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Faraday

—Predict customer behavior with AI-powered insights.

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March 21, 2023

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Faraday

Customer analysis

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Predict customer behavior with AI-powered insights.

Overview

Overview Releases Pricing Reviews Prompts Pros & Cons Q&A Alternatives Recommendations

Customer analysis49 0

API Data-Driven Decision Making Predictive Business Strategy Customer Behavior Analysis Customer Engagement Prediction Algorithms

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Faraday is an AI-driven platform that focuses on predicting customer behavior. It integrates with existing business stack to facilitate data-driven decision making, with a specific emphasis on predicting customer engagement and behavior.

Features of the platform include built-in consumer data capabilities, stack integrations, AI safety, developer-ready API, and deployment options for both private and public cloud.

The platform collects customer-related data to generate a comprehensive understanding of consumer behavior; such data can range across over 1500 consumer attributes.

Faraday uses different types of prediction algorithms like GBT and GenAI to forecast a customer's next action, potential spend, churn prediction, and more.

Biases that might be present in the model are identified and handled, fostering fairness, and explainability in AI predictions. Faraday also emphasizes security and privacy, including compliance with SOC-2, NIST 800-53, CCPA, HIPAA, and more.

The goal of the tool is to empower businesses to make insightful decisions, improve customer engagement and ultimately, enhance their predictive business strategy.

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Initial release

February 4, 2021

Initial release of Faraday.

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Customer analysis Faraday

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Faraday was manually vetted by our editorial team and was first featured on March 21st 2023.

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Pros and Cons

Pros

Free starting option

No coding skills required

Customer behavior prediction

Developer-friendly API

Consumer data processing

Stack integration

Built-in prediction algorithms

Deployment on private/public cloud

Faraday's Cookie usage for functionality

Over 1500 consumer attributes

Built-in bias mitigation

SOC-2, NIST 800-53, CCPA, HIPAA compliance

Intuitive prediction guidance

Secure user data handling

Powerful, ergonomic API

Identity resolution for accuracy

Secure hosted option

Various deployment options

Tools to correct bias

Predictive features for software teams

Browse included traits

Adaptive discounting feature

Content personalization

First best offer prediction

Lead scoring tool

Rep assignment option

Churn scoring tool

Predicts next best offer

Repeat purchase scoring

Tools for customer data source

Various deployment destinations

Easy to build prediction recipes

Zapier integration

Great customer engagement support

Facilitates data-driven decision making

Privacy assured with legal compliance

Handles various consumer attributes

Facilitates consumer data understanding

Enhances predictive business strategy

Robust customer behavior prediction

Ensures secure data infrastructure

Secures customer marketing data

Facilitates personalized customer experiences

Improves stack data predictions

Predicts potential customer spend

Detects potential customer churn

Flags biased historical data

View 42 more pros

Cons

Shares user data with partners

No API documentation provided

Limited to 1500 data attributes

Requires site cookies

Doesn't have free tier

Limited built-in bias mitigation

View 1 more cons

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Q&A

What is Faraday?

Faraday is a customer prediction platform powered by artificial intelligence. It is designed to aid businesses in predicting customer behavior, all without requiring any coding or data science skills. Faraday can be integrated seamlessly with existing business stacks, enhancing data-driven decision-making processes. It provides insightful projections on customer engagement and behavior using varied prediction algorithms.

What are the key capabilities of Faraday?

Faraday's key capabilities include predicting customer behaviour, using a developer-friendly API, facilitating data-driven decision making, processing consumer data, integrating with the existing business stack, ensuring AI safety, and deploying either on private or public cloud. It uses varied prediction algorithms for accurate forecasting and mitigates any biases in the model to promote fairness. The platform also complies with multiple security and privacy regulations for maximum data protection.

Is coding or data science knowledge necessary to use Faraday?

No, a user does not need any coding or data science knowledge to use Faraday. The platform is designed to be easy-to-use and non-technical professionals can operate it seamlessly.

How does Faraday use cookies?

Faraday employs cookies to enhance site functionality, assess its usage, and assist in marketing activities. It tracks user interactions with the website and shares this information with marketing and analytics partners, which can then be combined with other details that the user has provided or gathered from other services.

What are the categories of cookies used by Faraday?

