For Analytics Teams
Analytics teams don’t just need more data. They need to know whether the signal is right, and what the business should do with it.
Facteus gives your team credit card transaction data you can explore, validate, integrate, and model – plus analyst-ready intelligence that gets you from business question to confident answer faster.
Why did sales move? Is it happening across the category? Which competitor is gaining? Is this signal strong enough to change the forecast?
Analytics sits between the business question and the decision that follows. Which means getting the answer quickly is only half the job. You also need to know where it came from, whether you can reproduce it, and whether it holds up under scrutiny.
Facteus gives you credit card transaction data and analyst-ready tools designed for both sides of that job.
Get to the answer faster.
Ask a business question, and use Chroma to surface analyst-quality answers grounded in real consumer spending. Start with “Why is this category slowing?” Then ask which competitors are gaining, where the change is concentrated, or which customers are driving it – giving your team the first useful answer faster without giving up the ability to dig deeper.
Put the answer in context.
A number rarely means much on its own. Use Chroma to compare companies, categories, competitors, geographies, and consumer behaviors so the business can understand not only what moved, but what it moved relative to. That’s where credit card transaction data moves from just another dataset to context for the decision.
Validate what’s underneath it.
Actually, we’ve already done that for you, benchmarking our signal against verified economic sources like BEA Personal Consumption Expenditures, U.S. Census Monthly Retail Sales and company-reported earnings. But if you want to validate further, put Facteus up against your internal numbers – customers usually see correlation of >90%.
Bring the signal into your own models.
Use point-in-time credit card transaction data in forecasting, segmentation, competitive analysis, predictive models, or whatever your team is doing next. Deliver it through Snowflake, S3, API and other workflows so the analysis doesn’t stop inside Facteus. Get aggregated data feeds with Chroma or row-level data with Spectrum.
Do these questions sound familiar?
Compare your internal results with category, competitor, customer, and geographic trends to find the external forces behind it.
Use daily data and external benchmarks to see whether the signal is broad, sustained, and strong enough to matter.
Test the methodology and underlying credit card transaction data before it becomes an input to a higher-stakes decision.
Move from identifying the change to understanding which competitors, markets, customers, or behaviors are driving it.
Take the underlying data into your own environment for custom analysis, modeling, and production workflows.
You know the pattern…a question comes in five minutes before the meeting. The business wants the answer now, and your team still has to make sure the number is right.
Ask Facteus in plain language and get analyst-quality answers in seconds, grounded in consumer transaction data from the real U.S. consumer economy.
Interactive Demo
48 of 50 states
within 2 percentage points of expected BEA Personal Consumption Expenditures spending share
92% average correlation
with U.S. Census Monthly Retail Sales
Daily visibility
85% of data arrives the day after the transaction, with a 5-day full fill
Facteus credit card transaction data is built from passively collected purchase behavior across 200M+ active U.S. consumer cards, 5M+ merchant locations, 3,500+ brands, and 18+ direct financial sources.
And we check our signal every day against outside benchmarks instead of asking you to trust our panel just because we said so.
Move from “we’ll look into it” to an answer the business can explore with you in real time.
Give finance the outside context to know whether an internal trend reflects the company or the market around it.
Show where competitors, customers, and market are actually moving before an assumption becomes a recommendation.
Test coverage, history, representativeness, stability, and signal quality before bringing a new data source into production.
Bring verified consumer behavior into forecasting, segmentation, competitive, and predictive workflows.
Trace an insight back through the data and external benchmarks when someone asks how you know.
Industries We Serve
Restaurants
Benchmark competitor sales, traffic, and share down to the store level. See whether a soft quarter is your stores, the broader category, or guests shifting to the competition.
Retail
Track named competitors, market-share shifts, and shopper behavior across markets. See where demand is growing, where customers are moving, and where you have an opportunity to win.
Gas & Convenience
Separate fuel from the in-store spending, track trips by daypart, and benchmark local performance against convenience stores, QSRs, and coffee chains competing for your same customers.
Artificial Intelligence
Train, calibrate, and validate AI models against observed consumer spending behavior, so synthetic consumers and agents look like the real people who make up the U.S. economy.
Direct-to-Consumer
See where your buyers shop, which competitors share their wallet, and where lapsed customers go. Uncover retention risks and growth opportunities your first-party data can’t show you.
We’ll show you how quickly Facteus can get you to an answer, and give your team the credit card transaction data, methodology, and depth to decide whether that answer deserves to drive your next move.
Book a demoWhat level of credit card transaction data can analytics teams access?
Facteus supports granular, extractable transaction data for teams that want to build their own analysis, models, dashboards, and signals. You can get the data at an aggregate level via Chroma or go deeper with row-level data from Spectrum.
How is Facteus delivered?
Facteus works how you do. Data can be leveraged in your decisions through the Facteus platform, Snowflake, S3, API, or MCP to fit existing analytics and data-engineering workflows.
Can our business users explore the data without relying on analysts for every question?
Yes. Chroma’s natural-language experience lets users ask questions and explore the data conversationally, while analytics teams can retain access to the underlying data and methodology for deeper validation.
How do you validate representativeness?
Facteus scales its transaction signal to reflect the U.S. population and benchmarks it against external sources including BEA Personal Consumption Expenditures, U.S. Census Monthly Retail Sales, and company-reported earnings.
How current is the data?
Facteus data begins arriving the day after transactions occur, with 85% available on a 1-day lag and full fill typically reached within five days.
Can we combine Facteus with our first-party data?
Yes. Facteus can be integrated into existing analytics environments so teams can analyze external consumer behavior alongside internal datasets.
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