US Food Market: Understanding the FMI and IRI Data Sources

Making commercial decisions in the US food market requires accurate market intelligence. FMI (Food Marketing Institute) and Circana (formerly IRI) are the two most widely cited data sources in US food retail. Understanding what each publishes and how to access it helps food businesses make evidence-based decisions.

FMI — Food Marketing Institute

FMI represents US food retailers and their suppliers. Their published research includes:

• US Grocery Shopper Trends: Annual report on US consumer food shopping behaviour, attitudes, and channel preferences
• Power of Produce: Annual category report on fresh produce retail trends
• Power of Foodservice: Data on US restaurant and prepared food purchasing

FMI research is publicly available (some reports are free; full data requires membership). It provides macro-level trend data useful for market sizing and positioning.

Circana (IRI)

Circana (the merged IRI and NPD Group) provides the most detailed US food retail point-of-sale data. Their CPG market intelligence covers:

• Category sales velocity by retailer channel
• Market share by brand and SKU
• Consumer panel data on food purchasing behaviour
• Innovation tracking (new product launches and sales performance)

Circana data is expensive for independent access. Many US retailers share Circana category data with their suppliers as part of the trading relationship.

Using Market Data as a Small Food Business

For small food businesses, the most accessible route to US market intelligence is FMI's free reports, the USDA Economic Research Service (free, government published), and Mintel food market reports (available via many public libraries).

Enter the US market with compliant allergen management using Allergen Matrix in FALCPA mode.

How to Read Category Velocity Data

Category velocity data, as reported by Circana, measures how quickly products sell through retail channels over a defined period. It is typically expressed as sales per point of distribution, which normalises performance across retailers of different sizes. Understanding velocity benchmarks for your specific category — whether ambient grocery, chilled, or specialty — helps you assess whether a new product launch is gaining meaningful traction or underperforming relative to competitors already established on shelf.

When you receive velocity data from a US retail buyer, it is important to understand which channel it represents. Circana segments data across channels including food, drug, mass merchandise, club, and dollar stores. A product performing strongly in natural and specialty channels may show lower velocity in conventional grocery, and that difference is not a failure — it reflects genuine channel dynamics. Comparing your product only against the correct channel benchmark prevents misreading early commercial performance.

For small food businesses approaching US retail buyers without direct Circana access, the practical solution is to request category sell-through data directly during buyer meetings. Many major US grocers, including regional chains, will share category context to help suppliers understand the opportunity. Preparing specific questions about category velocity before meetings — and knowing the FMI macro-level data as context — signals commercial credibility and helps move conversations forward faster.

Understanding USDA Economic Research Service Data

The USDA Economic Research Service (ERS) is one of the most underused free resources available to food businesses entering the US market. The ERS publishes detailed data on food expenditure patterns, commodity price trends, food-away-from-home versus at-home spending splits, and long-run category consumption trends. Because it is government-produced and updated regularly, it provides a reliable baseline that commercial data sources like Circana build upon with retail-level detail.

ERS data is particularly useful for understanding structural trends rather than short-term sales movements. For example, ERS research consistently tracks the long-run shift in US consumer spending toward convenience and prepared foods, the relative price sensitivity of different income groups, and regional variation in food purchasing behaviour across the US. These structural insights help food businesses make category positioning decisions that are grounded in durable consumer trends rather than short-cycle retail noise.

Accessing ERS data requires no registration and no cost. The ERS website organises data by commodity and topic, making it straightforward to find relevant category reports. Food businesses should treat ERS as a first-stop research tool when sizing a US market opportunity, and use it alongside FMI's published reports to build a macro-level market view before investing in more expensive commercial data sources or commissioning primary consumer research.

Translating Market Data Into Shopify Product Strategy

Market intelligence from FMI, Circana, and the USDA becomes directly actionable when it informs how you structure your Shopify store for the US market. Category trend data can guide which products to prioritise in your US range, which claims to lead with in product descriptions, and how to position your brand relative to the dominant players identified in Circana share data. Food businesses that skip this translation step often build US-facing stores that reflect their UK positioning rather than genuine US consumer demand signals.

Velocity benchmarks and category growth rates should also inform your US content strategy. If Circana data shows that your category is growing fastest in the natural and specialty channel, your Shopify content — product pages, blog posts, and collection copy — should reflect the language, values, and purchase motivators that drive that shopper segment. FMI's Grocery Shopper Trends report provides additional colour on how US consumers describe their food priorities, which feeds directly into how you write product copy and meta descriptions for a US audience.

Publishing regular, data-referenced content through your Shopify blog builds long-term authority in your category with US audiences. Blog posts that reference FMI or USDA data demonstrate that your brand understands the market, not just its own products. Using a tool like BlogFlow to manage a consistent publishing cadence makes this sustainable for small teams. Structured, well-researched content also improves organic search performance in the US, where search intent around food trends and category education is consistently high.

Interpreting Consumer Panel Data for Niche Food Categories

Consumer panel data, which Circana sources from its proprietary panel of US households, tracks actual purchase behaviour rather than retailer sell-through. This distinction matters for niche food categories where a product may have limited but highly loyal buyers. Panel data reveals household penetration rates — the percentage of US households that have bought your category at least once — and purchase frequency, which together define the growth opportunity available through recruiting new buyers versus selling more to existing ones.

For specialty and ethnic food categories, panel data often reveals a pattern of low penetration but above-average purchase frequency among buyers who engage with the category. This means growth strategy should prioritise trial recruitment over frequency building — getting new households to try the product is more valuable than encouraging existing fans to buy more often. Understanding this dynamic shapes how you allocate marketing spend, which retail channels you prioritise for distribution, and how you structure introductory pricing and promotional mechanics in the US market.

Small food businesses rarely have direct access to Circana panel data, but trade press publications including Progressive Grocer, Grocery Dive, and Food Business News regularly publish panel-derived insights in their editorial coverage. Monitoring these sources consistently gives food businesses a working understanding of category-level consumer dynamics without the significant cost of a Circana subscription. Combining this secondary research habit with FMI's annual reports provides a practical intelligence framework that is achievable without a dedicated market research budget.

Building a Repeatable US Market Research Process

The businesses that use US market data most effectively treat it as a recurring process rather than a one-time exercise before launch. Building a simple quarterly research review — pulling the latest FMI updates, checking USDA ERS for commodity and expenditure trends, and reviewing trade press for Circana-cited category data — keeps your commercial decisions grounded in current market conditions rather than assumptions formed at launch. Markets shift, category dynamics change, and consumer priorities evolve, so intelligence needs to be refreshed regularly.

A practical structure for this process is to separate macro research from category-specific research. Macro research draws on FMI and USDA data to monitor broad shifts in US food retail — changes in channel mix, evolving shopper attitudes, and spending pattern trends. Category-specific research focuses on trade press coverage, buyer conversations, and any retailer-shared data to track competitive dynamics within your specific segment. Keeping these two layers distinct prevents macro trends from being misread as direct signals about your product's immediate commercial position.

Documenting your research process and outputs in a consistent format — even a simple shared document updated quarterly — builds institutional knowledge over time. This is particularly valuable for small food businesses where market knowledge often sits with one or two people. When the business scales, brings on new team members, or approaches US investors or retail buyers, having a structured record of how market intelligence has informed decisions demonstrates commercial rigour. Pair this with a consistent content publishing habit using BlogFlow to turn your market knowledge into organic visibility in the US.

Try BlogFlow free at saltai.app — no credit card required.