Skip to content
Log in Start now →
Product
PlatformPricingDimensionsIntegrationsSecurityCompare
Solutions · by use case
Customer, guest and fan experienceProduct feedback and prioritizationRevenue, churn and retentionAgenciesContact center performanceAI agent and chatbot analyticsMulti-location performanceReviews and competitive benchmarking
Solutions · by industry
Hotels and hospitalityRestaurants and food serviceFitness and leisureRetail and e-commerceSports and live entertainmentInsuranceBanking and financial servicesSoftware and SaaSAutomotiveConsumer products and CPGContact centers and BPOsPublic sector and nonprofitReal estateGaming and betting
Learn
Artifacts GalleryCustomer storiesResearchBlogThought leadershipLessons Log in Start now

The Dimension Labs Blog

Connecting the dots on the data industry.

Essays, methods and analyses from the Dimension Labs team: where customer analytics is heading, what we find in real customer data, and how to do the work yourself.

Last updated Oct 27, 2026

Each star is a post.Lines run from a post to related later ones.
Pinned 4 min What Is an AI Analytics Agent for Customer Conversations? An AI analytics agent reads every ticket, chat, call, review and survey answer, turns each one into structured fields, and answers questions with numbers. How it differs from dashboards, chatbots and ChatGPT. Author/ Maddox HaleTopic/ Methods Cover of the Duolingo customer analysis
Chart: Marriott issues ranked by volume and by cause 5 min Which Complaints Cause Bad Reviews? Hotel, Gym and Café Data In public reviews of a hotel group, a gym chain and a café chain, the most-mentioned complaint was not what drove the one- and two-star reviews. The numbers, and how to check your own. Author/ Maddox HaleTopic/ Methods Chart: share of gym members who say they will leave, by issue 6 min Why Gym Members Say They Will Cancel: Evidence From 9,186 Reviews In 9,186 public reviews of a gym chain, staff problems had the biggest effect on bad ratings, but billing complaints were the ones most likely to say the member was cancelling or warning others away. Author/ Maddox HaleTopic/ Methods
Recent 4 min How to Measure Why Customers Escalate From a Chatbot An escalation rate says how often a bot hands off to a person, not why. What to record for each conversation, how to count it, and what QuickBooks and Dropbox changed. Author/ Maddox HaleTopic/ AI agents 6 min How to Compare Restaurant Locations Using Guest Reviews Star ratings mix how a store is run with where it is. Using public reviews of 24 Atlanta restaurants, here is how to compare each location with stores like it. Author/ Maddox HaleTopic/ Voice of customer 8 min Customer Feedback Analytics Pricing: 20 Tools Compared Published prices for 20 customer feedback and voice of customer analytics tools, read from each vendor's own page on October 26, 2026: who publishes a price, who needs a demo, and who has a trial. Author/ Maddox HaleTopic/ Voice of customer
  1. 4 min How to Measure Why Customers Escalate From a Chatbot An escalation rate says how often a bot hands off to a person, not why. What to record for each conversation, how to count it, and what QuickBooks and Dropbox changed. Maddox HaleAI agents
  2. 6 min How to Compare Restaurant Locations Using Guest Reviews Star ratings mix how a store is run with where it is. Using public reviews of 24 Atlanta restaurants, here is how to compare each location with stores like it. Maddox HaleVoice of customer
  3. 8 min Customer Feedback Analytics Pricing: 20 Tools Compared Published prices for 20 customer feedback and voice of customer analytics tools, read from each vendor's own page on October 26, 2026: who publishes a price, who needs a demo, and who has a trial. Maddox HaleVoice of customer
  4. 4 min What Is an AI Analytics Agent for Customer Conversations? An AI analytics agent reads every ticket, chat, call, review and survey answer, turns each one into structured fields, and answers questions with numbers. How it differs from dashboards, chatbots and ChatGPT. Maddox HaleMethods
  5. 8 min Which Problems Go With Bad Reviews at Home Depot Stores? Using 2,354 public reviews of 24 Atlanta Home Depot stores, which problems go with one- and two-star ratings, and how to compare stores without ranking noise. Maddox HaleCompany
  6. 8 min Which Problems Go With One-Star Reviews at Car Dealerships? Using 23,375 public reviews of 24 AutoNation dealerships, which sales and service problems go with one-star reviews, and why the store matters more than the brand. Maddox HaleCompany
