Blog Practical know-how for surveys, analysis and reporting.
Find guides, methods and perspectives for your work with data.
Featured
Analyzing NPS Comments with AI: From Scores to Real Customer Understanding
The NPS score alone is not enough. Learn how AI-powered text analysis automatically evaluates thousands of NPS comments — aspect-based, segmented by Promoters, Passives, and Detractors.
Analyzing Employee Surveys with AI: A Guide for HR Teams
How HR teams use AI text analysis to systematically evaluate thousands of free-text responses from employee surveys – with data protection and the works council in mind.
AI Text Analysis and Privacy: A Customer Feedback Checklist
Analyze customer feedback with AI: review data flows, legal basis, providers, access and deletion. A practical checklist for research and CX teams.
No articles found.
Guides & methods 24
AI Maturity in Organizations: From Excel to Integrated Analysis in 5 Levels
Where does your organization stand with AI-powered text analysis? Our 5-level maturity model shows the path from manual Excel analysis to integrated analysis – with self-assessment and a concrete migration path.
Analyzing CSAT Comments: From Numbers to Action
How aspect-based sentiment analysis turns CSAT comments into concrete action recommendations – and why the score alone is not enough.
From Email to ERP Record: AI Data Extraction in Logistics
How AI-based data extraction turns delivery notes, emails and freight documents into structured ERP records – with a fictional example and an approach to calculating ROI.
Preventing Hallucinations in AI Chatbots: 5 Strategies for Reliable Answers
5 proven strategies against hallucinations in AI chatbots: RAG grounding, source citations, confidence scoring, guardrails, and human-in-the-loop for reliable enterprise chatbots.
The Build vs. Buy Decision: Build Your Own AI Text Analysis or Use a Platform?
Build your own AI text analysis or use a platform? We show the cost blocks of building in-house and how to compare the platform side for your volume, point out hidden traps, and provide a framework for the right decision.
What Does AI Text Analysis Cost? Pricing Models and Total Costs
Compare licenses, data volume, setup and review effort: a practical guide to calculating total AI text analysis costs for research and CX teams.
RAG Explained: How AI Chatbots Work with Enterprise Knowledge
Retrieval-Augmented Generation (RAG) makes AI chatbots intelligent: instead of hallucinating, they access real enterprise knowledge. Here is how the technology works in detail.
Chatbot vs. Search: Why Classic Search Fails in Knowledge Bases
Keyword search, semantic search, or RAG chatbot? Why classic search functions fail in knowledge bases and how AI chatbots deliver direct answers.
Multilingual Text Analysis: How to Analyze Feedback in Multiple Languages
Three approaches to multilingual text analysis compared: language-specific models, multilingual models, and translate-then-analyze. Which approach delivers the best results?
Intent Detection: What Customers Really Want — and How AI Finds It
Sentiment tells you how customers feel. Intent tells you what they want. Learn how AI automatically detects purchase signals, intentions to cancel, and feature requests in customer feedback.
From Raw Data to Dashboard: Visualizing Text Analysis Results
How to properly visualize text analysis results: the 5 most important widget types, drill-down concepts, and dashboard design for different stakeholders.
Topic Analysis vs. Keyword Analysis: What Actually Finds the Relevant Topics?
Keyword lists only find what you search for. AI topic analysis finds what actually exists in your data. A systematic comparison using a fictional example.
ROI of AI Text Analysis: How the Investment Pays Off
How to calculate the ROI of AI text analysis: from direct savings to quality improvements to strategic value. With a concrete example calculation.
Analyzing Employee Surveys with AI: A Guide for HR Teams
How HR teams use AI text analysis to systematically evaluate thousands of free-text responses from employee surveys – with data protection and the works council in mind.
AI in Market Research: Analyzing Open-Ends Faster and Better
Manual coding of open-ends is expensive, slow and often inconsistent. Learn how AI analyzes thousands of free-text responses in a structured way – and how to check the quality.
Anonymizing Text Data: Methods, Examples and Limits
Removing names may not be enough. Learn how to check free text for identifying details, combine automated detection with review and preserve useful findings.
Analyzing NPS Comments with AI: From Scores to Real Customer Understanding
The NPS score alone is not enough. Learn how AI-powered text analysis automatically evaluates thousands of NPS comments — aspect-based, segmented by Promoters, Passives, and Detractors.
AI Sentiment Analysis: How Companies Turn Customer Feedback into Strategy
Learn how AI-powered sentiment analysis automatically evaluates unstructured customer feedback – and why traditional methods fall short.
AI Text Analysis and Privacy: A Customer Feedback Checklist
Analyze customer feedback with AI: review data flows, legal basis, providers, access and deletion. A practical checklist for research and CX teams.
5 Reasons Why Companies Should Invest in AI Text Analysis Now
The technology is mature, data volumes are growing, customers expect more. Five reasons why now is the right time for AI text analysis – and why waiting isn't a neutral option.
Structured vs. Unstructured Data: Why So Much Feedback Goes Unused
Most business data is unstructured text. Learn why that's a strategic problem – and how AI text analysis solves it.
Text Mining and Text Analysis: Methods, Practice, and Business Applications
From sentiment analysis to named entity recognition: how modern text mining works and where businesses use it today.
Hybrid Intelligence: Why the Best Decisions Come from Humans and AI Together
Neither pure AI automation nor manual analysis delivers optimal results. Hybrid Intelligence combines both strengths – here's how it works in text analysis.
What is AI-Powered Text Analysis?
Learn how artificial intelligence transforms unstructured text data into valuable business insights – from customer feedback to market research.
Perspective: AI & society 8
Articles on the job market, law, ethics and the environment.
AI and CO2: What Actually Matters in Text Analysis
AI applications do require computing resources, but their environmental footprint is not determined by the model alone. For insights and CX teams, the key question is how queries, data volume, and real-world usage interact.
How much CO2 does an AI query really use? A practical view for market research and CX
CO2 claims about AI are often reduced to a single number — which makes them sound precise, but usually misleading. For market research and CX, the real question is what kind of request, model, and workflow sits behind that number.
AI and the Job Market: 92 Million Jobs at Risk — or New Opportunities?
92 million jobs could disappear by 2030 due to AI. But 170 million new ones may emerge. What's true — and what does it mean for you?
AI Bias: When Algorithms Discriminate — and Nobody Notices
AI systems discriminate — often unnoticed. How bias enters algorithms, its consequences, and what companies can do about it.
EU AI Act: What the World's First AI Law Means for Your Business
The EU AI Act is in force. What must businesses comply with? Risk levels, deadlines, obligations — a practical guide.
AI and Copyright: Who Owns the Training Data?
$1.5 billion settlement, artists suing, new laws: How copyright is reshaping the AI industry.
The Ecological Footprint of AI: The Hidden Cost of Intelligence
AI data centers will consume 1,050 TWh of electricity by 2026. What does AI's energy hunger mean for climate and environment?
AI and the Military: Where Is the Red Line?
AI and the military: Anthropic rejected a $200M Pentagon deal, OpenAI stepped in. Where is the ethical line for AI and weapons?
See the analysis in action
We’ll show you surveys, analysis and reporting in deepsight cloud.