What Is SPINS Data? Natural Channel Coverage

SPINS data is syndicated retail point-of-sale data covering the natural, organic, and specialty channel. Where Circana and NielsenIQ built their networks around conventional grocery and mass merchants, SPINS built its panel around the stores where health-conscious shoppers spend the most: Whole Foods Market, Sprouts Farmers Market, Natural Grocers, co-ops, and thousands of independent natural retailers. If you sell a plant-based snack, a functional beverage, or a supplement and you want weekly dollar and unit sales across those accounts, SPINS is the primary source.

This post covers what SPINS actually measures, how its product-attribute tagging works, how SPINS retail data compares to the other major providers, and what brand teams need to know to get value out of a subscription.

What Is SPINS?

SPINS is a Chicago-based data and analytics company founded in 1995. Its core product is a weekly POS data panel built from scanner data collected directly from natural channel retailers. The company also layers on a proprietary attribute taxonomy, which is what makes the panel distinctive: every product in the SPINS database is tagged across dozens of wellness and lifestyle dimensions (more on that below).

SPINS operates what it calls a "universe" of retailers that have agreed to share scanner data. That universe concentrates on three trade channels it defines separately: Natural Supermarkets (large-format natural chains), Specialty Gourmet (premium independents and specialty chains), and Conventional Multi-Outlet (MULO), which is the same conventional grocery and mass universe covered by Circana and NielsenIQ. The natural supermarket and specialty gourmet channels together are often called the "natural channel" or the SPINS Natural Enhanced Channel, and that is where SPINS has no peer.

Understanding what is syndicated data is a prerequisite here: SPINS, like the other major panels, sells subscriptions that let brands see aggregated weekly sales across its panel without having access to individual retailer files. A brand does not need a data-sharing agreement with Whole Foods to see total SPINS natural supermarket velocity for its category.

Natural and Specialty Channel Focus

The practical difference between SPINS and its competitors comes down to which stores are in the panel. SPINS has deep coverage of the accounts that matter most to emerging and better-for-you brands. As of 2024, the SPINS Natural Supermarket channel covers roughly 2,200 stores. The Specialty Gourmet channel adds several thousand more independents, co-ops, and premium specialty locations.

That coverage profile creates a specific use case: a brand launching in the natural channel almost always needs SPINS data before it needs Circana or NielsenIQ data. Consider a functional mushroom coffee brand with 800 natural doors and zero conventional distribution. Circana MULO would show near-zero velocity because the brand has no conventional presence. SPINS natural supermarket would show the real story: $4.20 per point of distribution per week, growing 18% year over year, with strong velocity in the Pacific and Mountain regions. That is the number a brand manager needs for a Whole Foods regional review, a UNFI pitch, or a Series A deck.

As a brand scales into conventional, the picture shifts. A brand that crosses into Kroger, Target, or Walmart needs MULO data to see the full picture. At that stage, SPINS alone understates the brand's total retail footprint. Many mid-size natural brands end up subscribing to both SPINS and a conventional panel.

SPINS vs. Circana vs. NielsenIQ

The three major syndicated data providers cover overlapping but distinct retail landscapes. Choosing among them, or deciding whether to subscribe to more than one, depends almost entirely on where your distribution lives. Here is how the providers compare on the dimensions that matter most to CPG brand teams.

A few things are worth unpacking in that table. First, "channel strength" is about panel depth, not exclusivity. SPINS does offer a MULO channel, and Circana has some natural coverage, but neither penetrates the other's core turf as deeply. Second, Circana's causal data (feature ads, displays, price) tends to be more complete for conventional accounts, which is relevant for trade promotion analysis. See Circana Data Explained for a fuller breakdown of that panel.

Third, the comparison is not static. After Circana's 2022 merger of IRI and NPD, the company expanded into new categories. And SPINS has added conventional MULO coverage over the years. If you are evaluating subscriptions in 2025 or later, ask each provider to show you their exact store count in the channels where your brand has distribution before signing.

