Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, detecting fraudulent transactions, or even dynamically pricing products and services.
AWS observed the need of boosting customer happiness with data analytics and machine learning, so it specially invited Samuel from eCloudvalley to introduce three common patterns of customer data analytics and high-level implementation architecture in AWS Web Day.
Learn more about from the video 👉 https://hktw-resources.awscloud.com/aws-data-analytics-web-day-hong-kong/boosting-customer-happiness-with-data-analytics-and-machine-learning
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pricing machine learning 在 AppWorks Facebook 的最佳解答
eBay was founded in 1995, they used two decades of data and customer behavior insights to train its AI algorithms. In 2018, they hired Jan Pederson (formerly of Twitter and Microsoft, as vice president and chief scientist, artificial intelligence) to optimize their Artificial Intelligence and Machine Learning.
Here’s are few examples of how eBay uses AI and ML to boot its business.
Enhance search: By using AI to understand the context of a search and then provide relevant products. With computer vision, the buyers can use image search to find the items similar to the one they were looking at.
Optimize pricing and selling: ML can help the seller to identify the best prices, when to market themselves better to attract buyers.
Platform as a service: eBay provides AI-powered tools for sellers. They can use data, metrics and analytics information that managed on the platform to improve their selling business.
Machine translation: Languages would no longer be barrier between buyer and seller on eBay.
Augmented reality to simplify shipping: eBay came up with this reality technology on their app where the sellers can use the feature to find the optimal box for your shipping item.
With AI and ML, eBay was driving north of $1 billion per quarter in incremental marketplace sales.
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