How to Predict Marketing Performance with No-Code AI from Faraday
Want to actually use AI to attract, engage, and retain customers, without having to code?
Faraday is a no-code AI platform that makes consumer predictions at scale.
The tool's machine learning creates predictive models that marketers can use to predict cross-sell and up-sell opportunities, as well as churn.
We spoke with Faraday VP, Marketing Danielle Rand to learn more about how this AI-powered solution works.
In a single sentence or statement, describe Faraday.
Faraday is a consumer prediction platform that empowers marketers at direct-to-consumer brands to deliver personalized and predictive customer experiences with responsible, no-code AI at scale.
How does Faraday use artificial intelligence in its products?
Faraday uses a combination of unified, cookieless third-party data and our proprietary machine learning pipeline to create predictive models for brands to help attract, engage, and retain high-value customers.
We do this all without using cookies and without bias in our models.
What are the primary marketing use cases for your AI-powered solutions?
We have several:
- Customer insights and segmentation.
- Audience management on paid search and social.
- Lead management.
- Predict cross-sell, up-sell, churn, retention.
What makes your AI-powered solution smarter than traditional approaches and products?
- AI-driven recommendations. Marketing-accessible, no-code AI to generate predictive models that optimize for performance.
- Real-time data capture and activation in the tools you already use. Capture and score changes in product purchasing, customer, lead score, subscription behavior etc., in your CRM, ESP, Marketing Hub so you never miss a beat.
- Unified, cookieless data model. Unification of first-party customer data with cookieless, third-party data (FIG™) to know your customers better than ever before.
Are there any minimum requirements for marketers to get value out of your AI-powered technology? (e.g. data, list size, etc.)
They must sell a consumer product or service, and have access to Personal Identifiable Information (PII) defined as: any representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.
For Faraday this means, at minimum, access to an email address—and email and home address is even better.
Who are your ideal customers in terms of company size and industries?
Direct-to-consumer brands with 100+ employees, ideally five-to-seven person marketing team minimum, digital-first marketing strategy, and have some kind of CRM, ESP, data warehouse etc.
What do you see as the limitations of AI as it exists today?
AI feeds on high-quality data. Insufficient amounts of data or poor quality data will lead to poor results from any kind of AI solution implemented.
As we move more towards a cookieless world and we see the end of the third-party cookie soon, brands will need to be hyper-focused on how to continue collecting and responsibly managing customer data.
Brands will need to seek solutions that blend a unique combination of responsibly sourced cookieless third party data with fair and unbiased machine learning algorithms to fuel their predictive marketing efforts.
What do you see as the future potential of AI in marketing?
Predictive marketing is the perfect marriage between machine learning and human intelligence. The beauty of it is I think marketers will be able to have better one-to-one relationships with their customers, but do it at enterprise scale.
Any other thoughts on AI in marketing, or advice for marketers who are just getting started with AI?
It's never too early to get started.
About Paul Roetzer
Paul Roetzer (@paulroetzer) is founder and CEO of PR 20/20, author of The Marketing Performance Blueprint and The Marketing Agency Blueprint, and creator of The Marketing Artificial Intelligence Institute and Marketing Score. Full bio.