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return false;"> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path d="M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z"/></svg> </a></li></ul><div class="topnav-buttons"> <a href="#" data-toggle="modal" data-target="#lc-subscription" class="btn-desktop-only pulse-button v5 topnav-btn"> <span class="button-inner"> XP² Newsletter </span> </a> <a href="/newsletter/" class="pulse-button v5 topnav-btn btn-mobile-only"> <span class="button-inner"> XP² Newsletter </span> </a></div></div></div><div class="lc-progress-wrap"><div class="lc-scroll-progress"></div></div></header><article id="post-114898" class="et_pb_post post-114898 article type-article status-publish has-post-thumbnail hentry article-category-recommendations article-industry-ecommerce article-tags-amazon-personalization article-tags-product-recommendations article-function-conversion-optimization article-function-merchandising-ecommerce article-function-marketing article-type-industry-research article-type-thought-leadership"><div class="article-content"><div class="article-head-content-inner"><div class="article-breadcrumbs"> <a href="https://www.dynamicyield.com/articles/" title="Articles">Articles</a> <a href="https://www.dynamicyield.com/articles/category/recommendations/ ">Recommendations</a></div><h1 class="article-title">Two decades in the making – the powerful strategies behind the Amazon recommendation engine</h1><h2 class="article-excerpt">Built to humanize digital experiences for consumers, the Amazon recommendation engine has transformed eCommerce. And by taking a page from Amazon's book, brands can leverage winning strategies for their own personalization efforts.</h2><div class="article-authors lc-flex"><div class="article-author-box lc-col lc-flex"><div class="article-author-image lc-col"><div class="entry_author_image"><img src="https://www.dynamicyield.com/wp-content/authors/LeahRetta-81.png" alt="Leah Retta" width="76" height="76" /></div></div><div class="article-author-title lc-col"><div class="article-author-name"> <a href="https://www.dynamicyield.com/blog/author/leahretta/" title="Posts by Leah Retta" rel="author">Leah Retta</a></div><div class="article-author-title-text"> Content Writer</div></div></div></div></div><div class="entry-content article-entry-content"><div class="article-entry-content-inner"><p><em>This article is an excerpt from Dynamic Yield’s original <a href="https://www.dynamicyield.com/guides/amazon/">book about Amazon</a>, “The Chronicles of a Personalization Giant.” An in-depth analysis on how Amazon tailors the customer experience, chapter one outlines the strategy behind the retailer’s product discovery and merchandising tactics, including the sophistication of the </em><em>Amazon product recommendation</em><em> engine.</em></p><p>Amazon’s investment in <a href="https://www.dynamicyield.com/article/personalization-guide/">personalization</a> dates back to the early 2000s when it designed a plan to create a robust <a href="https://www.dynamicyield.com/product-recommendations/">product recommendation engine</a> after realizing the potential payoffs in becoming a powerful hub for product discovery. And to Amazon, it was clear that building a digital home for product inventory was not enough. Developing and continuously enhancing the Amazon recommendation engine algorithm, with access to an unprecedented amount of consumer data, could completely transform the way customers are matched with items they would most likely be interested in purchasing.</p><p>Not only would it work to provide pleasant user experiences, but more importantly, ones that felt personal. Before the era of eCommerce, the way consumers shopped was heavily influenced by the opinions and recommendations of friends and family – a component of product discovery Amazon sought to mimic online. “Discovery should be like talking with a friend who knows you, knows what you like, works with you at every step, and anticipates your needs,” <a href="https://pdfs.semanticscholar.org/0f06/d328f6deb44e5e67408e0c16a8c7356330d1.pdf" rel="noopener noreferrer" target="_blank">write Brent Smith and Greg Linden</a>, two industry titans specializing in personalization and recommendations at Amazon and Microsoft, respectively. From the onset, the end goal was to harness the power of machines and data to humanize the digital experience for consumers. </p><p>Since filing its first patent for the Amazon recommendation engine in 2001, the company has been uniquely marrying key customer data points across its digital properties to design tailored experiences for both known and unknown site visitors. And while endless variables have contributed to the company’s dramatic rise, its personalization efforts have indisputably played an integral role. As a result, <a href="https://www.dynamicyield.com/glossary/amazonization/">Amazonization</a> has disrupted and eaten up the eCommerce market, serving as a portal for product discovery, all while it continues to rapidly expand its reach into entertainment, subscriptions, food, voice, wearables, and more.