Media & Entertainment
Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming.
"Our team at Warner Bros. Discovery wanted to build a promotion engine to customize movie and show recommendations for unauthenticated users across our digital properties. We wanted to drive cross brand engagement as users traverse the brands and content across the WBD ecosystem. With Amazon Personalize we were able to build and train a real-time recommendation engine POC within two days. Since deployment on our TBS, TNT, TruTV and Adult Swim web properties, over 25k unique consumers have clicked on cross-portfolio promotions for the movies, shows and site sections recommended by Amazon Personalize. These promising results have paved the way for us to deploy our promo engine on CNN next month. For the users receiving personalized promotions we have seen total user engagement increase by 14% and cross brand engagement increase by 12% compared to a randomized control group. We have also observed a 2x to 3x increase in response rate using personalized promotions vs. simply promoting our most popular items to consumers. Amazon Personalize has been instrumental in showcasing content that our fans want to see more effectively across our various brands."
Don Browning, VP Cloud Architecture, WBD
FOX Corporation (FOX) produces and distributes news, sports, and entertainment content. Initially, FOX was using a monolithic, legacy system to personalize user content, but wanted to pioneer a new solution in the cloud. They chose to innovate with Amazon Personalize to curate customer experience and marketing across their properties.
“The ability to recommend videos, articles and relevant marketing information based on user or content trends across all Fox properties allows us to curate an experience that puts our customer first. Using Amazon Personalize, we have been able to suggest content more accurately to our customers, and early analyses indicate a lift of 6% in average minutes viewed per recommendation and 15% reduction in bounce rate compared to our legacy system. We’ve also been able to continue to build upon the level of personalization we offer to our customers, since Amazon Personalize makes it easier for our data scientists to iterate quickly. This means that each customer's journey is getting more and more tailored to their preferences the longer they visit our properties.”
Alex Tverdohleb, VP of Data Services, FOX
Discovery Education (DE) is the worldwide edtech leader whose state-of-the-art digital platform supports learning wherever it takes place. Through its award-winning multimedia content, instructional supports, and innovative classroom tools, Discovery Education helps educators deliver equitable learning experiences engaging all students and supporting higher academic achievement on a global scale. Discovery Education serves approximately 4.5 million educators and 45 million students worldwide, and its resources are accessed in nearly 100 countries and territories.
“Our goal is to use machine learning to better match what we know about our educators, and what we know about our students, and how our platform is being used, to make a better, more personalized recommendation. In turn, this allows teachers to spend more time with their students, and less time looking for content. By using Amazon Personalize, we are able to personalize our K12 learning platform through a “Just For You” reel on the homepage to connect educators with a unique, personalized set of resources based on grade level, preferences, and resources. As a result, we have seen a 229% increase on click-through-rate with resources on the homepage, as well as a 220% increase to our high-value interactions with content, such as assigning, downloading, and sharing. For us we feel like we're just in the early innings of using machine learning and what personalization can help us achieve.”
Pete Weir, Chief Product Officer, Discovery Education
Bundesliga, Germany’s premier football league (aka Deutsche Fußball Liga (DFL)), leverages Amazon Personalize to create an individualized, regionalized and personalized experience for their fans.
“We used Amazon Personalize to generate individualized content for our millions of active Bundesliga Official App users each season. As a result, we’ve seen a 67% increase in article reads per user and a 17% improvement in the amount of time users spend in the app. Amazon Personalize is instrumental in supplying our fans with the content they want to see more effectively.”
Andreas Heyden, EVP of Digital Innovations, DFL Group
Equinox Group is a high growth collective of the world's most influential, experiential, and differentiated lifestyle brands. In addition to Equinox, its other brands, Blink, Pure Yoga, SoulCycle, and Equinox Hotels are all recognized for inspiring and motivating members to maximize life. Its portfolio of brands is recognized globally with locations within every major city across the United States in addition to London, Toronto, and Vancouver.
