{"id":3637,"date":"2024-10-10T19:34:37","date_gmt":"2024-10-10T19:34:37","guid":{"rendered":"https:\/\/www.enginius.biz\/index.php\/models\/predictive-2\/"},"modified":"2024-10-14T18:39:16","modified_gmt":"2024-10-14T18:39:16","slug":"predictive","status":"publish","type":"page","link":"https:\/\/www.enginius.biz\/index.php\/business\/models\/predictive\/","title":{"rendered":"Predictive modeling"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"3637\" class=\"elementor elementor-3637\" data-elementor-post-type=\"page\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-fc02610 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fc02610\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\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-b8bc4c1\" data-id=\"b8bc4c1\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-6cac7d6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6cac7d6\" 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-50 elementor-inner-column elementor-element elementor-element-842e829\" data-id=\"842e829\" 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-cd5972e elementor-widget elementor-widget-image\" data-id=\"cd5972e\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"370\" height=\"400\" src=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/placeit_predictive_overview.png\" class=\"attachment-full size-full wp-image-1844\" alt=\"\" srcset=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/placeit_predictive_overview.png 370w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/placeit_predictive_overview-278x300.png 278w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/placeit_predictive_overview-185x200.png 185w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-7a2344d\" data-id=\"7a2344d\" 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-e702eb6 elementor-widget elementor-widget-heading\" data-id=\"e702eb6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Predictive modeling<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f45602f dark-para elementor-widget elementor-widget-text-editor\" data-id=\"f45602f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The predictive module in Enginius is a powerful and versatile model that helps managers predict a variety of outcomes, such as loyalty, brand choice, response to an offer, expected revenues, and so on, based on a set of available predictors. Once the model has been calibrated on past data, it can be directly applied to new data sets with ease to obtain predictions.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\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\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2264ecb elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2264ecb\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\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-50 elementor-top-column elementor-element elementor-element-a99bd9b\" data-id=\"a99bd9b\" 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-edc0aa8 elementor-widget elementor-widget-heading\" data-id=\"edc0aa8\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What you put in...<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2373e43 elementor-widget elementor-widget-text-editor\" data-id=\"2373e43\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Customer&#8217;s choice data for alternative offerings<\/li><li>Customer ratings of alternative offerings on their key attributes<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-cf3e941\" data-id=\"cf3e941\" 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-0e7747b elementor-widget elementor-widget-heading\" data-id=\"0e7747b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What you get out...<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2c96225 elementor-widget elementor-widget-text-editor\" data-id=\"2c96225\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Purchase probabilities, predicted and observed choices of customers<\/li><li>Factors influencing customer choice, including brand as well as performance attributes<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\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<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0200c61 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0200c61\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\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-3a5a92e\" data-id=\"3a5a92e\" 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-e475c3a heading elementor-widget elementor-widget-heading\" data-id=\"e475c3a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Key features<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-cff8c1c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"cff8c1c\" 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-50 elementor-inner-column elementor-element elementor-element-099dbe4\" data-id=\"099dbe4\" 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-583c15b elementor-invisible elementor-widget elementor-widget-image\" data-id=\"583c15b\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeInLeft&quot;}\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"400\" height=\"300\" src=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_1.png\" class=\"attachment-large size-large wp-image-1909\" alt=\"\" srcset=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_1.png 400w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_1-120x90.png 120w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_1-300x225.png 300w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_1-260x195.png 260w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-4f25980\" data-id=\"4f25980\" 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-8a7d792 elementor-widget elementor-widget-heading\" data-id=\"8a7d792\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Versatile predictive models<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c9027b2 elementor-widget elementor-widget-text-editor\" data-id=\"c9027b2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Enginius can predict different types of variables, such as binary outcomes (which customers will buy, churn, or click?), multinomial outcomes (which brand will they choose?), or continuous ones (how much will they spend?), all from the same simple interface.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\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<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-c2fe170 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c2fe170\" 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-50 elementor-inner-column elementor-element elementor-element-2e8903e\" data-id=\"2e8903e\" 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-b99839a elementor-invisible elementor-widget elementor-widget-image\" data-id=\"b99839a\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeInLeft&quot;}\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"400\" height=\"300\" src=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_2.png\" class=\"attachment-large size-large wp-image-1910\" alt=\"\" srcset=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_2.png 400w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_2-120x90.png 120w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_2-300x225.png 300w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_2-260x195.png 260w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-6f70a4c\" data-id=\"6f70a4c\" 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-f024f44 elementor-widget elementor-widget-heading\" data-id=\"f024f44\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Discrete-continuous model<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-78b275d elementor-widget elementor-widget-text-editor\" data-id=\"78b275d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The discrete-continuous model is a powerful variant where the model predicts at the same time who will make a purchase, and if so, for how much? The target variable is therefore either a zero (no purchase) or an amount, and the same predictor is allowed to have a positive impact on one component of the model, but a negative impact on another. For instance, customers who usually purchase for small quantities might experience a higher chance of making a future purchase (higher likelihood) but for a smaller amount (lower value). These moving parts are independently estimated, and then combined to compute the net effect of each predictor.