</p><h2>A masterful recommendation strategy</h2><p>Recommendations truly are the bread-and-butter of Amazon’s personalization operation. By far the most sophisticated and distinguished element of the company’s eCommerce efforts, recommendations are visible across every page, channel, and device, employing dozens of unique and innovative strategies and taking endless forms. Upon conducting our research, <strong>45 different recommendation widgets were visible</strong> on the app homepage alone – a true testament to the company’s devotion to promoting product discovery and a signal of the power behind the Amazon machine learning recommendation engine.</p><p>Each recommendation widget served is based on a number of variables, including but not limited to:</p><ul><li>Location</li><li>Recent purchases</li><li>Trending: near you / on Amazon / by category / by shopping trend / by season</li><li>Saved items or lists</li><li>Deals, bargains, or discounts</li><li>Purchases other customers have completed after viewing similar products</li><li>User reviews</li><li>Curated top picks for customers</li></ul><p>As a hub for product discovery, constantly serving recommendations goes back to Amazon’s core belief for retail: <strong>never pass up an opportunity to capture a sale</strong>. Now that Amazon.com has increasingly become the initial starting point for discovery, the company is doubling down on its top-of-funnel marketing efforts. And a large part of the Amazon recommendation engine revenue generated is a direct result of the company’s sizable investment in personalization.</p><p>Having mastered traditional recommendations, Amazon’s approach has matured as it now invests in finding unique ways to uplevel its widgets with unconventional eCommerce tactics. For starters, Amazon tends to include dozens of recommendations on both a single page and also within a single widget. Its eCommerce team has also ensured the experience of browsing through recommendation carousels is consistent across channels, creating a pleasant and familiar user experience on every device. And while Amazon does invest in content discovery, it typically takes the form of banners or email messaging – reserving widgets solely for <a href="https://www.dynamicyield.com/lesson/product-recommendations-guide/">product recommendations</a>.</p><h3>The web experience</h3><p>With millions of products for sale on its site, in pursuit of driving purchases, Amazon relies heavily on recommendations to surface new products tailored to each web user. Never afraid to go a bit overboard, the number of widgets placed across each page is limitless, and the number of products served per widget knows no bounds. </p><p><img fetchpriority="high" decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/1-The-Web-Experience-Test5-1.gif" alt="" width="1330" height="686" class="alignnone size-full wp-image-114992" /></p><h3>The mobile experience</h3><p>Amazon uses its mobile properties as recommendation-focused digital inventory, squeezing as many product and content suggestions on the screen as possible, much like the web experience.</p><p><img decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/2-The-Mobile-Experience-Test.gif" alt="" width="1330" height="680" class="alignnone size-full wp-image-114966" /></p><p>Both the mobile site and app mimic one another, each featuring lengthy homepages with dozens of unique recommendation strategies. For example, some recommendations promote product discovery, while others encourage users to buy items previously purchased before.</p><h3>The email experience</h3><p>Amazon finds unique opportunities to leverage email to bring customers back to its site. It views email as prime inventory for showcasing more products and content. Transactional emails often feature recommendation widgets based on previously purchased items, seasonality, and trending products on the site at a given moment. Unlike the web and mobile experiences, however, email widgets are typically limited to just two recommendations per message.</p><h2>Examples of Amazon’s innovative recommendation strategies</h2><p>If today’s retailers want to <a href="https://www.dynamicyield.com/lesson/the-economics-of-ecommerce-conversion-optimization/">maximize eCommerce conversion rates</a> and revenue, they’ll have to go beyond serving average recommendation experiences. Below are a few of the unique ways Amazon is implementing recommendations, which brands can repurpose and leverage to capture sales and increase <a href="https://www.dynamicyield.com/glossary/average-order-value/">average order value (AOV)</a>.