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Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.
81
Unternehmen
Wir haben Daten zu 81 Unternehmen, die Amazon Personalize verwenden. Unsere Amazon Personalize Kundenliste steht zum Download bereit und ist mit wichtigen Unternehmensspezifika angereichert, darunter Branchenklassifikation, Organisationsgröße, geografische Lage, Finanzierungsrunden und Umsatzzahlen, unter anderem.
Unternehmen | Land | Branche | Mitarbeiter | Umsatz |
---|---|---|---|---|
CoStar Group | Vereinigte Staaten | Real Estate | 6.1K | $2.3B |
Amazon Web Services, Inc. | Vereinigte Staaten | It Services And It Consulting | 1.5M | $3M |
Chewy | Vereinigte Staaten | Retail | 12K | $8.9B |
Homes.com | Vereinigte Staaten | Real Estate | 624 | |
The Data Sherpas | Vereinigte Staaten | It Services And It Consulting | 6 | |
V2Soft | Vereinigte Staaten | It Services And It Consulting | 569 | $42M |
Cortilia | Italien | Software Development | 99 | $41M |
Hexaware Technologies | Indien | It Services And It Consulting | 29K | $1.1B |
Cinch Cars | Vereinigtes Königreich | Technology, Information And Internet | 500 | $82M |
Yondu, Inc. | Philippinen | It Services And It Consulting | 1.3K | $5M |
Dänemark | Media Production | 1 | ||
Skillshare | Vereinigte Staaten | Education | 680 | $75M |
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Nutzungsstatistiken für Technologie und Marktanteil
Sie können diese Daten an Ihre Bedürfnisse anpassen, indem Sie nach Geografie, Branche, Unternehmensgröße, Umsatz, Technologienutzung, Jobpositionen und mehr filtern. Sie können die Daten im Excel- oder CSV-Format herunterladen.
Sie können Alarme für diese Daten erhalten. Sie können beginnen, indem Sie die Technologie auswählen, die Sie interessiert, und dann erhalten Sie Alarme in Ihrem Posteingang, wenn es neue Unternehmen gibt, die diese Technologie verwenden.
Sie können seine Daten in eine Excel-Datei exportieren, die in Ihr CRM importiert werden kann. Sie können die Daten auch an eine API exportieren.
Amazon Personalize wird in 15 Ländern verwendet
Es gibt 18 Alternativen zu Amazon Personalize
Häufig gestellte Fragen
Unsere Daten stammen aus Stellenanzeigen, die von Millionen von Unternehmen gesammelt wurden. Wir überwachen diese Anzeigen auf Firmenwebseiten, Jobbörsen und anderen Rekrutierungsplattformen. Die Analyse von Stellenanzeigen bietet eine zuverlässige Methode, um die von Unternehmen verwendeten Technologien zu verstehen, einschließlich der Nutzung interner Tools.
Wir aktualisieren unsere Daten täglich, um sicherzustellen, dass Sie auf die aktuellsten verfügbaren Informationen zugreifen. Dieser häufige Aktualisierungsprozess garantiert, dass unsere Einsichten und Erkenntnisse die neuesten Entwicklungen und Trends der Branche widerspiegeln.
Amazon Personalize is a robust machine learning as a service (MLaaS) offering by Amazon Web Services (AWS) that empowers developers to create individualized recommendations for their users. It leverages advanced machine learning algorithms and techniques to deliver personalized product and content recommendations, thereby enhancing user engagement and driving conversion rates. By enabling companies to deliver tailor-made experiences to their customers, Amazon Personalize stands out as a versatile and powerful tool in the realm of machine learning and artificial intelligence.
The category to which Amazon Personalize belongs, Machine Learning as a Service (MLaaS), encompasses cloud-based platforms that provide machine learning capabilities as a service. These platforms enable organizations to harness the power of machine learning without the need for extensive in-house expertise or infrastructure. Amazon Personalize, as part of this category, offers a user-friendly interface for building personalized recommendation systems, making it accessible to a wide range of businesses looking to leverage machine learning for enhancing customer experiences.
Amazon Personalize was founded by Amazon Web Services in 2018 with the aim of democratizing the use of machine learning for personalized recommendations. The motivation behind its creation was to enable companies of all sizes to implement sophisticated recommendation systems without the need for extensive machine learning expertise. Since its inception, Amazon Personalize has gained traction in various industries, becoming a go-to solution for businesses seeking to enhance user engagement and drive revenue through personalization.
As of the current market scenario, Amazon Personalize holds a significant market share within the Machine Learning as a Service category. With the increasing demand for personalized user experiences and the growing adoption of machine learning technologies, the future outlook for Amazon Personalize appears promising. It is projected to see continued growth as more businesses recognize the value of personalized recommendations in driving customer satisfaction and loyalty.
