AI & Tech
Read articles and blog posts to understand how AI and technology is used to analyze unstructured feedback data at scale. Keep up to date with the latest in AI technology, including LLMs, Machine Learning, NLP, Prompt Engineering and more.
Qualitative Feedback: Examples, Types & Analysis Paid Members Public
Learn about qualitative feedback examples and types. Explore how businesses navigate the diverse landscape of customer insights from various sources.
The Primary Methods of Qualitative Data Analysis Paid Members Public
In academic research as well as in the business landscape, qualitative data analysis plays a crucial role in understanding and interpreting non-numerical data. Qualitative data analysis helps us make sense of the stories and personal narratives. In the business context, qualitative data analysis turns customer feedback into an in-depth understanding
How to validate your AI-driven insights Paid Members Public
AI-driven insights are a powerful tool to enable analysts to extract value from qualitative data like user feedback. Here's how to build confidence in the results!
How will LLMs change Customer Experience? Paid Members Public
If you work in customer experience (CX), this article is for you. Explore how LLMs are poised to make a radical difference in CX and beyond.
The future of insights: introducing Thematic Answers Paid Members Public
Stop searching your feedback data. With Thematic Answers, type in your question and get a detailed answer, along with quantified and verbatim evidence. Dive in and ask for more details. It's for insights on the spot!
Predictive Operational Data Analytics and NLP: complementary parts of the same world Paid Members Public
How can predictive operational data analytics and NLP work together to deliver amazing business insights?
Generative AI and Feedback Analysis: security and data privacy concerns Paid Members Public
How can you use generative AI safely? In this post, Alyona covers security concerns around generative AI, and addresses how to lower risks.
What does GPT-4 mean for Insights Professionals? Paid Members Public
How will GPT-4 change the work of insights professionals? Will it take over the insights and research landscape - or can we use it to our advantage?