“With demand for home-based workouts increasing during the pandemic, we wanted to customize the member experience in the Equinox+ app by recommending relevant, contextualized content and classes based on individual member preferences. Using Amazon Personalize to A/B test the benefits of machine learning-generated recommendations against an existing rule-based recommendation system on a small portion of app traffic, we saw a 92% increase in engagement with carousel content on our app's homepage. Personalize was also relatively quick to stand-up and scale, which was how we were able to show the business value of personalization to internal teams. Because of this, we are moving forward on expanding Personalize capabilities more broadly across our app and other business units."
Jay Fuller, Head of Data Science, Equinox
Public Broadcasting Service (PBS) is a Virginia-based nonprofit organization founded in 1969 that broadcasts educational, news, and entertainment programs to more than 100 million television viewers across the U.S. and more than 32 million people online. PBS currently has approximately 330-member television stations, distributing the highest quality of content to all 50 U.S. states, Puerto Rico, U.S. Virgin Islands, Guam, and American Samoa.
“We worked with ClearScale, an AWS Premier Partner, to set up and configure our initial solutions and data pipelines. We needed to leverage insights faster and launch something in months rather than years. Their experts set up an AWS Cloud configuration and related services for using Amazon Personalize to save us a tremendous amount of effort and thousands of engineering hours. With Amazon Personalize, just inserting a small set of viewers, videos, and interactions, we saw recommendations that stood up and could possibly scale. From there, we knew it was time to go a step further, do a real proof of concept, and establish an architecture that could plug in with our existing databases."
Mikey Centrella, Direct of Product Management, PBS
Razer is the world’s leading lifestyle brand for gamers with over 175 million users. With a fan base that spans every continent, the company has designed and built a gamer-focused marketplace of hardware, software, and services.
“With a large and growing number of users, we saw an opportunity to deepen the relationships we had with our gamers by offering them hyper-relevant products. As such, we were keen to test the possibilities of machine learning (ML). However, as a small team, it posed a challenge when we needed to maintain a recommendation infrastructure. Using Amazon Personalize for intelligent user segmentation and advanced filtering, personalized recommendations were implemented on Razer Synapse, a software utility tool. The tool now recommends complementary devices to users given their existing device setup and configuration in both batch and real-time communications. Amazon Personalize has enabled us to see a click-through-rate 10x better than industry standards, generating additional revenue for the business. Leveraging ML and Amazon Personalize made it easier and more convenient for us to maintain a personalization system.”
Hong Jie Wee, Big Data Lead, Razer Inc.
Ticketek is owned by TEG and is a global leader in ticketing and technology with 40+ years of experience ticketing major international events and partnering with the world’s premier venues. Based in Australia, TEG operates more than 30 brands in 40 countries on six continents.
“Fans and innovations are at the heart of everything we do. We bring thousands of live events to fans, selling ~30 million tickets annually at some of the world’s most iconic venues, and connect hundreds of entertainment and brand partners to new audiences each year. While our Tier 1 events tend to sell themselves, our Tier 2-4 events do not sell-out and rely on marketing and promotion. In Australia, we have 4 million subscribers that receive a weekly email newsletter. It was only sent based on “state” parameters with no other personalization. Using Amazon Personalize, we are now able to provide customers with a greater diversity of shows and events that suit their unique interests. Our purchase rate improved by 250%, with volume of tickets sold per newsletter open increasing by 49%. This demonstrates how the convergence of technology, marketing, and data science has yielded impactful operational and growth benefits for us.”
Tane Oakes, CTO, TEG
FanFight is one of India’s largest and most prominent fantasy sports companies, with over 5M users.
“We started FanFight in 2018 to bring disruption to the fantasy sports world in India. We pride ourselves on our customer focus and always seek to deliver the best experience for our users.
For initial years our goal was to build a scalable platform and give the best possible experience for the users to play fantasy sports games on our platform. With time we grew from 1 Million users in 2018 to 5 Million+ Users in 2020 and now we wanted to build a personalized experience for each user for better conversions. On our platform users have a variety of contests to play and it takes time for users to navigate and make decisions; we wanted to simplify this and make their decision-making process as seamless as possible. To solve this we used Amazon Personalize to build personalized recommendations for each user and recommend the most relevant contest on the first page. With Amazon Personalize, we were able to deliver the best possible contest recommendations based on user's playing history and also used it to upsell and cross other similar contests. This feature helped us improve the average number of contest joins per user by 12% and also improved the average transaction value of gameplay by 8%.”