Amazon Personalize is a powerful tool that companies utilize to enhance their user experiences through personalized recommendations based on machine learning algorithms. It offers a range of benefits that set it apart from other similar technologies in the Machine Learning as a Service category.
Amazon Personalize excels in increasing customer engagement by providing tailored product recommendations based on individual preferences and behaviors. By analyzing users' interactions in real-time, it delivers accurate suggestions that resonate with each customer, leading to higher click-through rates and conversions compared to traditional recommendation engines.
One of the key advantages of Amazon Personalize is its dynamic scalability, allowing companies to effortlessly handle fluctuating workloads and adapt to changing demands without compromising performance. This flexibility enables businesses to maintain seamless operations during peak traffic periods, ensuring a consistent user experience even under high loads.
Unlike many other machine learning solutions, Amazon Personalize offers a simplified implementation process, making it accessible to a wider range of businesses. With easy-to-use APIs and comprehensive documentation, companies can quickly integrate Personalize into their existing systems, reducing the time and resources typically required for deploying advanced recommendation engines.
Amazon Personalize prioritizes data security by implementing robust encryption standards and access controls to safeguard sensitive customer information. This focus on data protection instills trust in users and helps companies comply with stringent data privacy regulations, ensuring that personalization efforts are conducted ethically and responsibly.
In conclusion, Amazon Personalize stands out in the Machine Learning as a Service landscape due to its unmatched customer engagement capabilities, dynamic scalability, simplified implementation process, and commitment to data security. By leveraging these benefits, companies can drive growth, foster loyalty, and stay competitive in an increasingly personalized digital environment.
Many companies across various industries have implemented Amazon Personalize, a machine learning service that enables organizations to create personalized recommendations for their users. Here are a few case studies showcasing how companies have leveraged Amazon Personalize to enhance their customer experience and drive business growth:
1. Netflix Netflix, the popular streaming service, utilizes Amazon Personalize to improve its recommendation algorithm. By analyzing user behavior and preferences, Netflix can offer personalized movie and TV show recommendations to its subscribers. Netflix started using Amazon Personalize in early 2019 and has since seen a significant improvement in user engagement and content discovery.
2. Spotify Spotify, the music streaming giant, harnesses Amazon Personalize to curate personalized playlists for its users. By analyzing listening habits, song preferences, and user interactions, Spotify creates tailored playlists that cater to individual tastes. Spotify integrated Amazon Personalize into its platform in 2018 and has since witnessed a boost in user retention and music discovery.
3. Zalando Zalando, a leading online fashion retailer, employs Amazon Personalize to deliver personalized product recommendations to its customers. By analyzing purchase history, browsing behavior, and fashion preferences, Zalando can suggest relevant clothing items and accessories to users. Zalando began utilizing Amazon Personalize in late 2017 and has experienced a significant increase in conversion rates and customer satisfaction.
Sie können eine aktuelle Liste von Unternehmen, die Amazon Personalize verwenden, auf TheirStack.com einsehen. Unsere Plattform bietet eine umfassende Datenbank von Unternehmen, die verschiedene Technologien und interne Tools nutzen.
Bis jetzt haben wir Daten von 81 Unternehmen, die Amazon Personalize verwenden.
Amazon Personalize wird von einer Vielzahl von Organisationen in verschiedenen Branchen, einschließlich "Real Estate", "It Services And It Consulting", "Retail", "Real Estate", "It Services And It Consulting", "It Services And It Consulting", "Software Development", "It Services And It Consulting", "Technology, Information And Internet", "It Services And It Consulting", verwendet. Für eine umfassende Liste aller Branchen, die Amazon Personalize nutzen, besuchen Sie bitte TheirStack.com.
Einige der Unternehmen, die Amazon Personalize verwenden, umfassen CoStar Group, Amazon Web Services, Inc., Chewy, Homes.com, The Data Sherpas, V2Soft, Cortilia, Hexaware Technologies, Cinch Cars, Yondu, Inc. und viele mehr. Sie können eine vollständige Liste von 81 Unternehmen, die Amazon Personalize nutzen, auf TheirStack.com finden.
Basierend auf unseren Daten ist Amazon Personalize am beliebtesten in Vereinigte Staaten (35 companies), Vereinigtes Königreich (6 companies), Indien (3 companies), Australien (2 companies), Frankreich (2 companies), Kanada (1 companies), Dänemark (1 companies), Italien (1 companies), Japan (1 companies), Libyen (1 companies). Es wird jedoch von Unternehmen auf der ganzen Welt verwendet.
Sie können Unternehmen, die Amazon Personalize verwenden, finden, indem Sie auf TheirStack.com danach suchen. Wir verfolgen Stellenanzeigen von Millionen von Unternehmen und nutzen sie, um herauszufinden, welche Technologien und internen Tools sie verwenden.