Q&A

Create accurate predictions, eliminate guesswork, and create magical customer experiences with Mage.

Using machine learning and artificial intelligence to integrate product recommendations gives the most accurate predictions for successful advertising, eliminates guesswork in creating campaigns, and creates magical customer experiences. 

Using machine learning (ML) to battle “Nigerian princes,” hackers, and customers abusing chargeback requests in order to reduce unnecessary losses.

Creating measurable strategies to ensure customer retention, and taking data-driven actions to prevent churn, is key to thriving in the ever-growing, competitive ecommerce market.

Why aren’t prospects doing what we want? Figure out how we can use ML to show viewers what they’re searching for and get them to buy immediately.

Youtube's recommendation algorithm offsets the need for search as it delivers users a personalized ranking of relevant videos on their feeds.

ML tools make it possible to predict and prevent churn before it occurs. Churn prediction is used to identify areas of improvement and maintain happy customers.

Ranking is a type of machine learning that sorts data in a relevant order. Companies use ranking to optimize search and recommendations.

Deploying methods of deep learning, AI, and ML, Pinterest is able to customize every user experience, maintaining their high engagement and retention.

Amazon's use of artificial intelligence (AI) and machine learning (ML) has led to its success as a retail giant and to provide exceptional customer experience.