Mukul Anand, VP Product, FanFight
Proud digital partner to some of the biggest names in sport, Pulselive create experiences sports fans can’t live without, whether that’s the official Cricket World Cup website or the English Premier League’s iOS and Android apps.
“We’re focused on how we can use data to personalise and enhance the online fan experience for our clients through the Pulselive Platform. With Amazon Personalize, we’re now providing sports fans personalised recommendations enabled by machine learning. We don’t consider ourselves machine learning experts, but found Personalize to be straightforward and the integration was complete in a few days. For one of our clients, a premier European football club with millions of fans globally, we immediately increased video consumption by 20% across their website and mobile app. Their fans are clearly embracing the new recommendations. Leveraging Amazon Personalize, we will be able to further push the limits in building data driven 1-to-1 personalised experiences for sports fans everywhere.”
Wyndham Richardson, Managing Director & Co-Founder, Pulselive
Coursera is a leading provider of universal access to the world’s best education, partnering with over 190 top universities and organizations to offer courses online to its more than 40 million users.
"Every learner comes to Coursera with a unique set of educational goals. With over 4,000 classes available, the challenge is tailoring the experience to the personal interests of every user. Amazon Personalize allows us to adapt to individual preferences in real-time, providing highly relevant recommendations that engage our learners. Within a few weeks we were able to develop and deploy the Amazon Personalize model into production with the benefits of automatically scaling for our 40 million users."
Mark Chamness, Director, Data Science & Machine Learning, Coursera
SHOWROOM is a Japanese live streaming platform where thousands of people, including Japanese Idols such as AKB48 and NOGIZAKA46, regularly stream. The connection that is created between streamers and viewers is a unique experience at the core of the company’s business model.
“By using Amazon Personalize we were able to quickly deploy real-time customized performer recommendations to our new users. Amazon Personalize recommendations have increased livestream viewing by 60% among new users as compared to our legacy popularity-based recommendation system.”
Kengo Senuma, AI Team Manager, SHOWROOM Inc.
ViewLift is a full-service digital content distribution platform empowering media companies, sports leagues and teams, education providers and others to monetize their content through native branded apps on major OTT devices including web, mobile, TV connected devices, Smart TVs and gaming consoles.
“With Amazon Personalize integrated into our platform, we have enabled our clients to maintain a +24% increase in clicks on the recommended videos tray compared to the curated or auto generated trays of content. Even more, our cost and data science resources required to train our own custom machine learning recommendation models and scale to millions of users have significantly reduced.”
Manik Bambha, Co-founder & President, Viewlift
TVNZ is New Zealand’s state-owned, commercially funded broadcaster. TVNZ’s all about sharing the moments that matter - whether it’s breaking news, following adventures, sharing stories or putting smiles on faces. Each day, TVNZ reaches more than 2 million New Zealanders through TVNZ 1, 2, DUKE, TVNZ OnDemand and children’s platform HEIHEI.
“The TVNZ OnDemand platform provides New Zealanders with online access to a wide range of high quality local and international content, free of charge, on their devices of choice. With hundreds of shows available to stream at any time, one of the big challenges is to help each viewer find the content best suited to their individual tastes. With Amazon Personalize, we were able to quickly generate and evaluate show recommendations and start seeing the value of using a managed service. Since then, we have rolled out Amazon Personalize at the core of our personalisation engine for TVNZ OnDemand, and by A/B testing each new personalisation feature, we have seen significant improvements in key viewer engagement metrics. At the same time we've reduced time and costs associated with supporting our legacy, custom built recommendation engine, freeing up our developers to focus on value add initiatives. The online viewer of today expects a personalised experience, and with Amazon Personalize we are now delivering on that expectation.”
Nathan Wichmann, Product Manager, TVNZ OnDemand
Cencosud is a multinational retail company, the largest retail company in Chile, and the third largest listed retail company in Latin America.
"Cencosud chose Amazon Personalize to optimize their online shopping experience for customers by recommending products that would boost user engagement. With Amazon Personalize, Cencosud was able to quickly develop a machine learning-based personalization solution capable of scaling across multiple types business lines leading to a 600% increase in click-through rates and a nearly 26% increase in average order value compared with their prior non-ML driven approach. The scalability and what could be achieved by using the service, as well as the option to test without having to develop large and expensive projects, led us to choose Amazon Personalize.”
