Faraday - AI-powered customer behavior prediction platform

What is Faraday

If you've ever tried to predict which customers will buy, churn, or respond to your marketing, you know how complex it gets. Customer data lives in multiple systems, building accurate prediction models requires specialized ML expertise, and deployment can take months. That's exactly the problem Faraday was built to solve.

Faraday is an end-to-end customer behavior prediction platform that helps you predict any customer action—conversion, churn, purchase likelihood, repeat purchase readiness—without needing a data science team or months of model development. What makes Faraday different is its built-in consumer database: 1,500+ attributes covering 240 million US adults, giving you a head start even with minimal first-party data.

You can use Faraday in two ways. The no-code approach lets you point-and-click your way to predictions through pre-built templates. Or if you're a developer, the API-first architecture lets you integrate predictions directly into your existing workflows. This flexibility means marketing teams can self-serve predictions while engineering teams get programmatic access.

The scale speaks for itself: over 880 billion predictions have been deployed through Faraday in the past 30 days alone (87,662,754,513 to be exact), serving thousands of brands and platforms across industries. Whether you're a DTC brand, a marketing agency, or an enterprise, Faraday handles the ML complexity so you can focus on acting on the insights.

Security and compliance aren't afterthoughts—they're foundational. Faraday maintains SOC 2 Type II certification (audited since 2020), is compliant with CCPA, HIPAA, GDPR, and 17 US state privacy laws, and processes all data within US borders. Every employee who handles customer or consumer data passes a background check through Checkr.com.

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Core Features of Faraday

What can Faraday actually do for your business? Let's break down the capabilities that make customer prediction accessible to teams without ML expertise.

Customer Behavior Prediction is the core of what Faraday does. You can predict any customer action—conversion propensity, churn risk, purchase likelihood—by leveraging hundreds of specially-tuned gradient boosted tree (GBT) ensembles. These aren't one-size-fits-all models; Faraday selects the best model for each inference. The Lead Prioritization template, for example, has demonstrated a 94% conversion rate in real deployments.

Identity Graph gives you access to Faraday's built-in consumer database: 240 million US adults with 1,500+ attributes. You can match against this data using SHA-256 hashed emails, or plain text name/address/phone/email combinations. This is incredibly valuable for cold-start scenarios or enriching sparse customer records. One customer, Hazel, told us this feature saved them months of engineering time and six figures in data licensing costs.

Dynamic Prediction means Faraday automatically selects the best model ensemble based on where the customer is in their lifecycle. A long-term customer and a brand-new lead require different prediction approaches, and Faraday handles this automatically.

First-Party Feature Engineering automatically extracts time, frequency, and value-based projection features from your customer data. You bring your data, Faraday makes it prediction-ready.

Responsible AI is built into the platform with bias detection and mitigation, model explainability, and cross-validation. You get predictions that are fair, transparent, and compliant.

Transparent Reporting gives you everything from executive summaries to technical deep-dives, including feature importance with directional indicators and full performance reports.

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Who Uses Faraday

Faraday serves teams across industries who need to predict customer behavior without building ML infrastructure from scratch. Here are the most common use cases.

Lead Prioritization is ideal for sales teams overwhelmed with leads but lacking data to prioritize them. Faraday predicts which leads are most likely to convert, letting your team focus on the highest-value prospects. One customer achieved a 94% conversion rate and reported 22x monthly ROI after implementing lead prioritization.

Next Best Offer solves the challenge of knowing what product or service to recommend to each customer. Instead of generic recommendations, you get predictions of what each individual is most likely to purchase next.

Adaptive Discounting helps you move beyond one-size-fits-all promotions. By predicting customer lifetime value (LTV), you can tailor discount offers to each customer's predicted worth. One use case demonstrated a $1,879 predicted LTV for targeted customers.

Thematic Personalization lets you customize messaging and creative content based on predicted customer personas. Bee's Wrap, for instance, used this to power personalized campaigns that supported their partnership with 550 Target stores.

Repeat Purchase Readiness identifies which existing customers are most likely to buy again. A marketing agency client achieved a 17% improvement in repeat purchases after implementing this use case.

Lead Rejection is critical for high-cost industries like home services, where pursuing low-quality leads wastes significant resources. One home services brand uses Faraday to pre-identify and reject low-value leads, saving over $100,000 per month.

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Technical Features

For teams that want to understand the engineering behind the predictions, here's how Faraday works under the hood.

Dynamic GBT Ensembles form the core of Faraday's prediction engine. Instead of a single model, Faraday uses hundreds of specially-tuned gradient boosted tree ensembles. For each inference, it automatically selects the optimal model based on the prediction context—your data, your use case, and the customer's lifecycle stage.

Built-in Consumer Data gives you a massive head start. The database covers 240 million US adults with 1,500+ attributes including demographics, purchasing behavior, lifestyle indicators, and more. All features are fully normalized before training and inference, eliminating the data preparation headaches typical of ML projects.

Real-time and Batch Inference lets you choose based on your business needs. Need instant predictions for website visitors? Use the real-time API. Running weekly campaigns? Batch processing is more cost-effective.

Data Integration supports the tools you already use. Connect Snowflake, BigQuery, PostgreSQL, Amazon S3 (CSV files), or upload via API. On the output side, deploy predictions through Zapier automations or directly into your applications via REST API.

Security Architecture meets enterprise compliance standards. Faraday maintains SOC 2 Type II certification (with annual audits from Wipfli covering 2020-2025), undergoes HackerOne penetration testing and bug bounty programs, and processes all data exclusively within US borders. Every employee who handles consumer or customer data passes a Checkr.com background check. The platform is compliant with CCPA, HIPAA, GDPR, and 17 US state privacy laws.

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Ecosystem and Integration

Faraday is designed to fit into your existing technology stack, not replace it. Here's how it connects with the tools your team already uses.

Data Sources supported include Snowflake, Google BigQuery, PostgreSQL, Amazon S3 (for CSV uploads), and direct API uploads. If your data lives in one of these platforms, integration is straightforward.

Deployment Targets include Zapier for no-code automation and REST APIs for programmatic integration into any application. Whether you're a marketer setting up automated workflows or an engineer building custom prediction endpoints, Faraday meets you where you are.

Developer Resources are robust and growing. The GitHub organization (github.com/faradayio) provides SDKs and examples. The Discord community (discord.gg/gzAjCNPrYa) is active with fellow users and Faraday team members. Documentation is comprehensive at faraday.ai/docs, and the API reference at faraday.ai/docs/reference has everything developers need.

Template Center offers pre-built configurations for common use cases: lead prioritization, next best offer, adaptive discounting, churn prediction, and more. These templates dramatically reduce time-to-value since the model configuration is already optimized for each scenario.

Industry Coverage spans DTC brands, marketing agencies, home services, call centers, financial institutions, and insurance companies. This breadth demonstrates Faraday's versatility across business models and customer interaction patterns.

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Frequently Asked Questions