
In market and consumer research specifically, NLP is used for text analysis on open-ended survey questions, product reviews, social media comments, or other sources of text-based data.
How to Use NLP: Use Cases in Market Research
1. Understand Consumer Sentiments
While multiple-choice or ranking-style questions can give you some insight into consumers' perceptions of your brand or product, it's difficult to get the full picture.
NLP allows you to take raw customer feedback and analyze it to identify how people feel about your brand, product, or messaging. It does this by examining the text-based data it’s given, categorizing the emotional tone or attitude expressed in each piece of text. For those curious, this involves analyzing individual words and phrases to discern whether the overall sentiment is positive, negative, or neutral
The data you receive not only aids in assessing customer satisfaction but also enables proactive decision-making and targeted improvements based on the identified sentiments. Ultimately contributing to a more customer-centric and responsive approach.
2. Uncover Trends & Patterns
Because NLP algorithms can scour vast amounts of unstructured textual data, it can easily uncover emerging trends and patterns in your customers' feedback. For example, maybe you notice that customers keep mentioning support wait times in a negative context. Or, maybe an analysis of your product reviews yields insight into a new competitor encroaching on your market share.
These insights allow you to see patterns emerge, long before they affect your bottom line. Enabling your organization to develop strategies that align with the evolving market landscape.
3. Find the Language that Customers Use
How confident are you in the language you use to describe your brand or offerings?
While your marketing, sales, or product teams may use certain words or phrases to describe and promote your products, that doesn’t necessarily mean it’s the same language used by your customers or target market.
By using NLP on raw text data, you can find commonalities in the descriptive words used by your customers and target audience. These insights will allow you to craft messaging that better aligns with the natural language surrounding your brand, products, or industry, helping to set you apart from the rest of the pack.
The Benefits of NLP for Text Analysis in Market Research
Make Data-Driven Product Decisions
By analyzing product feedback with NLP, you can pick out common issues, uncover barriers to adoption, and discover unique ways customers may be using your product. The insights will help you drive your product development in a customer-centric way, tailoring your new launches and updates to the needs and use cases you know to be true.
Improve Your Messaging
Once you understand the words and phrases your customers use when discussing your product, you can insert them directly into your messaging and marketing collateral. Doing this will not only show your customers that you understand their pain points, but it will also allow you to speak their language in a way your competitors just can’t.
Enhanced Accuracy
When combing through hundreds, if not thousands, of text-based data snippets, human error is bound to occur. NLP on the other hand operates with remarkable precision, minimizing the risk of misinterpretation or oversight. Ensuring the insights derived are reliable and reflective of actual sentiments and trends.
Scalability
As your business grows, the volume of textual data will also grow exponentially. This is where scalability becomes a critical factor. NLP systems can effortlessly handle large datasets, making it feasible to analyze extensive amounts of information swiftly. This scalability is particularly advantageous for businesses aiming to expand their market research efforts as they grow.
Text Analysis with SightX
The SightX platform is the only tool you'll ever need for market research: a single, unified solution for consumer engagement, data collection, advanced analysis, and reporting. While powerful enough for insights teams at Fortune 500 companies, the user-friendly interface makes it simple for anyone to start, optimize, and scale their research.
With our Generative AI consultant, Ada, you can harness the power of OpenAI’s GPT to transform your marketing research and insights. Collaborating with Ada is like having an expert researcher, brilliant statistician, and ace marketer on your team, helping you ask the right questions, choose the best experiments, pick out key insights, and seamlessly apply them to your business.
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