</p><h3>Allowing for easy comparison of similar items</h3><p>When viewing a <a href="https://www.dynamicyield.com/glossary/product-detail-page/">product detail page</a>, Amazon places a few recommendation widgets below the fold, appearing after the general info and details about the product in view. This widget, which precedes technical details and product specifications in page order, allows customers to catch a quick glimpse of similar products side-by-side. Details listed include customer ratings, price, delivery information, and size info (when applicable). This widget highlights other available product options and helps site visitors narrow down their purchase decision, allowing them to immediately add the most suitable product to their cart. </p><p><img decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/3-Comparing-similar-items--1024x706.jpg" alt="amazon recommendation widget" width="1024" height="706" class="alignnone size-large wp-image-114899" /></p><h3>Nudging users to log-in for better recommendations</h3><p>It should come as no surprise that today’s brands are able to better personalize site experiences when they know as much about a site visitor as possible. The Amazon recommendation system can tailor experiences on a more granular level when a user is logged in. As a result, it urges logged out and unknown users to sign into their accounts for a richer recommendation experience. For those who do not log-in, the retailer recommends items based on products a user has viewed in that particular session. </p><p><img loading="lazy" decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/4.2-Nudging-users-to-log-in--1024x221.jpg" alt="amazon sign in" width="1024" height="221" class="alignnone size-large wp-image-114909" /></p><p> <img loading="lazy" decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/4.1-Nudging-users-to-log-in--1024x524.jpg" alt="amazon recommendations single session" width="1024" height="524" class="alignnone size-large wp-image-114904" /></p><h3>Recommending products on category pages </h3><p>Amazon goes a step further with its recommendation widgets, placing them not only on product detail pages but across the site, including category and <a href="https://www.dynamicyield.com/glossary/product-listing-pages-plps/">product listing pages</a>. Strategies employed for these widgets include “Recommended for you” and “More top picks for you.” </p><p><img loading="lazy" decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/5-Recommending-products-on-category-pages--1024x684.jpg" alt="amazon product recommendation" width="1024" height="684" class="alignnone size-large wp-image-114914" /></p><h3>Serving subsequent purchase recommendations</h3><p>Amazon devolves from its standard recommendation widget design to promote products users tend to subsequently purchase after viewing a particular product. A <a href="https://www.dynamicyield.com/lesson/the-power-of-social-proof/">social proof strategy</a>, this approach pushes users further along the purchase funnel by focusing on products most likely to result in a <a href="https://www.dynamicyield.com/glossary/conversion/">conversion</a>.</p><p><img loading="lazy" decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/6-Serving-subsequent-purchase-recommendations--1024x651.jpg" alt="complementary product recommendation" width="1024" height="651" class="alignnone size-large wp-image-114919" /></p><h3>Surfacing recommendations for short-term promotions</h3><p>To create a sense of urgency, Amazon extends recommendations to its time-sensitive product promotions, curating a collection of recommendations from a given day’s “deals.” To further entice users, it lists the previous price of the product, educating users on the savings they will accrue if they choose to purchase the product while it is temporarily discounted.</p><p><img loading="lazy" decoding="async" src="https://www.dynamicyield.com/wp-content/uploads/2020/01/7-Surfacing-recommendations-for-short-term-promotions--1024x538.jpg" alt="promotional recommendation" width="1024" height="538" class="alignnone size-large wp-image-114924" /><br /></p><h2>An opportunity to make recommendations work harder</h2><p>eCommerce merchants may look at Amazon and see the odds stacked against them, but there are endless possibilities when it comes to improving the customer experience which aren’t limited to the retail giant. By taking a page from its book on recommendations, brands can stand taller and reap greater rewards, carving out a piece of the market for themselves.</p><p>Interested in deploying Amazon-style recommendations on your site? Learn more about Dynamic Yield’s <a href="https://www.dynamicyield.com/personalization/">personalization platform</a>.