Market Research Automation: Trends, Tools, and What’s Next in 2025
Market Research Automation: 2025 State of Play Automation is reshaping market research in 2025. In a recent Displayr study, 85% of researchers said automated tools have already improved their workflow, namely by helping them save time and enabling faster insights. But how exactly are the top researchers leveraging automation? Who are the major players? What’s […]
12 Best AI-Powered Text Analysis Software Tools in 2025
Whether it’s social media comments, online reviews, or survey feedback, researchers need to find themes and take action. AI text analysis tools make turning text into strategic insights faster and easier. But in a crowded market, selecting the right tool for your needs can be difficult. Here, we look at some of the different options […]
Text Data Visualization: What It Is and How To Use It
Text data visualization is your not-so-secret weapon when it comes to telling impactful market research stories. In theory, it’s a simple process. Just collect your data, analyze it for key insights,and then transform these insights into memorable visualizations. But anyone who has ever attemted to wrangle survey verbatims into a bar chart knows it is […]
AI By You: How To Use Custom Prompts in Text Analysis
AI-powered text analysis is revolutionizing how researchers categorize open-ended responses—making it faster, more accurate, and easier to scale. That’s why it is now an integral part of Displayr’s text analysis capabilities. To maximize efficiency, we leverage advanced Artificial Intelligence (AI) and Natural Language Processing (NLP) to identify themes and automatically categorize your text data. However, […]
Build an Effective Text Analysis Dashboard (With 5 Data Visualization Ideas)
Introduction to Dashboarding for Text Analysis Text analysis is all about finding the meaning behind your text data. But then what? In many ways, the insights you generate from analyzing text are only as good as the dashboards you use to visualize the data. There exists a complex relationship between text analysis and dashboarding. Too […]
Transform Your Survey Data | Categorize Themes Using AI Text Analysis
Whether it’s customer feedback or employee engagement – to better understand your open-ended survey data is to better understand your business. Advancements in AI text analysis have given researchers the ability to categorize tens of thousands of verbatims in seconds, meaning they can identify themes and generate data-driven insights. Here, we show you exactly how […]
Comprehensive Guide to Text Analytics for Market Research
This comprehensive guide to text analytics for market research covers everything from thematic coding to sentiment analysis and – most importantly – how to implement it effectively. It is useful for anyone looking to extract insights from text and should show you that getting started with text analytics doesn’t have to be difficult. If you are […]
Prompt Like a Pro | AI Text Analytics Best Practices
As generative AI tools become more pervasive, writing clear and direct prompts has emerged as a critical skill. Prompts are instructions or queries that describe the task the AI should perform. For best results, they need to be clear, specific, and concise, providing context when necessary. AI text analytics prompts for market research If you’re […]
ChatGPT Text Analysis: How to Analyze Text with AI
Should you analyze text with ChatGPT? There are numerous ways to analyze text in 2025, whether that involves categorizing survey responses manually or utilizing a text analytics platform (like Displayr) to expedite the process. However, recent advances in AI now mean that a free tool like ChatGPT can be used to quickly generate insights. Here, we’ll examine some […]
Sentiment Word Cloud in R: Step-by-Step Guide + R Code
The Word Cloud above summarizes some data from tweets by President Trump. The green words are words that are significantly more likely to be used in tweets with a positive sentiment. The red represents words more likely to be used in negative tweets. The code I used to create this tweet is below. All you […]
Learn Text Analytics in R: A Step-by-Step Guide
Introduction Text analytics is the process of using computational methods to extract meaningful insights from text data. It combines techniques from statistics, machine learning, and natural language processing to help organizations understand and analyze large volumes of written content like documents, social media posts, and customer feedback. In this step-by-step tutorial, you’ll learn how to […]
Survey Text Analysis | Key Techniques for Extracting Meaningful Insights
Why Do We Need Text Analytics for Surveys? Survey text analysis enables organizations to extract valuable insights from free-form survey responses. By applying advanced techniques like sentiment analysis, topic modeling, and text mining, businesses can transform raw feedback into meaningful data that informs decision-making. In this guide, we will walk you through the key techniques […]
Text Analytics Software | Understanding the Features, Benefits, and Implementation