Javiera Valenzuela Rivera, CRO Corporate Lead, Cencosud
Dress the Population makes luxury clothing created from premium materials that is attainable through its in-person and online stores while offering fair working conditions throughout its supply chain.
“Thinking that recommendation algorithms need months of learning before being effective, we were hesitant to invest in a machine learning solution. But with Obviyo Growth Bots and Amazon Personalize, we were able to quickly and cost effectively launch a high-quality recommendation engine. We’ve been able to dramatically improve the product discovery experience for our digital customers. Obviyo Recommend has exceeded my expectations. We went live a day after our first meeting and I have seen significant results. Within 72 hours of using Obviyo Recommend, revenue per visit was 350% higher for visitors who engaged with personalized recommendations. And after 14 days, we saw a 28% lift in conversions. From watching day-to-day progress, I can see how the Amazon Personalize algorithms are continually learning and improving results in near real-time.”
Shoshana Ritzle, VP Marketing and Creative, Dress the Population
Yelloh (formerly known as Schwan’s Home Delivery) delivers high-quality frozen foods directly to homes in 48 states, reaching more than 1.5 million customers and processing 7.5 million transactions annually.
“Over the past 70 years, we have developed a rich history of trusted relationships and customer connections. During our transformation into a modern, mobile retailer, we wanted to improve our services to meet our customers where they are — at the door or on their smartphone. Prior to working with AWS, our mobile retailer operations were ~50% ineffective. With Amazon Personalize, we are better positioned to suggest new food items customers might like, based on previous orders and like-buyer baskets. Coupled with Amazon Pinpoint and Amazon Connect to maximize sales and availability of when we can make food deliveries, we are making it easier and more efficient for shoppers to buy products. This increases brand loyalty and purchase orders. We ran a digital communications campaign and sent more than 100,000 personalized messages asking customers if they wanted certain food items delivered based on their unique preferences. We received 10,000 “yes” responses that represent ~$200 million in annual revenue and another ~$50 million in savings due to better delivery routes taken when customers gave “no” responses. We are now on pace to reduce 10 million miles a year. That’s true sustainability.”
Kevin Boyum, Chief Strategy Officer, Schwan’s Home Delivery/Yelloh
Lotte Mart is a subsidiary of Lotte Conglomerate, the leading retail company in Korea. It operates hypermarket, members-only warehouse discount outlets, electronics digital shops, and toysRus stores in Korea. It has 187 stores in Korea, Indonesia and Vietnam.
“By using Amazon Personalize, we have seen a 5x increase in response to recommended products compared to our prior big data analytics solution resulting in increased revenue per month. In particular, Amazon Personalize has increased the number of products that the customer has never purchased before up to 40%. The new recommendation service powered by AWS is the first of a much broader roll-out of AI technologies across our organization.”
Jaehyun Shin, Big Data Team Leader, Lotte Mart
Zola is the fastest growing wedding company in the country using design and technology to create the easiest wedding planning and registry experience for couples getting married today.
"At Zola, we develop innovative wedding planning tools to serve couples. We want to be there along the entire wedding journey and provide the best possible recommendations to our customers based on their style, interests, or preferences. Until now, those recommendations have been implemented via rule-based ranking, popularity, or, more recently, via a similarity model calculated offline. These methods were difficult to maintain and scale. Amazon Personalize provides us with state-of-the-art algorithms and an end-to-end personalization solution that enables us to respond to customer actions in real-time. Being a small team, using Amazon Personalize will allow us to quickly deliver solutions that would have otherwise taken a much larger team and several months' development time."
Stephane Bailliez, VP of Engineering, Zola.com
Pomelo Fashion is a leading omnichannel fashion brand based in Bangkok, Thailand, with a global customer base.
"Our goal is to be the best omnichannel company in Southeast Asia. We work relentlessly to make that dream a reality by constantly improving the customer experience at all stages through the shopping journey, both offline and online. We use Amazon Personalize to deliver a unique shopping experience to our many customers across the globe. Amazon Personalize allows us to seamlessly provide this personalization at scale. For Pomelo, Amazon Personalize is not just powerful but transformational in today’s e-commerce world!"
