Circana Data Explained (Formerly IRI)

Circana is the market-research firm behind the syndicated point-of-sale and consumer-panel data that most large CPG brands use to track how their products sell. It was created when two long-standing firms, IRI and The NPD Group, merged in 2022 and took the single Circana name in 2023. If you have ever seen a category review built on 'IRI data' across grocery, drug, and mass retailers, you have already used Circana: the IRI name was retired, but the panel and methodology behind it carried straight over. This guide explains what Circana is, what its data covers, how it compares to NielsenIQ and SPINS, the platforms it ships on, how brands get access, and where it falls short.

What is Circana? The IRI and NPD merger

Circana is a Chicago-based market-research and analytics company that sells syndicated retail data: a standardized, market-wide picture of what is selling, where, and at what price. It came together in 2022 through the merger of two firms with complementary coverage. IRI (Information Resources, Inc.) had spent decades measuring point-of-sale movement in grocery, drug, mass, convenience, and club. The NPD Group specialized in discretionary general-merchandise categories like technology, toys, apparel, beauty, and footwear, plus foodservice. The combined company kept both books of business and dropped both old names in favor of Circana.

For a CPG brand, the practical takeaway is simple: when a buyer, a broker, or an old category deck says 'IRI', they almost certainly mean Circana now. The store panel, the methodology, and the metrics are continuous across the rename, so a search for 'Circana IRI data' and a search for 'IRI data' land on the same lineage. The same goes for NPD in the discretionary world. For the wider context on where Circana sits among data providers, see the guide to what syndicated data is.

What Circana data covers: POS and panel

Circana data comes in two fundamentally different forms, and most brand teams license both. The split matters because each answers a different question, and neither can do the other's job.

Circana POS data, also called scan data, is built from the checkout. Participating retailers share their point-of-sale scans with Circana under license, and Circana aggregates them across thousands of stores into a weekly read of units sold, dollar sales, average price, and promotional activity, broken out by product, retailer, market, and channel. This is the backbone of distribution and velocity reporting, and the source behind metrics like %ACV distribution and total distribution points. What scan data cannot tell you is who bought the product: a unit is a unit whether a first-time shopper or a loyal household scanned it.

Circana panel data fills that gap. A recruited, demographically balanced set of households records its purchases, and Circana projects that sample up to the population to measure household penetration, repeat rate, basket composition, and buyer demographics. Panel data is less precise on absolute sales than scan data, because it is a projected sample rather than a census of registers, so teams pair them: POS data for what sold, panel data for who bought it and whether they came back. That POS-versus-panel distinction runs across every provider, and we cover it in syndicated vs. panel data.

Those two tracks are also the short answer to how Circana collects its data. The POS side is retailer-supplied scan feeds, standardized so that every UPC maps to a product and every product to a category and a week. The panel side is recruited households scanning or reporting what they buy. Circana then layers modeling on top of both to fill coverage gaps and project the sample up to the full market.

Circana vs. NielsenIQ vs. SPINS

Circana is one of three providers that dominate U.S. syndicated retail measurement, and which one a brand leans on depends almost entirely on the channel it sells into.

The headline difference is channel. Circana and NielsenIQ are the conventional-channel heavyweights, while SPINS owns the natural and specialty channel. A natural-products brand selling through Sprouts and Whole Foods lives in SPINS; a brand built on Kroger, Walmart, and Albertsons lives in Circana or NielsenIQ. Brands that straddle both channels often end up licensing two providers and reconciling the seams by hand, because the panels do not share a hierarchy or a calendar. For the full side-by-side, see SPINS vs. Circana vs. NielsenIQ and our guide to what SPINS data is.

Liquid Data and Unify: the Circana platforms

Circana data is delivered through a few named platforms, and the names trip people up because some are inherited from IRI. Liquid Data is the long-standing IRI-era data network and delivery layer, the pipes that move standardized POS and panel data to subscribers and to partner applications. Unify (and Unify+) is the self-service analytics front end, the dashboards and reporting workspace where an analyst pulls a category view, builds a share report, or runs a promotion read without writing code.

Most brands also receive Circana data as flat-file extracts or through an API, which is how it lands in a data warehouse or a third-party analytics tool. In practice an analyst's week is a mix: a few canned Unify reports, a recurring extract feeding an internal model, and a pile of spreadsheet reconciliation to make the two agree. The platform is rarely the bottleneck. The reconciliation is.

How brands access Circana data

Circana data is a licensed subscription, not a public dataset. A brand signs an annual agreement scoped to the categories, channels, and markets it wants to see, and the cost typically runs into five or six figures a year, scaled by that scope. Access usually flows through one of three routes: a Unify login for self-service reporting, recurring data extracts piped into the brand's own systems, or a broker or category-management partner who holds the subscription and pulls reports on the brand's behalf, which is common for smaller brands that cannot justify a direct license.

Whichever route a brand takes, the raw output is famously hard to work with. Circana extracts are wide, deeply hierarchical, and formatted for completeness rather than convenience, which is why so much of a brand analyst's week disappears into cleaning them and joining them against retailer first-party feeds like Walmart Retail Link and Kroger's 84.51 and Stratum.

Strengths and gaps of Circana data

Circana's strengths are breadth and continuity. It has the deepest conventional-channel POS coverage in the U.S., a store panel large enough to read as statistically representative across grocery, drug, mass, and convenience, and decades of consistent history to trend against. The merger added discretionary general-merchandise and foodservice tracking that no pure grocery provider offers. For a brand whose volume sits in conventional retail, Circana is the closest thing to a market-wide scoreboard. The gaps are just as real:

• Coverage gaps. Not every retailer reports, and the natural and specialty channel is thinner than SPINS. Club and hard-discount accounts such as Costco are partial or modeled, so a category can look flat in Circana while it is growing in the accounts the panel cannot see.
• Reporting lag. Syndicated data lands a week or more after the selling week closes, with revisions trickling in after that. For a fast promotion read, a retailer's own first-party feed is days fresher.
• It tells you what, not why. A dip in the scan data could be a shelf reset, an out-of-stock, a competitor promotion, or genuine demand loss. Separating those is the analyst's judgment, not the data's.
• Cost and handling. Between the subscription and the analyst hours spent wrangling extracts, the true cost of Circana sits well above the list price.

None of this makes Circana optional for a conventional-channel brand. It remains the market-wide, apples-to-apples read that buyer conversations are built on. The discipline is to pair it with retailer first-party POS data and the brand's own shipments, and to keep its blind spots in view rather than treating the panel as ground truth. For how the velocity, share, and distribution metrics interact once the data is clean, see the velocity, share, and TDP decision tree.

Where Scout fits

Scout is an AI retail analytics platform that harmonizes Circana data with NielsenIQ, SPINS, retailer first-party feeds, and a brand's own shipment numbers into one comparable view. The reconciliation that used to eat an analyst's week happens automatically: mismatched hierarchies get mapped, calendar weeks get aligned, and the Circana read gets netted against the Kroger first-party number. The team gets one trustworthy picture of distribution, velocity, and promotion performance, and the analyst gets back to the interpretation that actually needs a human. To see it run on your own syndicated data, reach out at hello@cpgscout.ai.