Data-backed answers about American consumers, in Claude, ChatGPT, and more
Ask Faraday lets you ask questions about 240M+ US adults from the AI assistant your team already uses, compare any market to your own customers, and act on what you find.
Your best customers are a hypothesis. Make them a fact.
Ask a marketing team why their best customers are their best customers, and the answer you’ll usually get will be a hypothesis. It’s not an ill-informed one. But the questions that shape strategy still get answered with intuition or aggregated survey data.
What your customers do
- Clicks
- Visits
- Purchases
The behavioral data is all there. None of it tells you who those people actually are.
Who your customers are
- Who actually buys from us?
- What do they have in common that our prospects don’t?
- Is the market we’re about to enter full of people who look like them, or empty?
Closing the context gap is our mission, and Ask Faraday is a new place to start.Ask Faraday lets you ask questions directly of Faraday’s US consumer data, and your own customer data, from Claude, ChatGPT, or whichever AI assistant your team already uses. Use it to explore: form hypotheses, analyze markets, and discover insights. When you’re ready to engage every customer as the unique person they are, the Faraday platform gives you the individual-level context to do it.
From analyst project to a question you can type
An analyst project
For years, Faraday’s clients have relied on our team to answer who buys from them and where to find more of those people. That work drove real value, but it took analyst time and plenty of back-and-forth.
- Home services
A major home services company used Faraday’s analysis to identify its strongest markets and doubled down in them.
- High-end jewelry
A high-end jewelry brand relied on Faraday analysts to choose new store locations.
A question you can type
Ask Faraday lets anyone on your team do that work themselves. From the AI assistant they already use, they can ask a question, compare the answer to your customers, and act on what they find, without waiting on an analyst.
query_insightsAsk. Compare. Act.
1Ask
Any question about the US population, in plain language, from inside the assistant the team already uses (Claude, ChatGPT, Gemini, etc.).
Try household income by county, the ratio of women to men across the Northeast, or how many homes in a state were built before 1980.
Answers come from Faraday’s identity graph: more than 240 million US adults and their households, with 1,400+ curated attributes per person.
How many homes in Arkansas were built before 1980?✓query_insightsFaraday Identity GraphAbout 540,000 Arkansas homes were built before 1980, a bit over a third of the state’s housing.
Arkansas homes by year built
Before 196014%1960–197923%1980–199933%2000 or later30%2Compare
Ask the same kind of question about your own customers. Ask Faraday compares two groups and shows which traits one has more or less of: your customers against a market, leads against customers, or one-time buyers against repeat customers.
Knowing what sets your repeat customers apart tells you who is responding to your marketing, and who isn’t.
Connect your customer data the way that suits you: an easy CSV upload, your data warehouse, or a cloud bucket.
How are our repeat customers different from one-time buyers?✓query_insightsrepeat vs. one-time customersYour repeat customers are long-time homeowners, often in older homes. One-time buyers are far more likely to rent.
Repeat vs. one-time customers, % difference
Owner occupied+34%Home built before 1980+28%Same home 10+ years+22%Renter−47%3Act
The assistant that answers your questions also works with the rest of Faraday, so it can help you put findings to use right away.
Rank which one-time buyers are most likely to buy again with lead prioritization, build personas to tailor what you send each group, and learn more about each person from Faraday’s 1,400+ attributes.
When you’re ready, the same conversation can turn those insights into smarter customer lists and campaigns.
How can we turn more one-time buyers into repeat customers?✓query_insightsone-time buyersStart with one-time buyers who own older homes. They look most like your repeat customers, and 4,200 of them haven’t bought in a year.
Suggested next steps
- ✓Score one-time buyers on how likely they are to buy again
- ✓Build personas from repeat customers to shape each message
- ✓Send the top-scoring owners of older homes a spring offer
Real data about the people you serve, for teams of any size
Today, understanding your buyers and sizing a market usually means expensive, slow consumer research, or generic AI answers you can’t verify. Ask Faraday gives teams a way to build strategy on real data.
Marketing teams
Run recurring customer and lead analysis without waiting on an analyst.
Startups
Check big decisions against real data instead of instinct.
Strategy and corp dev
Size new categories or regions before moving into them.
Privacy built into the database, not bolted on
Ask Faraday rejects any question that could single out a person. Every result has to be backed by at least 50 distinct people. Faraday enforces that rule on every request at the database level, so it holds against a jailbroken assistant, a curious user, and even a bug in our own code.
- No person-level records
- Checked on every request
- Holds against jailbreaks
query_insights8,412 householdsHere’s the distribution for all 8,412 households in Bangor.
query_insights214 households214 households match. Most of them earn $60k to $100k.
query_insights1 householdThat question describes a single household. Every result has to represent at least 50 people, so the database rejected it before any result left.
“Faraday’s consumer dataset is painstakingly crafted from the world’s best permissioned sources, and we use it internally to make billions of predictions every day for thousands of brands. We asked ourselves: what if our users and their agents could run SQL queries against it? Ask Faraday was the answer.”
Andy RossmeisslCEO and co-founder, FaradayBring Faraday’s consumer data into your AI assistant
Existing Faraday clients can request access. New to Faraday? Request access and a context consultant will get in touch.
Frequently asked questions
What is Ask Faraday?
Ask Faraday lets you ask plain-language questions about American consumers and get answers from Faraday's data on 240+ million US adults and their households. You can also compare the market against your own customer base.
Which AI assistants work with Ask Faraday?
Ask Faraday works from inside the assistant your team already uses, including Claude, ChatGPT, and Gemini.
What kinds of questions can I ask?
You can ask about demographics, households, homes, and markets. Examples include household income by county, how many homes in a state were built before 1980, or how your customers differ from the broader market.
How does Ask Faraday protect consumer privacy?
Every result must be backed by at least 50 distinct people. The database itself enforces this rule, so a question narrow enough to single out one person is rejected. Requests for individual person-level records are refused outright.
Who is Ask Faraday for?
It's for marketing teams running customer and lead analysis, startups making early strategy decisions, and strategy and corporate development teams entering new categories or regions.
How do I get access?
Use the request button above.
How do I use Ask Faraday?
Ask Faraday is a subset of the tools available in Faraday's Enterprise MCP, namely describe_insights_schema and query_insights. Existing Faraday users can simply add the MCP to their assistant to get started.
What can I do with the insights I learn?
Faraday recommends using insights from this service to inspire powerful engagement across your business. The Faraday platform is built to deliver the individual-level context you need to target the right segments and personalize your outreach.
How do I get the context I need to target and personalize?
The same assistant you use for Ask Faraday—Claude, Gemini, ChatGPT, etc.—can configure your Faraday account for you, including connecting your data sources, building predictive models, and deploying consumer data, predictions, and more.