  7. 9 min What Do Carvana Reviews Say About Buying vs Selling a Car? In 5,380 public Carvana reviews, people selling a car were far happier than people buying one on Trustpilot. For buyers, the worst ratings came after delivery, when a problem was never resolved. Maddox HaleCompany
  8. 8 min What Goes With Bad Visits to American Dream? 4,540 Google Reviews In 4,540 public Google reviews of the American Dream mall and entertainment complex, a review complaining about parking was 6.4 times as likely to be one star. The attractions themselves stayed well reviewed. Maddox HaleCompany
  9. 7 min Correlation vs Causation in Customer Experience Data In three public-review analyses, the issue customers mentioned most was not the one doing the most damage to ratings. Here is why, and what a causal estimate does differently. Maddox HaleVoice of customer
  10. 8 min Key Driver Analysis From Text, Not Just Survey Scores Key driver analysis usually runs on survey scores. Here is how to run it on tickets and reviews, and how correlation, regression, Shapley and causal methods rank the same six drivers. Maddox HaleCompany
  11. 9 min Topic Modeling vs LLM Classification for Customer Feedback Topic models discover themes; fixed-schema LLM labels apply the ones you define to every record. We ran clustering, LDA and a 23-field schema on the same 8,504 hotel reviews. Maddox HaleAI agents
  12. 8 min How to Tell if Your AI Tagging Is Accurate Compare the model's labels with people labelling the same records, and read percent agreement next to Cohen's kappa. A worked example, sample sizes and numbers from our research. Maddox HaleCompany
  13. 7 min Aspect-Based Sentiment Analysis, With Customer Review Examples Aspect-based sentiment analysis scores each thing a review talks about, not the review as a whole. Using public hotel, gym and restaurant reviews, here is how it works and why aspect sentiment is not the same as impact on a rating. Maddox HaleVoice of customer
  14. 5 min Text Analytics vs Sentiment Analysis: What's the Difference? Sentiment analysis is one task inside text analytics: it scores tone, while text analytics extracts topics, problems, names and intent. Here is a side-by-side comparison with examples from reviews and support conversations. Maddox HaleVoice of customer
  15. 5 min Did Our NPS Drop, or Did Different Customers Answer? NPS can fall when no group of customers got less happy, because more answers came from a group that always scores low. Here is a worked example, the Python to split the change, and a checklist for your own survey. Maddox HaleCompany
  16. 7 min How to Build a Codeframe for Open-Ended Survey Responses A codeframe is the list of codes, definitions and rules used to tag open-ended survey answers consistently. Here are the five steps to build one, an example codeframe and agreement test, and how codeframes relate to Dimensions. Maddox HaleCompany
  17. 8 min How to Export Intercom Conversations and Find Top Contact Reasons Intercom's Dataset export CSV leaves out what customers wrote. Here is which export to use, how to tag contact reasons consistently, and how to rank them by cost as well as volume. Maddox HaleAI agents
  18. 8 min How to Analyze Zendesk Tickets With AI, Step by Step Zendesk's CSV export leaves out the ticket text. Here is how to export the comments, label every ticket with a fixed schema, check the labels and join them to outcomes. Maddox HaleCompany
  19. 6 min Containment Rate vs Resolution Rate vs Deflection Rate Containment counts conversations that never reached a person; resolution counts problems solved; deflection counts contacts that never happened. Here are the formulas and why they disagree. Maddox HaleCompany
  20. 7 min How to Check Whether Your AI Agent Really Resolved Conversations Many AI agents count a conversation as resolved when the customer stops replying. Here is how to sample, score and report what really happened. Maddox HaleAI agents
  21. 7 min How to Analyze Google Reviews Across 50 or More Locations A step-by-step method for reviews across many locations, with worked numbers from 102 hotels, gyms and restaurants: tagging, comparing like with like, recent ratings and review surges. Maddox HaleCompany
  22. 6 min Why Gym Members Say They Will Cancel: Evidence From 9,186 Reviews In 9,186 public reviews of a gym chain, staff problems had the biggest effect on bad ratings, but billing complaints were the ones most likely to say the member was cancelling or warning others away. Maddox HaleMethods