</p><div class="article-separator"><svg width="54" height="26" viewBox="0 0 54 26" fill="none" xmlns="http://www.w3.org/2000/svg"> <path d="M53.0088 25.6367C52.7884 21.9564 51.8025 18.3625 50.1141 15.0849C48.4256 11.8073 46.0718 8.9181 43.2031 6.60203L43.2031 25.6367L53.0088 25.6367Z" fill="black"/> <path d="M14.4395 3.59038C10.3237 5.69174 6.82743 8.83082 4.29638 12.6973C1.76533 16.5638 0.28711 21.0239 0.0078125 25.6367L14.4395 25.6367L14.4395 3.59038Z" fill="black"/> <path d="M17.6563 2.20809L17.6562 25.6367L39.9829 25.6367L39.9829 4.36701C39.9829 4.36701 30.7303 -2.31342 17.6563 2.20809Z" fill="black"/> </svg></div><div class="article-tags-block"> <strong>Tags:</strong> <a href="https://www.dynamicyield.com/tags/amazon-personalization/">Amazon Personalization</a><a href="https://www.dynamicyield.com/tags/product-recommendations/">Product Recommendations</a></div></div><div class="article-content-sidebar"><div class="article-content-sidebar-inner"><h4>Read next</h4><ul class="article-sidebar-nav"><li> <a href="https://www.dynamicyield.com/article/how-visual-search-is-redifining-product-discovery/">When Words Fall Short, Let the Image Speak: How Visual Search Is Redefining Product Discovery</a><div class="article-sidebar-nav-author">Lior Delouya</div></li><li> <a href="https://www.dynamicyield.com/article/ai-personalization-revolutionizing-ecommerce-search/">How AI and Personalization Are Revolutionizing E-commerce Search (Finally)</a><div class="article-sidebar-nav-author">JR Moore</div></li></ul></div></div></div></div></article></div></div><section class="lc-subscription-section"><div class="lc-subscription-form-block lc-subscription-inner"><h4 class="lc-subscription-title">Sign up for the XP² newsletter</h4><div class="lc-subscription-text">Join thousands of readers from Target, Citi, Spotify, Hulu, Google, Sephora, and other innovative brands who read our bi-weekly XP² newsletter, delivering educational content, research, and insights straight to your inbox</div><form class="mktoForm" data-formId="3876" data-formInstance="sub-inline"></form><div class="lc-privacy-wrapper"><div class="lc-privacy"> You may unsubscribe at any time. 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// GA ID and Referrer
var dy_utms_cookie = {};
document.cookie.split(';').forEach(function(el) {
var splitCookie = el.split('=');
var key = splitCookie[0].trim();
var value = splitCookie[1];
dy_utms_cookie[key] = value;
});
if(dy_utms_cookie["_ga"]) {
form[0].querySelector('input[type="hidden"][name="Visitor_ID__c"]').value = dy_utms_cookie["_ga"].substring(6);
}
if(dy_utms_cookie["personalize_referrer_string"]) {
form[0].querySelector('input[type="hidden"][name="Referral__c"]').value = dy_utms_cookie["personalize_referrer_string"].substring(6);
}
// ZoomInfo
if(localStorage.getItem('ZoomInfoData')) {
var zoominfo_data = JSON.parse(localStorage.getItem('ZoomInfoData'));
if(zoominfo_data) {
form[0].querySelector('input[type="hidden"][name="Alexa_Rank__c"]').value = zoominfo_data.alexaglobalrank;
form[0].querySelector('input[type="hidden"][name="Employees__c"]').value = zoominfo_data.employeesrange;
form[0].querySelector('input[type="hidden"][name="Company_Revenue_Range__c"]').value = zoominfo_data.estimatedannualrevenue;
}
}
// Also, dispatch a dataLayer event on success
_form.onSuccess(function(values, follow_up_url) {
window.dataLayer = window.dataLayer || [];
if([3739, 4802, 5094, 5110, 4946, 5076, 5116, 5171, 5172, 5173].includes(_form.getId())) {
window.dataLayer.push({
'event': 'demo_request_complete',
'eventCallback': function() {
if(follow_up_url) {
window.location.href = follow_up_url;
}
}
});
return false;
} else if([3876].includes(_form.getId())) {
window.dataLayer.push({
'event': 'newsletter_signup_complete',
'eventCallback': function() {
if(follow_up_url) {
window.location.href = follow_up_url;
}
}
});
return false;
}
});
});
}</script> <script>if(typeof(jQuery) !== 'undefined') {
$ = jQuery.noConflict();
}
function getUrlParameter(sParam) {
var sPageURL = decodeURIComponent(window.location.search.substring(1)),
sURLVariables = sPageURL.split('&'),
sParameterName,
i;
for (i = 0; i < sURLVariables.length; i++) {
sParameterName = sURLVariables[i].split('=');
if (sParameterName[0] === sParam) {
return sParameterName[1] === undefined ? true : sParameterName[1];
}
}
}
$(window).load(function(){
var videoID = getUrlParameter('video');
if(videoID !== undefined){
if($('#wistia-' + videoID + '-1').length){
var videoName = $('#wistia-' + videoID + '-1').parents('.tab-pane');
videoName = videoName[0].id
}
if($('a[href="#' + videoName +'"]').length){
$('a[href="#' + videoName +'"]').each(function(){
$(this).click();
});
}
addScript('https://fast.wistia.com/embed/medias/'+ videoID +'.jsonp');
addScript('https://fast.wistia.com/assets/external/E-v1.js');
$('body').append('<span class="wistia_embed wistia_async_'+videoID+' popover=true popoverContent=link dy-wistia-popup" style="display:inline"></span>');
window._wq = window._wq || [];
_wq.push({ id: videoID, onReady: function(video) {
var video = Wistia.api(videoID);
video.popover.show(); // open the popover
video.play(); // play the video
setTimeout(function(){video.unmute();}, 500);
}});
}
});</script> <style>#adBanner {
background-color: transparent;
height: 0;
width: 1px;
}</style><div id="wrapfabtest"><div id="adBanner"></div></div></body></html>
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