Faraday is a customer context platform designed to provide AI agents and workflows with rich, on-demand data for personalized customer experiences. It offers context on 240 million U.S. adults through multiple deployment methods: MCP (Model Context Protocol), real-time API, and batch file append. Users can select from over 1,400 consumer and identity data points sourced from top compilers to build custom payloads. The platform includes predictive capabilities such as propensity to convert, next best offer, and persona clustering, which are powered by bespoke machine learning models that can be automatically trained on user data.
Key features include the Faraday Identity Graph (FIG v2), which has been overhauled for improved accuracy and performance. The platform integrates seamlessly with major data warehouses, cloud providers, and marketing tools, enabling continuous deployment across the tech stack. Use cases range from lead scoring and customer profile enhancement to personalized marketing campaigns. For example, jewelry brand John Hardy uses Faraday to instantly enhance customer profiles, while American Standard achieved a 3x higher margin by prioritizing leads with high Faraday scores. Subscription brand Bespoke Post saw a 5x ROI, 5% lift in revenue per customer, and 3% reduction in churn by scoring customer traits against product attributes.
Technical details: Faraday provides expert-level context through predictions and segments. Users can compare segments, build personas, and access detailed reporting. The platform is built for scalability and ease of use, with a focus on delivering actionable insights. Pricing is usage-based, with options for API calls, data points, or batch deployments. Faraday is ideal for businesses seeking to engineer delightful customer experiences by combining identity, consumer data, and predictions into their engagement workflows.
AI agents, marketing teams, data scientists, customer experience teams, e, commerce brands, lead scoring teams, personalization engineers
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