Paulo Almeida, Vice President of Engineering, Pomelo Fashion
BASE is an e-commerce platform in Japan hosting over 1 million online shops. Our mission is “Payment to the People, Power to the People.” We aim to empower individuals and small teams.
“We leverage Amazon Personalize to improve user experiences on our mobile app by recommending items for our users. Since we have a wide variety of products in the service, it is necessary to support our users in finding products that match their preferences. Recommending products on the first view while searching can reduce abandonment rates and improve customer lifetime value. When tested, Amazon Personalize outperformed our existing recommendation solutions by driving product page views up 56%. This drove key business outcomes while also accelerating time to value at a lower cost for our team."
Yusuke Saito, Machine Learning Group Manager, BASE Inc.
Marc O’Polo, one of the leading modern casual and sustainable lifestyle brands in the global premium segment, prides itself on being at the forefront of technical innovations. The company was looking for a way to give product recommendations to several hundred thousand customers subscribed to their newsletter campaigns.
“Amazon Personalize allows us to recommend popular or similar items based on our customers’ previous purchases. Since implementing Amazon Personalize to deliver personalized product recommendation emails, one third of transactions based on these newsletters contain at least one of the recommended products. Overall, we achieved a 56% improvement in product purchases as compared to our standard customer e-mails.”
Steffen Sandner, Director Digital Intelligence, Marc O’Polo
Ateam Inc. is a Japanese company with several lines of business including an online bicycle store called “cyma.”
“Our cyma store delivers fully assembled bicycles directly to customers’ doorsteps. Our growing business aims to be a leader in Japanese bicycle e-commerce, a goal that we’re aiming to achieve through our excellence in recommending products according to users’ personalized needs. We decided to use Amazon Personalize as a cost effective, highly compatible solution for our personalization needs. In addition to using the recommendation results from Amazon Personalize for our website, we plan to utilize the insights from Amazon Personalize in our sales flow. We are excited for upcoming features and services from Amazon Personalize and AWS.”
Masahiro Funakoshi, Director Vice President of Engineering, Ateam Lifestyle Inc.
GrocerApp is an affordable online supermarket that allows users to order grocery items for delivery. The company wanted to enable customers to quickly find the most relevant products and add them to their carts.
“We leveraged Amazon Personalize to provide product recommendations to customers on our apps using customer purchase data. With Amazon Personalize, we have achieved a massive 17% increment in the average order value, enabling us to fill customer orders immediately while increasing the overall basket size.”
Hassaan Sadiq, CTO, Co-founder, GrocerApp
Travel & Hospitality
Traveloka is Southeast Asia’s lifestyle super app that provides users access to discover and purchase a wide range of travel, local services, and financial services products. Traveloka has been downloaded more than 100 million times, making it the most popular travel and lifestyle booking application in the Southeast Asian region.
“Traveloka's mission is to fulfil the lifestyle needs and aspirations of customers across Southeast Asia. This has been driving our product development strategy for services ranging from accommodations to financial services and in particular for personalizing recommendations. We have experimented with multiple technologies in the quest to provide a seamless discovery experience of relevant services and offerings to Traveloka's customers – and scale in the process. We experimented with Amazon Personalize to recommend inventory for the Xperience product in the mobile app’s homepage feed. The result showed that Amazon Personalize delivered 13% and 66% better Click through-rate compared to other third party and existing in-house models respectively. Based on these results, Traveloka has now expanded use of Amazon Personalize to deliver personalized inventory recommendations across more products and services in Traveloka's app such as flights and hotels.”
Adi Alimin, VP Platform Products, Traveloka
Intuit is a business and financial software company that develops and sells financial, accounting and tax preparation software and related services for small businesses, accountants and individuals.
"With Amazon Personalize, we were able to quickly design and launch a recommendation engine for Intuit’s Mint budget tracker and planner app. Using customer profile and behavioral data, with machine learning, the service helps deliver the right financial offer to the right customer at the right time, based on their spending habits, lifestyle, and goals."
