{"id":320,"date":"2019-06-19T19:33:04","date_gmt":"2019-06-19T19:33:04","guid":{"rendered":"https:\/\/blog.geneea.com\/?p=320"},"modified":"2026-01-29T19:46:04","modified_gmt":"2026-01-29T19:46:04","slug":"nlp-for-voc-en","status":"publish","type":"post","link":"https:\/\/geneea.com\/news\/nlp-for-voc-en","title":{"rendered":"Interested in business advice? Your customers will give you the best one"},"content":{"rendered":"\n<h4 class=\"wp-block-heading\" id=\"understanding-customer-feedback-via-artificial-intelligence-and-natural-language-processing\">Understanding customer feedback via Artificial Intelligence and Natural Language Processing<\/h4>\n\n\n\n<p>To stay successful and grow, businesses need to make wise decisions based on qualified and effective analyses of the right data. An <strong>increasing amount of data<\/strong> comes from the customers via <strong>social media<\/strong> and <strong>recommendation sites<\/strong> in the form of post-visit reviews, posts, and mentions. Such data contain significant business value as they often point out <strong>specific issues<\/strong> encountered by customers.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img decoding=\"async\" src=\"https:\/\/geneea.com\/news\/wp-content\/uploads\/2022\/02\/reviews2.png\" alt=\"\"\/><\/figure>\n<\/div>\n\n\n<p>Unlike neatly ordered numbers in a database table, user reviews are unstructured. They are hard to process by computers and hard to quantify. However, thanks to <strong>The Interpretor<\/strong>, our <strong>Natural Language Processing <\/strong>(NLP) platform, we are able to access their hidden value and extract the most important information from the vast amount of user-generated content. <\/p>\n\n\n\n<p>Let us introduce you into some of the NLP superpowers that could boost your business, whether you are a bank, restaurant chain, e-shop, or an airline.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"making-sense-of-reviews\"><strong>Making sense of reviews<\/strong><\/h2>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><a href=\"https:\/\/blog.geneea.com\/wp-content\/uploads\/2022\/02\/categories_example.png\"><img decoding=\"async\" src=\"https:\/\/geneea.com\/news\/wp-content\/uploads\/2022\/02\/categories_example.png\" alt=\"Sentiment analysis of various aspects in four retail chains \"\/><\/a><figcaption class=\"wp-element-caption\">Sentiment analysis of various aspects in four retail chains <\/figcaption><\/figure>\n<\/div>\n\n\n<p>The Interpretor organizes customer feedback into meaningful clusters, capturing the <strong>content<\/strong> of reviews and taking into account your needs. For this, we use various approaches and techniques:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Keywords and relations:<\/strong> Text analysis returns the most relevant meaningful words, phrases, and relations \u2013 e.g., <em>unfriendly manager, knowledgeable staff, overcooked macaroni and cheese, racial discrimination.<\/em> <\/li>\n\n\n\n<li><strong>Domain-specific terms:<\/strong> For review analysis, we use customized models that take into account the language specifics of your business and identify relevant items \u2013 e.g., <em>food items <\/em>for restaurants, <em>room types<\/em> for hotels, or<em> account types <\/em>for banks.<\/li>\n\n\n\n<li><strong>General categories:<\/strong> Out of the box, the Interpretor distinguishes when people talk about general categories, such as staff, service, price, or waiting time.<\/li>\n\n\n\n<li><strong>Sentiment analysis:<\/strong> Are your customers satisfied with your service or products? What do they mention in a negative and positive way? Star ratings can give us a general idea about the customers\u2019 satisfaction, however, unlike NLP, it is not able to recognize a <strong>specific subject<\/strong> with which people are satisfied or dissatisfied without bothering them with long questionnaires.<\/li>\n<\/ul>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><a href=\"https:\/\/blog.geneea.com\/wp-content\/uploads\/2022\/02\/voc-banks-attributes_sentiment_c.png\"><img decoding=\"async\" src=\"https:\/\/geneea.com\/news\/wp-content\/uploads\/2022\/02\/voc-banks-attributes_sentiment_c.png\" alt=\"Attributes and sentiment used when talking about staff in reviews of banks in London\"\/><\/a><figcaption class=\"wp-element-caption\">Attributes and sentiment used when talking about staff in reviews of banks in London<\/figcaption><\/figure>\n<\/div>\n\n\n<h2 class=\"wp-block-heading\" id=\"alert-detection\">Alert&nbsp;detection<\/h2>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><a href=\"https:\/\/blog.geneea.com\/wp-content\/uploads\/2022\/02\/alerts_example.png\"><img decoding=\"async\" src=\"https:\/\/geneea.com\/news\/wp-content\/uploads\/2022\/02\/alerts_example.png\" alt=\"Graph of various automatically generated alerts in time\"\/><\/a><figcaption class=\"wp-element-caption\">Alert types in time<\/figcaption><\/figure>\n<\/div>\n\n\n<p>A successful business gets a lot of feedback. And even when using the techniques described above, one cannot review the analytics every second. But sometimes, a <strong>quick reaction<\/strong> is necessary: a customer is complaining of food poisoning, a blind person was kicked out of the restaurant for bringing in a dog, an employee was extremely rude, etc. This is where alerts come into play.<\/p>\n\n\n\n<p>To generate alerts, we use various techniques such as anomaly detection or good old manually specified rules to identify important information that potentially needs to be acted upon quickly.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"curious-what-text-analysis-says-about-your-data\"><strong>Curious what text analysis says about your data?<\/strong><\/h2>\n\n\n\n<p>For starters, try our <a href=\"https:\/\/demo.geneea.com\/?sample=12\">demo<\/a> or <a href=\"https:\/\/help.geneea.com\/api_general\/\">API<\/a>. You can also find our <a href=\"https:\/\/geneea.com\/case-studies\/keboola\/\">app in Keboola<\/a>.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Understanding customer feedback via Artificial Intelligence and Natural Language Processing To stay successful and grow, businesses need to make wise decisions based on qualified and effective analyses of the right data. An increasing amount of data comes from the customers via social media and recommendation sites in the form of post-visit reviews, posts, and mentions&#8230;.<\/p>\n","protected":false},"author":3,"featured_media":750,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[348,358],"tags":[527,525],"class_list":["post-320","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-resources","category-voice-of-the-customer","tag-integration","tag-nlp-cs-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Interested in business advice? 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