{"version":"1.0","provider_name":"Technology and Operations Management","provider_url":"https:\/\/d3.harvard.edu\/platform-rctom","author_name":"Paxton Zhou","author_url":"https:\/\/d3.harvard.edu\/platform-rctom\/author\/paxton-zhou\/","title":"Machine Learning in Airline Loyalty Programs - Technology and Operations Management","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"LO5Y0vhtHf\"><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-in-airline-loyalty-programs\/\">Machine Learning in Airline Loyalty Programs<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/machine-learning-in-airline-loyalty-programs\/embed\/#?secret=LO5Y0vhtHf\" width=\"600\" height=\"338\" title=\"&#8220;Machine Learning in Airline Loyalty Programs&#8221; &#8212; Technology and Operations Management\" data-secret=\"LO5Y0vhtHf\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/d3.harvard.edu\/platform-rctom\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Qantas.jpg","thumbnail_width":800,"thumbnail_height":498,"description":"Airline loyalty programs (also called Frequent Flyer Programs) have become a new source of high margin income for traditional airline companies. Meanwhile, loyalty programs also generate massive amount of data on customer behaviour as people spend and collect their points. Applying machine learning tools to understand the preferences of those frequent flyers, most of whom have strong spending power, will enable an airline loyalty program to monetize on areas beyond travel. Qantas Australia is the leader in adopting a data-centric approach to manage their loyalty business."}