  23. 5 min Which Complaints Cause Bad Reviews? Hotel, Gym and Café Data In public reviews of a hotel group, a gym chain and a café chain, the most-mentioned complaint was not what drove the one- and two-star reviews. The numbers, and how to check your own. Maddox HaleMethods
  24. 12 min Causal Inference: How to Move From Correlation to Cause Causal inference is having a moment in the data industry, and it is not because the math is new. Rubin's potential outcomes framework dates to the 1970s. Judea Pearl's do-calculus is 30 years old. Difference-in-differences goes back to a ch Eric GriffingMethods
  25. 11 min How to Build a Churn Risk Report: The Methodology, the Joins, and the Dimensions Your CRM can tell you exactly which accounts churned last quarter, but it cannot tell you which ones are about to. Eric GriffingMethods
  26. 6 min Voice of the Customer Best Practices: A Quick Guide Voice of the customer programs fail quietly. The surveys go out, the tickets get tagged, the sentiment dashboard stays green, and then churn spikes and nobody can explain why. Not because the feedback wasn't there, but because the program w Maddox HaleVoice of customer
  27. 5 min Voice of Customer Tools Are Good at Listening. They're Bad at Explaining Why. Your VP of Customer Success walks into the QBR with the NPS trend on slide one. Score dropped 7 points in Q3. The deck shows verbatim comments, a word cloud, a sentiment breakdown by region. Everyone in the room nods. Nobody can explain wha Maddox HaleVoice of customer
  28. 8 min Survey Text Analysis: A Practical Guide for Analytics Leaders You just closed a quarterly NPS survey. 12,000 responses. 4,200 of them include written comments, the actual sentences customers wrote in the open-text box. Your dashboard tells you the score dropped from 47 to 39. Eric GriffingVoice of customer
  29. 10 min The Analytics Stack in 2026: Layers, Tools, Trends, and What's Still Missing A VP of Analytics at a SaaS company just received the monthly operational report. Net revenue retention dropped from 112% to 104% in Q3, an eight-point swing that rewrites the board deck. Eric GriffingData stack
  30. 9 min Predictive Churn: A Complete Guide to Models, Data, and the Missing "Why" Layer A Head of Customer Success at a mid-market SaaS company opens her Monday churn report. Forty-seven accounts sit above the 70% risk threshold, representing $4.2M in ARR. She has eight CSMs covering nearly 600 accounts. She forwards the list Eric GriffingMethods
  31. 9 min Unstructured Data Tools: A Practical Guide to Turning Messy Inputs Into Real Answers The modern data stack was built around a comfortable assumption: that the data worth analyzing fits in rows and columns. Ingest it from a source system, model it in the warehouse, expose it through a BI tool, and the dashboards take care of Eric GriffingData stack
  32. 8 min Why Dashboards Don't Answer Why It's 9:14 on a Tuesday morning. You open your revenue dashboard, coffee in hand, and something ugly is staring back at you. Churn spiked 12% last quarter. The number is right there, big, red, undeniable. Your CFO will want to talk about it Eric GriffingMethods
  33. 8 min The Meaning Layer for Unstructured Data: Why the Next Decade Belongs Upstream Over the last decade, the modern data stack has centered itself around the warehouse. The warehouse became the gravitational center for analytics, BI, and increasingly ML. But something interesting is happening, and the recent dbt + Fivetra Andrew HongData stack
  34. 6 min From Chaos to Context: How Knowledge Graphs and Agentic Workflows Are Reimagining Unstructured Data For years, the analytics world has revolved around structure. Rows, columns, schemas, and dashboards have been our tools for understanding reality. Yet beneath this structured world lies a vast ocean of unstructured data, customer conversat Andrew HongData stack
  35. 10 min Beyond Sentiment and Categories: A New Era for Customer Insights For decades, when companies thought about “text analytics,” two words came to mind: sentiment and categories. Was the customer happy or upset? Which bucket does their feedback fall into, “billing issue,” “product complaint,” “shipping delay Andrew HongMethods