Attribute and Wellness Product Tagging

The feature that distinguishes SPINS most sharply from Circana and NielsenIQ is its product-attribute taxonomy. Every item in the SPINS database is tagged by SPINS analysts and automated systems across a large set of attributes covering ingredients, certifications, claims, and diet/lifestyle categories. Examples include: gluten-free, plant-based, non-GMO verified, USDA organic, keto-friendly, probiotic, allergen-free, and dozens more.

These tags are not self-reported by brands. SPINS maintains its own editorial process, reviewing packaging and certification documentation to assign attributes. That consistency is what makes the taxonomy useful for benchmarking: if you want to know how all plant-based protein bars are performing in the natural supermarket channel, SPINS can answer that question in a way that Circana cannot, because Circana's item data is not tagged at that level of wellness granularity.

How Attribute Tags Drive Category Analysis

In practice, brand teams use attribute tags to define a competitive set more precisely than standard category definitions allow. A functional beverage brand competing in the "Energy Drinks" UPC category might find it more useful to filter to items tagged "adaptogen" or "mushroom-based" to build a truer peer benchmark. With SPINS attribute data, you can build a custom segment: all items tagged "mushroom-based" and "functional" in the "RTD Coffee" category, sold in natural supermarkets, over the last 52 weeks.

That segment might contain 40 items from 15 brands. You can then see total segment dollars, your brand's share, average velocity per SKU, and which items are gaining or losing distribution. That level of analysis is not possible with UPC hierarchy alone.

Wellness Trend Tracking

SPINS publishes an annual Wellness Trends report built directly from its attribute data. Because the taxonomy is applied consistently over time, you can track attribute-level growth rates across years: what percentage of natural supermarket snack dollars in 2023 carried a "gut health" claim versus 2021. Retailers and distributors use this data to make category reset decisions. Brands use it to validate whether a wellness positioning angle has commercial traction before reformulating or relaunching.

How Brands Access and Use SPINS Data

SPINS sells data access through several models. Direct brand subscriptions give a brand team access to SPINS' own reporting platform (called SPINS Retail Insights, or the SPINS portal) where they can query sales, distribution, and attribute data for their categories and accounts. Subscriptions are typically scoped by channel (natural supermarket, specialty gourmet, MULO) and by category.

Many brands also receive SPINS data through their distributors. UNFI and KeHE both offer SPINS-powered reporting to their supplier partners at various tiers. The supplier-funded SPINS report through a distributor is often less expensive than a direct brand subscription and covers the distributor's own network, which is sufficient for brands in early distribution stages.

Worked Example: A 200-Door Natural Launch

Suppose a refrigerated plant-based dip brand launches into 200 natural supermarket doors in Q1. By Q2, the brand has 12 weeks of SPINS data. The key metrics to pull from a SPINS report for a buyer review:

• Velocity: dollars per point of distribution ($/PoD) per week. If category average velocity is $3.80 and the brand is at $5.10, that is a strong velocity story.
• TDP (Total Distribution Points): the number of items times the number of stores carrying them, across the reporting period. Flat or growing TDP means distribution is holding or expanding.
• ACV% Distribution: the share of panel ACV (All Commodity Volume) carrying the item. 200 doors in the natural supermarket channel might represent 14% ACV, a number buyers want to see trending up at reset time. (ACV here is All Commodity Volume, a store-size weight, not apple cider vinegar.)
• Attribute benchmarks: the brand can compare its velocity to all "plant-based" items in the dip/spread subcategory to show it is outperforming the segment average.

These metrics show up regularly across CPG data work. If terms like TDP or ACV feel new, WTD, CWW & Other CPG Data Acronyms is a useful reference to keep open alongside your SPINS reports.

Integrating SPINS with Other Data Sources

A common workflow issue for brand teams is that SPINS data lives in the SPINS portal while Circana data lives in Circana's platform and retailer portal data (Whole Foods Market's own POS, for example) lives in a separate login. Pulling a complete sales picture requires downloading reports, reformatting, and reconciling. Some brands build their own spreadsheet consolidation workflows. Others use platforms that ingest SPINS exports and harmonize them alongside Circana and retailer POS files so analysts are working from a single dataset. Scout is designed around that specific workflow, connecting SPINS, Circana, and direct retailer feeds in one place.

Common Questions About SPINS Data