Guides
Review and sentiment analysis
Methods for classifying reviews, measuring sentiment by theme and reading what changes over time.
- GuideHow to analyse Google reviews across hundreds of locationsA practical method for turning Google Maps reviews from every store into themes, trends and actions: what to collect, how to classify it, and how to decide what to fix first.Read more
- GuideHow to build a review taxonomy: themes, sub-themes and issuesA review taxonomy turns free-text feedback into categories you can count and compare. Here's how to design one in three levels, keep it stable and make it useful to every team.Read more
- GuideA customer feedback analysis report template, with a sampleA customer feedback analysis report sample and template: the one-page summary, issues with evidence, store view, actions and follow-ups, ready to adapt monthly.Read more
- GuideA customer feedback analysis template in Excel: how to build oneBuild a customer feedback analysis Excel template: the sheets, columns, drop-down topics, pivot tables and formulas for negative share and trend.Read more
- GuideOpen-ended survey analysis alongside reviewsOpen-ended survey analysis alongside public reviews: one taxonomy, detractors compared with promoters, and where surveys and reviews agree or differ.Read more
- GuideApp store review sentiment analysis by feature and versionApp store review sentiment analysis by feature and release: payments, login, performance and more, compared version to version, with languages and replies.Read more
- GuideAspect-based sentiment analysis: sentiment per theme, not per reviewAspect based sentiment analysis explained for customer reviews: what aspects are, how it differs from review-level sentiment, how to do it and how to use it.Read more
- GuideBrand sentiment analysis from customer reviewsBrand sentiment analysis from customer reviews: what reviews say about the brand beyond single visits, how to measure it, and how it differs from social media.Read more
- GuideManual vs AI feedback tagging: coding reviews by hand or with AIManual vs AI feedback tagging compared: accuracy, consistency, speed, cost, languages and control, and how to combine them so each does what it is good at.Read more
- GuideCustomer feedback analysis examples from retail, restaurants, hotels and appsCustomer feedback analysis examples from retail, jewellery, restaurants, hotels and apps: the question, the analysis, what it found and what changed.Read more
- GuideCustomer feedback classification, explainedCustomer feedback classification explained: what it is, manual vs rules vs machine learning vs language models, mention-level labels, evaluation and pitfalls.Read more
- GuideGoogle review summary examples, and how to write your ownGoogle review summary examples for a store, a restaurant and an app, showing what a useful internal summary includes: counts, trends, quotes and owners.Read more
- GuideHow a feedback taxonomy decays, and how to keep yours currentWhy a feedback taxonomy decays as products, policies and customers change, the warning signs, and a quarterly routine to keep it current, trends intact.Read more
- GuideHow to analyse customer complaints and find what to fixHow to analyze customer complaints so they stop recurring: collect them in one place, classify by specific issue, find where they cluster and trace the cause.Read more
- GuideHow to analyse customer feedback from every channelHow to analyze customer feedback from reviews, surveys, complaints and support: one taxonomy, the right measure for each channel, and findings people act on.Read more
- GuideHow to analyse customer reviews: a step-by-step methodHow to analyze customer reviews in seven steps: gather them, clean them, split mentions, classify, measure sentiment by topic, find what is rising and act.Read more
- GuideHow to analyze reviews in Excel, and when to stopHow to analyze reviews in Excel step by step: layout, topic drop-downs, mention rows, pivots for negative share and trend, and the signs you have outgrown it.Read more
- GuideHow to categorise customer feedback: building categories that workHow to categorize customer feedback into categories people can act on: three levels, clear definitions, mention-level tagging, examples and rules for change.Read more
- GuideHow to find emerging issues in reviews earlyHow to find emerging issues in reviews before they hit the rating: watch for new topics, rising shares on small volumes, clusters by store and update language.Read more
- GuideHow to organize customer feedback so you can use itHow to organize customer feedback from reviews, surveys, complaints and staff: one place, one set of categories, consistent fields and a routine to keep it up.Read more
- GuideHow to present review insights to stakeholders, with feedback report examplesHow to present review insights to leadership, owners and store teams, with feedback report examples: lead with the decision, show evidence, keep it short.Read more
- GuideHow to read Google reviews for a company, criticallyHow to read Google reviews for a company critically: look past the average, read recent and mid-range reviews, check patterns, replies and sample size.Read more
- GuideHow to spot fake Google reviews in your review dataHow to spot a fake Google review in your data: bursts, vague text, reviewer histories, identical wording and off-topic content, and what to do about each.Read more
- GuideHow to use AI to analyse customer reviews you can trustCustomer review analysis with AI: what language models do well, where they go wrong, how to set them up with your categories and how to check the results.Read more