  36. 10 min Why Building Your Own Unstructured Data ETL Pipeline Is Harder Than You Think For the last decade, enterprises have built powerful data stacks for structured information. With modern tools like Fivetran, Snowflake, dbt, and Tableau, data teams can ingest, store, transform, and analyze structured data at scale. But wh Andrew HongData stack
  37. 10 min A Guide to Unstructured Data Management In today’s data-driven world, organizations are inundated with vast amounts of information, much of which is unstructured. Unlike traditional structured data neatly organized in databases, unstructured data includes emails, call transcripts Eric GriffingData stack
  38. 6 min The Rise of the Language Data Engineer Over the last decade, the modern data stack has gone from niche idea to mainstream. Tools like Snowflake, dbt, and Looker redefined how companies ingest, transform, and activate data. Entire roles were born out of this movement, most famous Andrew HongData stack
  39. 12 min The Missing Layer in the Modern Data Stack: Unstructured Data By 2025, more than 80% of enterprise data will be unstructured. Yet if you look at the modern data stack it’s almost entirely designed for structured data. Andrew HongData stack
  40. 17 min What Is Customer Observability? A New Way to Understand Every Customer Interaction In the early 2010s, Uber entered New York City and transformed the transportation landscape. For decades, the city had limited taxi supply through a tightly controlled medallion system, capping the number of yellow cabs to under 14,000. Thi Jason PotteigerData stack
  41. 2 min Ada + Dimension Labs: Advanced Chatbot Analytics We’re excited to announce a new partnership between Ada and Dimension Labs to bring omnichannel analytics and insights to chatbot programs.  Eric GriffingAI agents
  42. 5 min How LLM Analytics Improve Accuracy & Performance As large language models (LLMs) become embedded in apps across customer service, product support, and digital experiences, one question still remains unanswered: how do you know your AI is performing well? Maddox HaleAI agents
  43. 5 min Data Taxonomy: Unveiling the Power of Unstructured Text Analytics Data taxonomy refers to a structured classification system that organizes data into defined categories, roles, and relationships. Implementing a robust data taxonomy can be the difference between chaotic data silos and a strategic powerhous Rumeer KeshwaniMethods
  44. 5 min Brand Sentiment Analysis: Leveraging Unstructured Text Analytics and LLMs for Strategic Insights In an age where brands can rise and fall at the speed of a trending tweet, understanding consumer sentiment has never been more crucial. A staggering 71% of consumers believe that brands should listen to their feedback to improve products a Rumeer KeshwaniVoice of customer
  45. 4 min How Top Hotels Leverage AI to Enhance Guest Experience and Drive Operational Efficiency The hospitality industry thrives on exceptional guest experiences. But as customer expectations rise, hotels face increasing pressure to deliver seamless service while controlling costs. Eric GriffingVoice of customer
  46. 6 min Semantic Clustering Demystified Semantic clustering groups text by meaning instead of exact words. Here it runs on 8,504 hotel reviews, including the part where it points at the wrong problem. Maddox HaleMethods
  47. 5 min What is Intercom: Empowering Customer Engagement Through Chat Systems In a world where the customer is king, organizations wrestle with how to provide a seamless experience that keeps customers engaged while fostering loyalty. With a staggering 79% of consumers preferring real-time interaction over waiting fo Rumeer KeshwaniAI agents
  48. 4 min Customer Interaction Analysis: Enhancing CX through Data-Driven Insights Customer Interaction Analysis (CIA) refers to the systematic evaluation of various customer touchpoints and interactions within an organization. By applying advanced analytical techniques, businesses can transform raw data from these intera Rumeer KeshwaniVoice of customer
  49. 8 min Top 10 Text Analytics Tools to Unlock Insights from Unstructured Data In the age of information overload, organizations are inundated with vast amounts of unstructured data, from customer feedback and social media comments to support tickets and chat logs. The challenge lies not in gathering this data, but in Maddox HaleData stack
