Data Appends - Docs

Faraday's Data Appends service enables businesses to enrich their existing customer data with high-quality third-party attributes from the Faraday Identity Graph. By filling gaps in your data, you can refine targeting, enhance marketing efforts, and make smarter, data-driven decisions. This feature integrates seamlessly with your existing systems, offering enriched data that is privacy-compliant, rigorously vetted, and ready for use in exploratory research, to complement an existing dataset, or even to improve the accuracy of your own predictive models.

This documentation will guide you through how to use Faraday's Data Appends service, including selecting attributes, matching them to your existing customer data, and integrating the enriched data into your workflows.

The Faraday Identity Graph and its role in Data Appends

Faraday’s data appends are powered by the Faraday Identity Graph. A rich proprietary third party data set, which contains over 1,500 attributes on 240 million adult consumers, covering demographics, property ownership, life events, and financial indicators, sourced from reputable data brokers and public records.

Visit our Traits documentation page or learn more about the FIG.

Do I need Data Appends to use Faraday’s predictive models

No, you do not need data appends to leverage Faraday’s internal predictive capabilities. The Faraday Identity Graph (FIG) is a core component of our platform and is seamlessly integrated into all customer models to improve segmentation and predictive outcomes by default, from day one.

Every Faraday user benefits from our internal data appending process, which enhances customer records with FIG attributes to improve model accuracy, enrich segmentation, and optimize predictions. This process happens automatically within our platform, ensuring that your models are always powered by the most relevant third-party data.

Data appends is only necessary for users who want to export raw FIG data for use outside of Faraday—whether for external analysis, direct marketing efforts, or other applications beyond our predictive modeling framework. If you're interested in how FIG data is applied within Faraday, visit our Traits documentation to learn how we incorporate these enriched attributes into our predictive models by default.

Types of available traits

Traits within FIG can generally be broken into two categories: property and consumer.

Property Traits in FIG come from sources like tax assessor offices and can vary by geographic region. These traits include information such as property type or heating system, which can be used to target specific homeowner segments.

Consumer Traits include demographic, financial, and lifestyle attributes derived from sources like surveys, public records, and non-cash transaction data. These traits are key for understanding customer behavior and improving marketing outreach.

Key use cases

Faraday’s Data Appends can be used to address a variety of business needs, including the following examples:

Exploratory research: Supplement your existing data for targeted market analysis and deeper insights.
Supplementing existing datasets: Fill in missing information like phone numbers or addresses to enable direct mail and call center outreach.
Powering custom predictive models: Use Faraday’s structured data to improve machine learning models by enhancing customer profiles and predictive outcomes.

How it works

Step 1: Select attributes

Select the third-party data attributes that align with your business needs. These could include:

Demographic data (e.g., income, household size)
Geographic data (e.g., location-specific behaviors)
Behavioral data (e.g., purchasing patterns, life events)

Step 2: Match & append

Faraday will match the selected attributes with your existing customer records using ai identity resolution software, ensuring the data integrates seamlessly and enriches your customer profiles.

Step 3: Integration

The enriched data is delivered in a structured, ready-to-use format. You can easily integrate this data into your systems or predictive models.

Why use Faraday’s Data Appends?

Faraday’s Data Appends offer several advantages over sourcing data independently:

Contracting simplicity: Faraday handles all vendor negotiations and upfront commitments, ensuring a smooth and efficient process.
Security compliance: All data is handled in accordance with privacy laws, ensuring full compliance with regulations like GDPR, CCPA, and SOC-2.
No data science overhead: Raw third-party data requires significant processing, feature selection, and bias mitigation. Faraday’s data is already cleaned, structured, and ready for immediate use, saving you valuable time and resources.

Trait currency

Faraday receives updated data from our data partners on varying schedules, but FIG is generally updated every 6-8 weeks. It should be noted that this does not mean that every record within FIG is updated with each installment. Here’s an example of a recent update from last year.