{"id":22518,"date":"2026-07-16T13:30:18","date_gmt":"2026-07-16T11:30:18","guid":{"rendered":"https:\/\/www.neuraldesigner.com\/use-cases\/customer-segmentation\/"},"modified":"2026-07-16T13:47:10","modified_gmt":"2026-07-16T11:47:10","slug":"customer-segmentation","status":"publish","type":"page","link":"https:\/\/www.neuraldesigner.com\/use-cases\/customer-segmentation\/","title":{"rendered":"Customer segmentation using machine learning"},"content":{"rendered":"<section>Targeting in marketing is a strategy that divides a large market into smaller segments to concentrate on a particular group of customers within that audience.Companies can analyze age, gender, interests, and other features of clients to target specific customers.This allows us to design marketing campaigns with a higher conversion rate.<\/section>\n<section>Here, we explain how to\u00a0<span style=\"box-sizing: border-box; margin: 0px; padding: 0px;\">utilize machine learning and\u00a0<a href=\"https:\/\/www.neuraldesigner.com\/\" target=\"_blank\" rel=\"noopener\">Neural Designer<\/a> to develop conversion models and refine<\/span>\u00a0marketing campaigns.<\/p>\n<h3>Contents<\/h3>\n<ol>\n<li><a href=\"#Objectives\">Objectives<\/a>.<\/li>\n<li><a href=\"#Benefits\">Benefits<\/a>.<\/li>\n<li><a href=\"#Approach\">Approach<\/a>.<\/li>\n<li><a href=\"#Results\">Results<\/a>.<\/li>\n<li><a href=\"#Conclusions\">Conclusions<\/a>.<\/li>\n<\/ol>\n<\/section>\n<p><!-- Objectives --><\/p>\n<section id=\"Objectives\">\n<h2>Objectives<\/h2>\n<p>Customer targeting involves identifying individuals who are more likely to purchase a specific product or service.<\/p>\n<p>The selection of customers is not always as straightforward as categorizing them by a single variable, such as age or gender. Indeed, complex combinations of different variables determine which customers are prone.<\/p>\n<p><img decoding=\"async\" style=\"width: 485px; max-width: 100%;\" src=\"https:\/\/www.neuraldesigner.com\/images\/activity-diagram-customer-targeting.svg\" height=\"254\" \/><\/p>\n<p>Customer targeting requires analyzing numerous features in specific ways relevant to marketing:<\/p>\n<ul>\n<li><b>Socio-demographic factors<\/b>: Gender, age, education&#8230;<\/li>\n<li><b>Engagement factors<\/b>: Recency, frequency, monetary&#8230;<\/li>\n<li><b>Stationary elements<\/b>: Season, date, time&#8230;<\/li>\n<li><b>Conversion of the customer.<\/b><\/li>\n<li>Etc.<\/li>\n<\/ul>\n<\/section>\n<p><!-- Benefits --><\/p>\n<section id=\"Benefits\">\n<h2>Benefits<\/h2>\n<p>These techniques effectively select potential clients more efficiently than traditional methods.<\/p>\n<h3>Benefits for the customer:<\/h3>\n<p><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/touch.svg\" width=\"70\" height=\"70\" \/><\/p>\n<h3>BETTER RECOMMENDATIONS<\/h3>\n<p>Identify common characteristics among clients to segment them effectively.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/search.svg\" width=\"70\" height=\"70\" \/><\/p>\n<h3>LESS DISTURBANCE<\/h3>\n<p>Discover the reasons a product fits better in one segment than others.<\/p>\n<h3>Benefits for the company:<\/h3>\n<p><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/location.svg\" width=\"70\" height=\"70\" \/><\/p>\n<h3>REDUCED COSTS<\/h3>\n<p>Predict which product will be bought by each client to make more efficient campaigns.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/trending_up.svg\" width=\"70\" height=\"70\" \/><\/p>\n<h3>INCREASED CONVERSION<\/h3>\n<p>Increase the conversion rate of your marketing campaigns.<\/p>\n<\/section>\n<p><!-- Approach --><\/p>\n<section id=\"Approach\">\n<h2>Approach<\/h2>\n<p>The most effective way to target customers is to create a model based on their specific characteristics.<\/p>\n<p>Neural networks can model the correct one given these variables and detect which customers are interested in your products and services.<\/p>\n<p>The following graph illustrates a neural network for customer targeting.<\/p>\n<p><img decoding=\"async\" style=\"width: 600px; max-width: 100%;\" src=\"https:\/\/www.neuraldesigner.com\/images\/customer_targeting_nn.webp\" \/><\/p>\n<p><!--\n\nThe following flow chart shows how to build and use a customer targeting model.