{"id":330,"date":"2023-03-17T10:01:49","date_gmt":"2023-03-17T10:01:49","guid":{"rendered":"http:\/\/geoiqfrontendblogsprodwordpress-env.eba-dpx723ys.ap-south-1.elasticbeanstalk.com\/index.php\/2023\/03\/17\/predicting-affluence-scores-for-lead-prioritization-location-data-at-play\/"},"modified":"2024-07-10T13:43:28","modified_gmt":"2024-07-10T08:13:28","slug":"predicting-affluence-lead-score-for-lead-prioritization-location-data-at-play","status":"publish","type":"post","link":"http:\/\/geoiq.ai\/blog\/predicting-affluence-lead-score-for-lead-prioritization-location-data-at-play\/","title":{"rendered":"Predicting Affluence Lead Score For Lead Prioritization: Location Data at Play"},"content":{"rendered":"<p><em>Lead prioritization is not a new concept. Businesses use CRM and other platforms to manage and prioritize their leads for faster conversions and better deal size. What has worked until now is to prioritize leads based on ICP (Ideal Customer Profile) and Degree of Intent, which is essential but insufficient. We take it a step further by introducing location data and affluence lead score to the process. <\/em><\/p>\n<figure class=\"kg-card kg-image-card kg-card-hascaption\"><figcaption><em><img fetchpriority=\"high\" decoding=\"async\" class=\"size-medium wp-image-1430 aligncenter\" src=\"https:\/\/geoiq.ai\/blog\/wp-content\/uploads\/2023\/03\/lead-priorisation-300x169.png\" alt=\"pillars of lead priorisation\" width=\"300\" height=\"169\" \/> \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Pillars of Lead Prioritization<\/em><\/figcaption><\/figure>\n<p><a href=\"https:\/\/geoiq.ai\/blog\/location-data-to-predictive-ai-bridging-the-gap\">Location data<\/a> is a great indicator of user affluence. One can draw a lot of intelligence and insights about user affluence and behavior by simply studying the location attributes of their presence. The affluence score that we calculate is an aggregate of multiple location attributes, some of which are average rentals, population density, presence of brands, average meal cost for two, household income, historical pattern, and more.<\/p>\n<p>When you augment the existing model for lead prioritization with<a href=\"https:\/\/geoiq.ai\/blog\/location-data-and-intelligence-trends-in-2023\"> location data and intelligence<\/a>, you are able to shrink your final funnel of warm leads to a smaller pool of hot leads. The result is in terms of increased conversions by reducing effort and time consumption.<\/p>\n<figure class=\"kg-card kg-image-card kg-card-hascaption\"><figcaption><em><img decoding=\"async\" class=\"size-medium wp-image-1432 aligncenter\" src=\"https:\/\/geoiq.ai\/blog\/wp-content\/uploads\/2023\/03\/augmented-model-300x114.png\" alt=\"augmented model\" width=\"300\" height=\"114\" \/> \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 A New improved model augmented with location data<\/em><\/figcaption><\/figure>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_73 ez-toc-wrap-left counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"http:\/\/geoiq.ai\/blog\/predicting-affluence-lead-score-for-lead-prioritization-location-data-at-play\/#Methodology_of_Attaining_a_lead_score\" title=\"Methodology of Attaining a lead score\">Methodology of Attaining a lead score<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"http:\/\/geoiq.ai\/blog\/predicting-affluence-lead-score-for-lead-prioritization-location-data-at-play\/#How_is_Affluence_Lead_Score_Calculated\" title=\"How is Affluence Lead Score Calculated?\">How is Affluence Lead Score Calculated?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"http:\/\/geoiq.ai\/blog\/predicting-affluence-lead-score-for-lead-prioritization-location-data-at-play\/#Outcome\" title=\"Outcome\">Outcome<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"http:\/\/geoiq.ai\/blog\/predicting-affluence-lead-score-for-lead-prioritization-location-data-at-play\/#Conclusion\" title=\"Conclusion\">Conclusion<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1 id=\"methodology\"><span class=\"ez-toc-section\" id=\"Methodology_of_Attaining_a_lead_score\"><\/span><strong>Methodology of Attaining a lead score<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>When you have a large number of leads coming in every day, it is practically impossible to pursue each of them. It is also not necessary to pursue all of them as a considerable percentage of these leads are junk.<\/p>\n<p>Even among the good leads, a considerable number of leads would be cold, where there is no intent or the lead does not fall in the ICP bucket. But what beyond that? For the leads that have intent or fall under the ICP category, the user might not have the spending capacity for the service\/ product.<\/p>\n<p>Here, affluence plays a key role, which could be quantified by considering location attributes. The true hot leads are the ones that are filtered through affluence lead score.<\/p>\n<h2 id=\"how-is-affluence-calculated\"><span class=\"ez-toc-section\" id=\"How_is_Affluence_Lead_Score_Calculated\"><\/span><strong>How is Affluence Lead Score Calculated?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Here\u2019s the process to calculate user affluence in simple pointers:<\/p>\n<ul>\n<li>Our no-code ML model takes the addresses of the older leads. That have converted or not converted as input and identify locations where these users are present<\/li>\n<li>It then studies the characteristics\/ attributes of these locations or catchments to identify affluence indicators<\/li>\n<li>The location attributes identified for users that converted are the positive indicators and similarly, the location attributes identified with the users that did not convert are negative indicators<\/li>\n<li>Location attributes to calculate affluence scores could be different for different businesses. It can be based on their products, target groups, use cases, and other factors<\/li>\n<li>In the case of a fintech brand we worked with, some of the key affluence indicators were identified to be average rentals, population density, presence of brands, average meal cost for two, household income, and presence of tertiary roads, among others<\/li>\n<li>Once model learning is complete, based on the attributes finalized for affluence prediction, the model will start assigning scores to all the new leads<\/li>\n<\/ul>\n<h2 id=\"outcome\"><span class=\"ez-toc-section\" id=\"Outcome\"><\/span><strong>Outcome<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>For one of our fintech clients, we achieved a 5% uptick in success rate, by prioritizing their leads considering affluence. Moreover, the time and effort wasted on futile leads were considerably saved, in turn reducing the turnaround time of conversions.<\/p>\n<figure class=\"kg-card kg-image-card\"><img decoding=\"async\" class=\"size-medium wp-image-1433 aligncenter\" src=\"https:\/\/geoiq.ai\/blog\/wp-content\/uploads\/2023\/03\/lead-score-calculation-300x132.png\" alt=\"affluence lead score\" width=\"300\" height=\"132\" \/><\/figure>\n<h2 id=\"conclusion\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><strong>Conclusion<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A location tells a lot about user behavior and affluence. When businesses harness this data and draw insights for prioritizing. They could benefit in terms of improving the accuracy of affluence prediction, success rate, leads\u2019 conversion rate, and turn-around time.<\/p>\n<p>Again, affluence is a key parameter when it comes to lead prioritization and it takes the whole process a notch higher.<\/p>\n<p>Visit <a href=\"http:\/\/geoiq.ai\">GeoIQ<\/a> to know more about how lead score can help in lead prioritization.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Lead prioritization is not a new concept. Businesses use CRM and other platforms to manage and prioritize their leads for faster conversions and better deal size. What has worked until now is to prioritize leads based on ICP (Ideal Customer Profile) and Degree of Intent, which is essential but insufficient. We take it a step [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":320,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-330","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.3 - 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