Question: How can I use machine learning to optimize my ecommerce campaigns and improve customer engagement?

If you want to fine-tune your ecommerce campaigns and use machine learning to better engage with customers, Bloomreach is a broad option. It marries real-time customer and product data with AI for personalized marketing, product discovery and content and conversational shopping. With email marketing, web personalization and ad optimization tools, Bloomreach automates SEO, product discovery and customer experience work across many channels.

Another good option is Dynamic Yield, which offers AI-powered personalization across many digital touchpoints. The platform includes features like audience discovery, content and offer personalization, product recommendations and customer engagement optimization. It spans many touchpoints, including the web, email, apps and ads, and is designed to help you create a personalized, continuous customer experience that can improve operations and revenue.

Nosto offers a Commerce Experience Platform that spans the entire shopping experience, using AI to personalize search, product recommendations and content. The company's real-time data engine and commerce-specific machine learning models produce actionable results, including higher average order value and online revenue. Nosto's interface is designed to be easy to use, and its integrations are designed to be seamless, making it a good choice for ecommerce experience management.

If you're looking for something more focused on cart abandonment and conversion, Metrical is worth a look. It uses real-time, anonymous data and machine learning to target and display personalized offers to keep customers from abandoning their carts and to maximize ecommerce revenue. With features like continuous campaign optimization and customizable reporting, Metrical helps retailers better understand their customers and communicate with them, resulting in higher conversion rates and loyalty.