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\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<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-9f94163 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"9f94163\" 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-50 elementor-inner-column elementor-element elementor-element-43f2543\" data-id=\"43f2543\" 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-cb681a4 elementor-invisible elementor-widget elementor-widget-image\" data-id=\"cb681a4\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeInLeft&quot;}\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"300\" src=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_3.png\" class=\"attachment-large size-large wp-image-1911\" alt=\"\" srcset=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_3.png 400w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_3-120x90.png 120w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_3-300x225.png 300w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_3-260x195.png 260w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-0154dd0\" data-id=\"0154dd0\" 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-d6c656a elementor-widget elementor-widget-heading\" data-id=\"d6c656a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Multifold-cross validation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-27b1f7e elementor-widget elementor-widget-text-editor\" data-id=\"27b1f7e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Cross-validation is a well-known mechanism to estimate the robustness of the predictions, and assess whether a good fit is not only achieved by chance, and that the model does not simply capture noise. Performing multifold-cross validation with Enginius is as simple as clicking on a button.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\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<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-77581eb elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"77581eb\" 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-50 elementor-inner-column elementor-element elementor-element-1ce8d61\" data-id=\"1ce8d61\" 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-4bdb654 elementor-invisible elementor-widget elementor-widget-image\" data-id=\"4bdb654\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;fadeInLeft&quot;}\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"300\" src=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_4.png\" class=\"attachment-large size-large wp-image-1912\" alt=\"\" srcset=\"https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_4.png 400w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_4-120x90.png 120w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_4-300x225.png 300w, https:\/\/www.enginius.biz\/wp-content\/uploads\/2018\/07\/predictive_feature_4-260x195.png 260w\" sizes=\"100vw\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-18d4ee5\" data-id=\"18d4ee5\" 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-f47e13c elementor-widget elementor-widget-heading\" data-id=\"f47e13c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Built-in data transformation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bc5712b elementor-widget elementor-widget-text-editor\" data-id=\"bc5712b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Real data is often skewed. For instance, most purchase amounts will be within the same range, but some observations will be outliers and may prevent the model to correctly fit the data. Rather than getting rid of valuable observations, Enginius allows you to automatically transform both the predictors and the target variable with the click of a button (Cox-Box or log-transforms). Categorical predictors (e.g., \u201cmale\u201d, \u201chigh value\u201d, etc.) will be automatically transformed and discretized as well.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\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 class=\"elementor-element elementor-element-7577bb6 heading elementor-widget elementor-widget-heading\" data-id=\"7577bb6\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">About predictive modeling<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-66a8a05 elementor-widget elementor-widget-text-editor\" data-id=\"66a8a05\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The Customer Choice (Logit) model is an individual-level response model that helps to analyze and explain the choices individual customers make in the market. The Customer Choice model helps firms to understand the extent to which such factors as price of a brand or its ease of installation influence a customer&#8217;s choice of a brand. A brand&#8217;s purchase probability at the individual level is equivalent to the brand&#8217;s market share at the market level.<\/p><p>Firms can use Customer Choice analysis to develop marketing programs that are tailored to specific market segments, or even tailored to individual customers.<\/p><p>This model uses the following input:<\/p><ul><li>Single Alternative\/Boolean<br \/>This method analyzes only one option instead of choosing one among several alternatives. For this analysis, only one brand&#8217;s data is required.<\/li><li>Multiple Alternatives<br \/>This method considers customer response across a subset of related competitors. For this analysis, the following data is required for all competing brands involved in the study.<\/li><\/ul><p>For each customer, the data that goes into this model is a set of ratings on various attributes of each alternative (either single alternative &#8220;yes\/no&#8221; response, or multiple alternatives &#8220;chose one of N&#8221; response) involved in the study, and the alternative that the customer chose in each period. For the &#8220;Single Alternative\/Boolean&#8221; option, this would be a 1 or 0, depending on whether or not the customer chose this alternative. For the &#8220;Multiple Alternatives&#8221; option, one alternative would be a 1 to indicate the alternative chosen during this period, while the others remain 0 to indicate that this particular customer did not choose the other alternatives.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\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<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ac9c23b elementor-section-height-min-height elementor-section-boxed elementor-section-height-default elementor-section-items-middle\" data-id=\"ac9c23b\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\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-a4e1538\" data-id=\"a4e1538\" 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-0faccdc elementor-widget elementor-widget-heading\" data-id=\"0faccdc\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Want to see Enginius in action and learn more about how Enginius can help you?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2606c61 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"2606c61\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/www.enginius.biz\/index.php\/business\/schedule-a-demo\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Contact us to schedule a demo!<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\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},"excerpt":{"rendered":"<p>Predictive modeling The predictive module in Enginius is a powerful and versatile model that helps managers predict a variety of outcomes, such as loyalty, brand choice, response to an offer, expected revenues, and so on, based on a set of available predictors. Once the model has been calibrated on past data, it can be directly &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/www.enginius.biz\/index.php\/business\/models\/predictive\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Predictive modeling&#8221;<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"parent":3629,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"yst_prominent_words":[502,98,149,83,417,67,376,770,727,731,557,365,993,369,85,420,253,989,406,981],"class_list":["post-3637","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/pages\/3637","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/comments?post=3637"}],"version-history":[{"count":0,"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/pages\/3637\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/pages\/3629"}],"wp:attachment":[{"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/media?parent=3637"}],"wp:term":[{"taxonomy":"yst_prominent_words","embeddable":true,"href":"https:\/\/www.enginius.biz\/index.php\/wp-json\/wp\/v2\/yst_prominent_words?post=3637"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}