{"id":3572,"date":"2025-11-26T11:13:19","date_gmt":"2025-11-26T10:13:19","guid":{"rendered":"https:\/\/neuraldesigner.com\/solution\/customer-segmentation\/"},"modified":"2026-02-09T11:43:17","modified_gmt":"2026-02-09T10:43:17","slug":"customer-segmentation","status":"publish","type":"solution","link":"https:\/\/www.neuraldesigner.com\/solutions\/customer-segmentation\/","title":{"rendered":"Customer segmentation using machine learning"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"3572\" class=\"elementor elementor-3572\" data-elementor-post-type=\"solution\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1bd65232 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1bd65232\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-79536483\" data-id=\"79536483\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1f7fab8f elementor-widget elementor-widget-text-editor\" data-id=\"1f7fab8f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p><\/p>\n<section>\n<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.<\/p>\n<p>Companies can analyze age, gender, interests, and other features from clients to target specific customers.<\/p>\n<p>This allows us to design marketing campaigns with a higher conversion rate.<\/p>\n<\/section>\n<section>\n<p class=\"medium_left\">Here, we explain how to use machine learning and <a href=\"https:\/\/www.neuraldesigner.com\/\">Neural Designer<\/a> to build conversion models and optimize marketing 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 people more prone to buy a specific product or service.<\/p>\n<p>The selection of customers is not always as evident as dividing them by a single variable such as age or gender. Indeed, complex combinations of different variables determine prone customers.<\/p>\n<p><img decoding=\"async\" class=\"\" 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 successfully select potential clients much better than traditional methods.<\/p>\n<h3>Benefits for the customer:<\/h3>\n<p><img decoding=\"async\" class=\"small_left\" src=\"https:\/\/www.neuraldesigner.com\/images\/touch.svg\" width=\"70\" height=\"70\"><\/p>\n<h3>BETTER RECOMMENDATIONS<\/h3>\n<p>Discover common characteristics between clients to divide them into segments.<\/p>\n<p><img decoding=\"async\" class=\"small_left\" 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\" class=\"small_left\" 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\" class=\"small_left\" 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 way to target customers is to create a model based on features from customers.<\/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><!--<\/p>\n<p>\n            The following flow chart shows how to build and use a customer targeting model.\n        <\/p>\n<p>\n        <img decoding=\"async\" class=\"tiny_left\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_1.svg\" \/><br \/>            The first step is to create a<br \/>            <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\">data set<\/a><br \/>            by collecting all the internal and external information related to the conversion of the product or service.\n        <\/p>\n<p>        <img decoding=\"async\" class=\"tiny_left\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_2.svg\" \/><\/p>\n<p>\n            Then, we need to build the<br \/>            <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-network\">neural network<\/a><br \/>            that will predict which customers will convert.\n        <\/p>\n<p>        <img decoding=\"async\" class=\"tiny_left\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_3.svg\" \/><\/p>\n<p>\n            A <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/training-strategy\">training strategy<\/a><br \/>            is applied to the neural network to discover the underlying relationships in the conversion data.\n        <\/p>\n<p>        <img decoding=\"async\" class=\"tiny_left\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_4.svg\" \/><\/p>\n<p>\n            To improve the predictive capabilities of the model,<br \/>            we 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        <\/p>\n<p>        <img decoding=\"async\" class=\"tiny_left\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_5.svg\" \/><\/p>\n<p>\n            Then, the resulting model undergoes an exhaustive<br \/>        <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/testing-analysis\">testing analysis<\/a>.\n        <\/p>\n<p>        <img decoding=\"async\" class=\"tiny_left\" src=\"https:\/\/www.neuraldesigner.com\/images\/number_6.svg\" \/><\/p>\n<p>\n            Finally, after <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-deployment\">model deployment<\/a>,<br \/>            the neural network is used to predict which customers will purchase the product or service.\n        <\/p>\n<p>\n            The data science and machine learning platform <a href=\"https:\/\/www.neuraldesigner.com\/free-trial\">Neural Designer<\/a><br \/>            guides you through this process so that you focus on your business and not on the details behind machine learning.\n        <\/p>\n<p>--><\/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 positive rates in the following plot without and with the model.<\/p>\n<p><img decoding=\"async\" class=\"\" 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 truly 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. In consequence, it allows 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>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"author":13,"featured_media":2330,"template":"","categories":[],"tags":[42],"class_list":["post-3572","solution","type-solution","status-publish","has-post-thumbnail","hentry","tag-retail"],"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<\/title>\n<meta name=\"description\" content=\"Explore how customer segmentation using machine learning can enhance targeting accuracy by identifying patterns in customer data for more effective analytics.\" \/>\n<meta name=\"robots\" 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