  50. 5 min Fan Insights: Unlocking Open-Ended Feedback in the Sports Industry In the age of digital transformation, the sports industry stands at a crossroads, with fan engagement evolving at a breakneck pace. Did you know that a staggering 71% of sports organizations see fan engagement as important to achieving thei Rumeer KeshwaniVoice of customer
  51. 4 min The Secret to AI Workflows & Customer Feedback In the new era of digital-first economies, customer feedback is no longer a simple input; it’s the lifeblood of strategic decision-making. Consider this, up to 85% of customers walk away due to poor experiences. That’s not just a statistic; Rumeer KeshwaniVoice of customer
  52. 5 min Data Enrichment: Enhance Decisions with Next Gen Insights In today's data-centric world, enterprises are inundated with vast amounts of data. A staggering 90% of the world's data was generated in just the last two years, compelling organizations to seek innovative methods to extract meaningful ins Rumeer KeshwaniData stack
  53. 4 min Welcome to Dimension Labs: Redefining Analysis of Unstructured Data We are thrilled to announce the launch of Dimension Labs, an AI-powered BI platform that transforms how enterprises understand their unstructured customer interactions. In today’s digital-first world, raw conversations carry vital insights, Andrew HongCompany
  54. 10 min Chatbot Analytics: 13 Metrics That Every Business Should Track How often have you built a chatbot and spent days thinking through every possible workflow only to deploy it and see that users never use them? Our guess: too often. The bigger issue is that your chatbot analytics tool may have marked this Maddox HaleAI agents
  55. 7 min What is Textual Data and Why Does It Matter to Customer Support Teams? Manually analyzing hundreds of unstructured text-based data sources is tedious and time-consuming. What's worse is that since it's in text format, you know this process can be made easier, but you're unsure how to do it. Eric GriffingData stack
  56. 6 min What Are Enterprise Chatbots And How Do They Work? Gartner defines chatbots as “A domain-specific conversational interface that uses an app, messaging platform, social network or chat solution for its conversations.” Maddox HaleAI agents
  57. 6 min Chatbots vs Conversational AI: A Complete Guide Chatbots have become commonplace in the business world. You can find them on almost every website these days, which can be backed by the fact that 80% of customers have interacted with a chatbot previously. Maddox HaleAI agents
  58. 4 min Conversation Analytics: What It Is and Why It Matters Conversation analytics refers to the use of artificial intelligence (AI), specifically natural language processing (NLP), to analyze customer conversations and use them to understand their sentiment, intent, and interests. Maddox HaleAI agents
  59. 8 min The Ultimate Guide To Unstructured Data Analytics According to the OECD, “Unstructured data are by far the most frequent type of data and thus provide the greatest potential for data analytics today.” Maddox HaleData stack
  60. 8 min What does a Conversation Designer do? Since the world has gone digital, the demand for chatbots and voice assistants has been rising fast. Due to this, new roles like conversation designers are emerging that allow companies to create better conversational experiences for their Eric GriffingAI agents
  61. 6 min How to Build a Customer Experience Dashboard in 4 Steps Due to the lack of data, most customer service professionals struggle to triage requests and track customer sentiment over time. But that's not the case anymore. Customer experience dashboards resolve this issue, giving them more direction Maddox HaleVoice of customer
  62. 5 min What is a Conversational Agent? A conversational agent is any dialogue system that conducts natural language processing (NLP) and responds automatically using human language. Conversational agents represent the practical implementation of computational linguistics and are Eric GriffingAI agents
  63. 9 min Unlock the Power of Automated Data Labeling: Revolutionizing Your Data Processing In today's data-driven world, organizations are generating and needing to process huge amounts of data to derive valuable insights. Processing this data correctly is often time-consuming and resource intensive. One key step in the data proc Eric GriffingMethods
Dimension Labs/Start with one file From $299 a month

Stop reporting. Start understanding.

Start with one file. Ask why a number moved. Plans from $299 a month, no demo and no contract on monthly plans.

Start now › See pricing ›