Introduction: Unlocking Insights with Text Analytics Software Text analytics software is a magic bullet for market researchers, marketers, data scientists, and anyone else who wants to unlock insights from text data. But how does it actually work? And what makes one tool better than another? Here, we break down all things text analytics software to […]
Implement Text Analytics for Effective Sentiment Analysis
Introduction to Sentiment Analysis Text analytics and sentiment analysis are essential tools for businesses to understand what people are saying about them online. While text analytics transforms unstructured data (like social media posts, reviews, and comments) into actionable insights, sentiment analysis goes a step further to determine whether those texts express positive, negative, or neutral […]
Get Started with Text Analytics Using Python
Why Python for Text Analytics? Text analytics is the process of examining unstructured text data to extract meaningful patterns. Of course, this can. be done manually by reading through various pieces of text to determine patterns and insights. But this is an arduous process, so we largely see it automated these days. Python, the programming […]
Explore Text Analytics Techniques and Implement Them Effectively
Introduction to Text Analytics Techniques We all probably know the ‘what’ and the ‘why’ of text analytics – but what about the ‘how’? Text analysis is an umbrella term for many different techniques, all of which involve extracting insights from text data. In this blog we’ll look at some of these different techniques, explain how they work, […]
Choosing the Right Type of Manual Categorization for Text Analysis
If you’re manually categorizing text data, Displayr will ask you to decide upfront whether to use Mutually Exclusive Categories or Multiple Overlapping Categories. If you’re unsure, you’ve come to the right place! Mutually Exclusive Categories means each of the text responses will be assigned to a single category. It’s appropriate if the data is relatively simple and each response really only captures […]
Learn More about Text Analysis in Displayr
Text Analysis in Displayr – General Resources These are the best places to start to learn about text analysis in Displayr. Webinar: The complete “how-to” guide for analyzing market research text data Ebook: Using Machine Learning to Automate Text Coding Fully-integrated Text Analysis with Displayr How to Set up Your Text Analysis in Displayr Technical […]
Thematic Coding vs. Sentiment Analysis: What’s Right for You?
Thematic coding and sentiment analysis – what’s the difference? In this blog post, we’ll examine when to use each method and explain why combining the two can yield the best results. Understanding Sentiment Analysis and Thematic Coding Sentiment analysis and thematic coding are two methods of qualitative data analysis that are (rightly) often grouped together. […]
Text Mining vs. Text Analysis vs. Text Analytics: Understanding the Differences
In this post, we’ll explore the similarities and differences between text mining, text analysis, and text analytics, and explain how these techniques can help you understand your data like never before. What is Text Analysis? Text analysis is the process of studying unstructured text data to gather insights. While the term is mainly used today […]
AI for Text Analysis | The Role of Natural Language Processing (NLP)
Are text analytics and natural language processing (NLP) the same thing? The short answer is no, but they are closely related. NLP plays a critical role in enabling effective text analytics, preparing data and laying the groundwork for powerful insights. AI for Text Analysis: Powered by NLP AI for text analysis – it’s now commonplace in […]
How to Calculate Sentiment Scores for Open-Ended Responses in Displayr
Sentiment analysis is a useful technique for calculating sentiment scores, which helps quantify the emotional tone of written text. In the context of surveys or big data, sentiment scoring can provide a more efficient way to gauge the overall attitude toward a brand, product, or service. Nothing is ever as accurate as having a researcher […]
How To Categorize Open-Ended Survey Questions
When you run a customer feedback survey and ask a respondent to enter some text as an answer, it is very likely most respondents will answer the same things, but phrased (or spelled) differently. Questions like these are called Open-Ended Survey Questions. The process of coding (a common term used to describe the process of […]
Text Analysis: Predicting Engagement from Tweets
Why do some tweets sizzle while others fizzle? This is a key question that predictive text analytics can help answer. By leveraging advanced algorithms and statistical techniques, predictive text analytics can identify patterns in text data that predict engagement levels, sentiment, and other crucial metrics. As an example, we consider a set of Donald Trump’s […]
Text Analysis: Hooking up Your Term Document Matrix to Custom R Code