- GuideNegative sentiment share: a better metric than average sentimentWhy negative sentiment share beats an average sentiment score for customer reviews: how to calculate it, how to read it with volume and trend, and its pitfalls.Read more
- GuideOne review, several issues: counting multi-topic reviewsHow to count multi topic reviews correctly: mentions vs reviews, why it matters, how to report each, handling mixed sentiment and avoiding double counting.Read more
- GuideProduct review sentiment analysis: quality, fit, value and moreProduct review sentiment analysis by attribute: quality, fit, durability, design, value and packaging, with product detail and links to returns and launches.Read more
- GuideHow to analyze reviews with ChatGPT: what goes wrongWhat goes wrong when you analyze reviews with ChatGPT or another LLM: invented counts, shifting categories, truncation, no evidence, and how to prompt better.Read more
- GuideCustomer feedback analysis for product improvementCustomer feedback analysis for product improvement: find product issues in reviews, separate them from service, size them and feed them to product teams.Read more
- GuideAnalysing reviews in other languages: Indian languages and HinglishHow to analyse reviews in other languages, especially Indian languages and Hinglish: scripts, code-mixing, translation pitfalls and accuracy by language.Read more
- GuideSentiment analysis accuracy: what to expect and how to checkSentiment analysis accuracy explained: why it varies, the hard cases, how to measure it on your own reviews and what level is good enough for decisions.Read more
- GuideSentiment analysis in Hindi and other Indian languagesSentiment analysis in Hindi and other Indian languages: scripts, Hinglish, negation and idioms, approaches that work and how to check accuracy by language.Read more
- GuideSentiment analysis for reviews across many locationsSentiment analysis for reviews across many locations: one taxonomy, topic sentiment by store, fair comparisons, regional roll-ups and evidence for local teams.Read more
- GuideSentiment analysis of customer reviews, explained for business teamsSentiment analysis of customer reviews in plain language: what it measures, review-level vs topic-level, how accurate it is and how teams should use it.Read more
- GuideSentiment analysis of Google reviews: a practical guideSentiment analysis of Google reviews for stores: collecting reviews, handling ratings and mixed text, measuring sentiment by topic and store, reading results.Read more
- GuideSentiment analysis of hotel reviews by stage of the staySentiment analysis of hotel reviews by stage of the stay: arrival, room, cleanliness, staff, food, facilities and checkout, compared across properties.Read more
- GuideSentiment analysis of restaurant reviews: food, service and deliverySentiment analysis of restaurant reviews by topic: food, service, waiting, hygiene, value and delivery, with examples, dish-level detail and outlet comparisons.Read more
- GuideSentiment analysis tools compared for business usersSentiment analysis tools compared by type for business users: generic APIs, chat tools, survey and reputation platforms and review analytics, and what to check.Read more
- GuideSentiment vs star rating: which should you trust?Sentiment vs star rating compared: what each measures, when they disagree, which to use for which decision, and how to report both together.Read more
- GuideSentiment analysis with ChatGPT vs dedicated toolsSentiment analysis with ChatGPT compared with dedicated tools: where a chat model is enough, where it breaks, and how to get consistent results either way.Read more
- GuideSentiment trend analysis: reading month-on-month changeSentiment trend analysis done right: comparing months fairly, separating real change from noise and seasonality, and explaining what moved and why.Read more
- GuideSmall sample size reviews: when to trust a location's numbersSmall sample size reviews explained: why percentages swing on few reviews, how to set minimums, show uncertainty and still learn from quiet locations.Read more
- GuideStar rating vs review sentiment: why the average lagsRating vs sentiment: why a store's average star rating moves slowly and hides causes, and how review text shows problems earlier and more precisely.Read more
- GuideFeedback taxonomy levels: themes, sub-themes and issuesFeedback taxonomy levels explained: why three levels work, what belongs at each, how to name and define them, and how each level is used for decisions.Read more
- GuideWhat a Google review summary tells you, and what it hidesWhat is a Google review summary, where does it come from, and what does it hide? How brands should read Google's summaries and snippets and what to do instead.Read more
- GuideWhat is feedback analysis? A plain-language guideWhat is feedback analysis? A plain-language definition, what it produces, how it works step by step, who uses it and how to tell good analysis from a dashboard.Read more
- GuideWhy an overall sentiment score misleadsWhy a single overall sentiment score misleads: polarisation, mixed reviews, volume effects and hidden topic changes, and what to report instead.Read more
Other topics
Free review snapshot
See what your customers are saying, before you talk to us.
Tell us your brand. We read its public Google reviews and send back the themes customers raise most, with the quotes behind them.
No commitment. We use your details only to send your snapshot and follow up. Privacy policy