It’s safe to say artificial intelligence, and more specifically generative AI, has had a transformative impact on the market research sector. From the contentious emergence of synthetic participants to the radical survey personalisation that chatbots are now able to deliver – the industry has fully embraced this new leap forward in technological innovation. And FlexMR is no different. Over 2023, we took a complete, strategic stocktake of the capabilities that InsightHub offers – to assess which opportunities offered by AI would be most valuable to our clients.
Our goal is to become the global leader in strategic customer insight management. That means empowering research teams to drive informed decisions and build assets which enable the efficient management of customer insight. It means delivering top quality services, consultancy, and technology. And it means always looking to the future.
InsightHub, our premier online research platform is designed to facilitate end-to-end customer insight at scale. To achieve this, our dedicated product development team focus on building key pipelines of data collection, analysis and activation – embedded in a robust and flexible management system.
An important outcome of our stocktake was the need to build capacity for quick and efficient qualitative data analysis. That’s why we built TextMR, our second-generation AI coding tool that enables teams to deliver in-depth analysis at scale.
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| TextMR is a second-generation AI coding tool, available on InsightHub, that enables teams to deliver in-depth analysis at scale. |
Using TextMR, you can create rich, detailed analyses of qualitative data complete with themes, a bespoke code frame and sentiment breakdowns in just a few minutes. Input sources include open-ended survey responses, question board tasks, or community datasets such as forums or blogs.
Unique codes and themes are automatically generated for each analysis. Coding happens in just one click. All you have to do is wait a few minutes for the generative AI algorithm to process your data. Once complete, you’ll be able to view a complete breakdown of results and explore key themes with in-built filters.
The summary tab offers a concise AI generated synopsis of your analysis to help you quickly explain complex data, while the dashboard provides a visual representation of codes and participant sentiment. What’s more, text analyses generated in this way can be easily added to ActivateMR boards, which facilitate informed decision-making, better communication, and insight-driven collaboration.
So now, you don’t have to choose between rich, qualitative analysis or quick, efficient research. Instead, you're empowered to deliver both - exceptional qual at substantial scale. To find out how TextMR and the InsightHub platform can help you inform more business decisions, watch our short introductory demo.
In launching TextMR, we aim to enhance insight team capabilities and automate a historically complex, time-consuming task; giving researchers more time to act as expert consultants to critical business decisions. Over the next 12 months, we will continue to extend the capabilities of TextMR and explore other AI enhancements to the InsightHub platform, whilst maintaining our strict standards of information security and responsible innovation.
But that’s not to say there’s few reasons to get started today. Here's a few of the key benefits we hope users of TextMR will be able to experience.
Qual at Scale: Natural language AI algorithms can process vast amounts of text data in a fraction of the time it would take human analysts. This efficiency is crucial in today's fast-paced business environment, where the volume of data that can be generated from a single survey often overwhelming. AI-powered text analysis allows researchers to quickly sift through massive datasets, identifying patterns and trends that may not be immediately apparent.
Automated Sentiment Analysis: Understanding customer sentiment is crucial. AI-powered sentiment analysis can automatically assess the emotional tone expressed in text data, helping businesses gauge customer satisfaction, identify areas for improvement, and respond promptly to emerging issues.
Identifying Emergent Trends: AI algorithms can perform advanced topic modeling, categorizing large datasets into relevant themes or topics. This capability is invaluable for identifying emerging trends, understanding what topics are resonating with the audience, and staying ahead of industry developments. Researchers can use this information to adapt strategies, launch targeted campaigns, and capitalise on evolving market preferences.
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| AI text coding enables quick identification of emergent trends, contextual understanding and rich qualitative feedback - all made available at the speed of business. |
Contextual Nuanced Understanding: Natural Language Processing (NLP) enables AI to understand the context and nuances of language. This is particularly beneficial in market research where the meaning of words and phrases can vary. AI can discern sarcasm, irony, or cultural references, providing a more accurate interpretation of textual data. This contextual understanding ensures that market researchers don't misinterpret customer sentiments or intentions.
Competitor Analysis and Benchmarking: Because code-frames are generated per analysis, it’s possible to ask questions and explore themes regarding customer perception of competitors. This allows businesses to benchmark themselves against rivals, identify strengths and weaknesses, and uncover opportunities for differentiation.
Real-Time Insights: The speed at which TextMR processes data allows businesses to gain real-time insights. This is crucial for making proactive decisions in response to rapidly changing market conditions. Whether it's adapting marketing strategies, addressing customer concerns, or capitalizing on trending topics, AI-powered text analysis enables businesses to stay agile and responsive.
Want to know more? You can find a complete guide to TextMR, including an interactive demo of the new tool, on the InsightHub Help Centre.