I have previously written about some of the text analysis options that are available in Displayr: sentiment analysis, text cleaning, and the predictive tree. As text analysis is a growing field, you likely want to use your own tools on top of those already built into Displayr. To feed information about your text into a statistical […]
How to Set Up Text Analysis in Displayr: A Step-by-Step Guide
Text data can be an unwieldy beast. Whether you’re analyzing tweets, reviews, or open-ended responses from a survey, you will usually need to do some cleaning and processing of the text before you can conduct your analysis. Why is this the case? When you analyze text, you are counting the uses of individual words or […]
Using Text Analytics to Tidy a Word Cloud
Why text analytics for word clouds? A common occurrence when people are creating word clouds is that they want more control. This might mean limiting the word cloud to frequently occurring words, joining together words in phrases, or automatically grouping together words with the same meaning. The trick to doing this is to first tidy […]
At Last, Machine Learning Can Accurately Categorize Text Data
5 Machine Learning Breakthroughs to Accurately Categorize Text! For the last 20 years, the survey research industry has waited with bated breath for text analysis technologies to transform the way we analyze text data. In the last year or so, technology has reached a point where they can work with a high level of accuracy. […]
Fully-Integrated AI Text Analysis with Displayr
Oh, text data – you love what it can tell you, but if I had to guess – you do not like analyzing it. In a state of information overload, people are communicating digitally more than ever, whether through tweets, reviews, or open-ended responses to surveys. The data within those messages is an untapped gold […]
Automatic List Categorization of Text Data with Displayr
It can often be difficult and time-consuming to organize raw text data into meaningful insights. Manually coding even a single text question can take several hours, even with relatively small sample sizes. Displayr has built-in text categorization tools designed to help you quickly categorize your text data to help easily find valuable insights. One of […]
Automatic Language Translation of Text Variables
In the screenshot below, for example, a text variable called Multilingual has been selected, and the button for Language translation then appears on the right side of the screen. When this button is pushed, a dialog box appears asking you what language the input text is in, and what language you want it translated into. If you […]
Automatic Language Translation with Automatic Categorization
Our automatic categorization tool (Insert > Text Analysis > Automatic Categorization > Unstructed Text) now has the ability to translate both the input language, and the resulting outputs. So, if you have data in a language you can’t understand, you can still get the text data automatically categorized, with the results returned the language of […]
Automatically Classify New Text Data Using an Existing Categorization
Fully automated text analysis can, sometimes, do a great job. However, the gold standard for automatic categorization is to first get a human being to manually “tag” the data, then use machine learning to automatically categorize new data. This saves tons of time, not only when you are working with preliminary data sets and trackers, […]
Semi-Automatic Coding of Text Data: A Cutting-Edge Technique
Manually coding text data into categories is one of the great pains of survey research. By contrast, many automatic text coding tools ease the pain of coding but don’t do as good of a job. As a result, oftentimes people just use word clouds to analyze text instead. However, a recent breakthrough in coding can […]
Automatically Extract Entities and Sentiment from Text
Text data often refers to entities, such as people, organizations, or places. These entities can be automatically extracted from text data, and then used in further analyses. As an example, in this post, I reanalyze a famous set of tweets by a candidate for the US Presidency in 2016 and see how the sentiment relates […]
Automatic Categorization of Unstructured Text Data
Categorizing text data can be a time-consuming and expensive activity. In cases where time is short and budgets low, using automatic categorization of text data can save the day and give you a good idea of what’s contained in your data. In the following example, I have some text data collected in a survey about […]
Tutorial: Smartphone Marketing – What’s in a Name?
Make sure you read our blog post What’s in a Name? A Data Science Analysis of Smartphone Marketing before reading on! Creating the first table Add your data as a dataset in Displayr. In the Data Sets section on the left, click Insert a Data Set. You can then drag and drop your data, select a file from […]
How to Show Sentiment in Word Clouds using Displayr
The Word Cloud above summarizes some data from tweets by President Trump. The green words are words that are significantly more likely to be used in tweets with a positive sentiment. The red represents words more likely to be used in negative tweets. This post describes the basic process for creating such a Word Cloud […]