\n\n<img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_1.svg\" \/>\nThe first step is to create a\n<a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\">data set<\/a>\nby collecting all the internal and external information related to the conversion of the product or service.\n\n<img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_2.svg\" \/>\n\nThen, we need to build the\n<a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-network\">neural network<\/a>\nthat will predict which customers will convert.\n\n<img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_3.svg\" \/>\n\nA <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/training-strategy\">training strategy<\/a>\nis applied to the neural network to discover the underlying relationships in the conversion data.\n\n<img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_4.svg\" \/>\n\nTo improve the predictive capabilities of the model,\nwe can also apply <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-selection\">model selection<\/a> by trying combinations of variables and choosing those with more impact in the sale of the product or service.\n\n<img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_5.svg\" \/>\n\nThen, the resulting model undergoes an exhaustive\n<a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/testing-analysis\">testing analysis<\/a>.\n\n<img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_6.svg\" \/>\n\nFinally, after <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-deployment\">model deployment<\/a>,\nthe neural network is used to predict which customers will purchase the product or service.\n\nThe data science and machine learning platform <a href=\"https:\/\/www.neuraldesigner.com\/downloads\/\">Neural Designer<\/a>\nguides you through this process so that you focus on your business and not on the details behind machine learning.\n\n--><\/p>\n<\/section>\n<p><!-- Results --><\/p>\n<section id=\"Results\">\n<h2>Results<\/h2>\n<p>As we have explained before, customer targeting aims to increase conversion rates.<\/p>\n<p>The following example is about a company that wants to sell its products. We can observe the favorable rates in the following plot, both with and without the model.<\/p>\n<p><img decoding=\"async\" style=\"width: 484px; max-width: 100%;\" src=\"https:\/\/www.neuraldesigner.com\/images\/customer_targeting_rates.webp\" height=\"249\" \/><\/p>\n<p>We can see that only 20% of customers are interested in the products without the model. However, after applying the model, we have selected the more likely customers, and we can see that 40% are genuinely interested.<\/p>\n<p>In case the company has doubled its sales with the model.<\/p>\n<\/section>\n<p><!-- Conclusions --><\/p>\n<section id=\"Conclusions\">\n<h2>Conclusions<\/h2>\n<p>In conclusion, customer targeting enables companies to find the most relevant leads. Consequently, it enables them to invest their marketing resources more efficiently.<\/p>\n<p>It is an economical and fast way to manage existing clients and acquire new ones.<\/p>\n<\/section>\n<section>\n<h2>Related posts<\/h2>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Targeting in marketing is a strategy that divides a large market into smaller segments to concentrate on a particular group of customers within that audience.Companies can analyze age, gender, interests, and other features of clients to target specific customers.This allows us to design marketing campaigns with a higher conversion rate. Here, we explain how to\u00a0utilize [&hellip;]<\/p>\n","protected":false},"author":152,"featured_media":2330,"parent":22498,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-22518","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Customer segmentation using machine learning - Neural Designer<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.neuraldesigner.com\/use-cases\/customer-segmentation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Customer segmentation using machine learning - Neural Designer\" \/>\n<meta property=\"og:description\" content=\"Targeting in marketing is a strategy that divides a large market into smaller segments to concentrate on a particular group of customers within that audience.Companies can analyze age, gender, interests, and other features of clients to target specific customers.This allows us to design marketing campaigns with a higher conversion rate. 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