Faraday classifies its cookies into three categories: necessary, preference, and statistic. 'Necessary' cookies enable basic website functionalities and secure access. 'Preference' cookies retain user preferences such as language or region to customise the user experience. 'Statistic' cookies gather and report anonymous user data to provide insights on website interaction.

What is the role of AI in Faraday?

AI is pivotal to Faraday's functionality. Artificial Intelligence is harnessed by Faraday to predict customer behavior, allowing businesses to build powerful predictive experiences. The AI drives the algorithm for the customer behavior prediction features of Faraday.

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How does Faraday predict customer behavior?

Faraday predicts customer behaviour by collecting and analysing a plethora of customer-related data to build a comprehensive understanding of consumer behaviour. This data might range across over 1500 consumer attributes. Faraday then uses dynamic prediction algorithms like GBT and GenAI to forecast a customer's possible next action, prospective spend and more.

How does Faraday's prediction algorithms like GBT and GenAI work?

Faraday's prediction algorithms like GBT (Gradient Boosting Trees) and GenAI function by analysing a wide range of data to predict customer behaviour. However, concrete technical details on these algorithms' specific operations, beyond general machine learning principles, are not directly provided.

Can Faraday help me with churn prediction?

Yes, Faraday is capable of helping with churn prediction. It provides insights into customer behavior, potential actions, and spend, which allow businesses to anticipate and address churn before it occurs.

How does Faraday handle biases in its model?

Faraday deals with biases in its model by incorporating built-in bias mitigation procedures. These procedures identify potential biases that may skew the AI's predictions and treat them appropriately to foster fairness and transparency.

What are the security and privacy measures implemented in Faraday?

Security and privacy are front and center in Faraday. It meets compliance standards such as SOC-2, NIST 800-53, CCPA, and HIPAA. While the specific security mechanisms implemented are not explicitly mentioned, adherence to these standards implies measures such as encryption, access control, network security, and comprehensive data protection strategies.

How does Faraday enhance predictive business strategy?

Faraday enhances predictive business strategy by providing companies with insightful forecasts about their customers. By examining vast ranges of consumer data and using AI to interpret patterns and predict behavior, Faraday empowers businesses to make informed decisions, improve customer engagement and boost their predictive strategizing.

What are the functions included in the developer-friendly API?

The developer-friendly API of Faraday allows businesses to build and rapidly deploy features related to the prediction of customer behavior. Specific functionalities offered by the API are not explicitly detailed.

What are the deployment options for Faraday?

Faraday offers flexible deployment options. It can be used on Faraday's secure hosted platform or launched on a company's private cloud, accommodating various business needs.

How does Faraday's stack integration feature work?

Faraday's stack integration feature integrates with the existing systems of a business, ensuring that predictions are incorporated where and when they're needed. Faraday works in harmony with your current stack, from cloud services to CRM tools, resulting in an efficient and unified system.

Can Faraday be integrated with other business tools I already use?

Yes, Faraday can be seamlessly integrated with existing business tools. In fact, it has built-in integrations for platforms such as Google Cloud, AWS, Azure, Snowflake, Shopify, Salesforce, Klaviyo, and HubSpot, ensuring synchronization and harmony with your current infrastructure.

How does Faraday process consumer data and what does it include?

Faraday processes consumer data by collecting a wide variety of information on user behaviour that spans over 1500 consumer attributes. This could include demographic information, online activity, purchase history, and more - depending on data sources and the specific application.

What is Faraday's stand on explainable AI?

Faraday prioritizes explainable AI by providing built-in bias mitigation mechanisms and explaining their AI's predictions frothily. It is committed to fostering transparency and understanding in the predictions it generates, making sure businesses understand the why and how behind each prediction.

What regulatory compliance does Faraday adhere to?

Faraday adheres to multiple data security and privacy standards such as SOC-2, NIST 800-53, CCPA, and HIPAA. These frameworks guide policies on data security, privacy, access control, auditing, and more, reinforcing Faraday's commitment to secure and privacy-conscious AI solutions.

How can Faraday help improve my customer engagement?

Faraday can significantly contribute to enhancing customer engagement by precisely predicting customer behavior. Its ability to forecast potential customer actions, spending, and churn allows businesses to engage with their customers in a proactive, individualized, and timely manner. The result is increased customer satisfaction, loyalty, and business growth.

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