Qiang Zhu, Director of Data Science, Intuit
Founded in 2009, MoneySmart provides a financial comparison and content platform for consumers to make informed financial decisions. With over 400k users, 30 financial product categories, and 250 items as of 2023, their mission is to empower their customers to make smarter financial decisions.
“We explored the possibility of starting from scratch and building a new system but soon realized that development costs were high since we had a large amount of customer interaction data and a wide range of product category variations between our banking, insurance, and investment products. AWS had a compelling platform solution with Amazon Personalize, affording us a nice balance between self-service and customizable technology that could get us to market quickly. Leveraging Amazon Personalize, we were able to deliver the first version of our product recommendation feature live in less than 3 months, saving us money and time. Within the next 6 months, we were active in 2 countries and generated more than 11k applications increasing our application rate from 6.5% to 13.6% for signed in customers exposed to recommended products. 42% of our customers have been exposed to this new experience and we are seeing more customer interactions by showing them products they are interested in. We are positively contributing to our cross-sell capabilities on the MoneySmart platform.”
Prateek Baheti, Head of Technology, MoneySmart
Paytm is a digital payments, ecommerce, and financial services provider located in India. It supports over 17 million merchants and is used by millions of individuals daily offering full-stack payment and financial solutions.
Using Amazon Personalize to help customers discover relevant products, Paytm collects user data and runs it through the recommendations model to generate unique content suggestions for each of the over 10 million daily visitors to the Paytm Mall, their ecommerce service. As a result, Paytm saw a 6% conversion rate from its new personalized homepage, which is 3 times more than their previous item-to-item recommendation solution.
Shgardi is a mobile app startup company based in Saudi Arabia focused on providing affordable, on-demand food delivery services for over 2.5m consumers and 10k+ restaurants.
“At Shgardi, we see about 5,000 new users per day, yet had difficulty converting them to engaged, loyal customers. We understood the value in creating relevant communications and promotions, and began exploring new ways to create a more engaging user experience. Using Amazon Personalize, we targeted new and existing users by adding a “recommended for you” section to our app homepage. For new users, we leveraged data like location, time, and popular restaurants to provide curated recommendations. For existing users, we were able to use a mix of past engagement data like frequently visited restaurants to generate recommendations that fit their unique taste and personal choice. We also tuned certain recommendations based on specific business goals we had. The “recommended for you” feature enabled us to respond to changing user intent in real-time, and to evolve our recommendations to align with users tastes and preferences. As a result, we were able to increase the conversion of new users to buyers by 30% and increase the number of total monthly orders by 20%.”
Tarek Dahab, CTO/Co-founder, Shgardi
The Chefz is a Saudi-based online food delivery startup, founded in 2016. At the core of The Chefz’s business model is enabling its customers to order food and sweets from top elite restaurants, bakeries, and chocolate shops.
“Using Amazon Personalize, we are able to achieve personalization at scale across our entire customer base, which was previously impossible. During Ramadan, we were able to double the interactions on recommended restaurants compared to our legacy solution leading to increasing the conversion rate on recommended restaurants by 35%. Amazon Personalize enables us to apply context about individual customers and their circumstances, and deliver customized communications such as special deals and offers through our mobile application.”
Ramzi Alqrainy, Chief Technology Officer, The Chefz
ABLY is a hot Korean startup with a transformative approach to ecommerce and apparel. Using our mobile apps we bring celebrity style and fashion from Instagram into the hands of millions with about 2,000 daily product uploads.
"At ABLY, we are transforming the apparel industry with our approach to e-commerce. With more than 6 million app downloads, 300,000 unique daily active users, and $180M annualized GMV, we needed to rethink how we generate repeat purchases and increase cart size to continue our accelerated growth. At ABLY, we are now using Amazon Personalize in our front app page to create individualized recommendations for our customers based on their browsing and purchase history. The results are exceeding expectations and we are amazed at the speed and performance of the recommendation model. For startups like us with limited resources and capacity, Amazon Personalize is a breakthrough—enabling us to build sophisticated personalization capabilities with no prior machine learning experience."
Yujun Kim, CTO, ABLY
Refer to the developer guide for instructions on using Amazon Personalize.
Instantly get access to the AWS Free Tier.