SPINS vs. 84.51° Stratum vs. Circana for Kroger data

Why your choice of Kroger data source matters

A brand sells through Kroger and wants better visibility into what's happening at the shelf and who's buying it. They have three buyable data sources:

• SPINS — syndicated, third-party, includes Kroger as part of MULO and MULO+ coverage
• Circana — the major syndicator for conventional grocery, with deep MULO coverage including Whole Foods
• 84.51° Stratum — Kroger's own data and analytics platform, operated by Kroger's data subsidiary 84.51° (under Kroger Precision Marketing)

Each one answers different questions. None is a complete substitute for any of the others. Buying all three is expensive; buying the wrong one for the question is also expensive. This page maps question → source.

SPINS, 84.51° Stratum, and Circana for Kroger data: what each source is

SPINS (syndicated, third-party)

• What it measures: Kroger sales as part of SPINS' MULO+ coverage. Includes total-store and (with paid add-on) banner-level reads for Ralphs, King Soopers, Fred Meyer, Harris Teeter, and other major Kroger banners.
• Granularity: Brand × SKU × banner × week is the typical bottom cell. Retailer-level and channel-level aggregations pull directly from the same data.
• Strengths: Kroger sits alongside every other retailer in the same data model. Cross-retailer, cross-channel comparisons are native — Kroger vs. Sprouts vs. Natural Grocers vs. Whole Foods (via Circana partnership data) in one report. Best for category-level comparison and benchmark work in a brand that spans natural and conventional. The SPINS product attribute layer (organic, plant-based, non-GMO, functional) applies to the Kroger data the same way it applies to natural-channel data.
• Weaknesses: No buyer demographics. No basket-level data. No loyalty-segment cuts. Banner-level data is a paid add-on; without it, you see only the total Kroger aggregate. Reporting cadence is weekly with a multi-week lag. The conventional-channel Kroger data feeds through the SPINS–Circana partnership rather than from a direct Kroger relationship.
• Pricing context: Standard SPINS contracts for natural brands start in the $30,000–$80,000 range. The MULO+ extension and banner-level Kroger add-on push toward the higher end. Most brands adding banner-level Kroger coverage to an existing SPINS natural contract are looking at incremental cost in the $5,000–$15,000/year range depending on the tier.

Circana (syndicated, third-party)

• What it measures: Kroger sales as part of Circana's MULO and conventional grocery coverage. Circana has a direct data relationship with Kroger conventional, and also carries Whole Foods — which SPINS doesn't. This makes Circana the preferred source for any brand where Whole Foods + Kroger is the relevant universe.
• Granularity: Brand × SKU × retailer × week at standard cuts; banner-level and geo-level with additional licensing.
• Strengths: Broadest conventional-grocery coverage including Whole Foods. The default source for any pure-conventional MULO analysis. Deep history and stable methodology. Circana Unify+ (the successor to the Liquid Data portal) is the long-established platform for conventional CPG work.
• Weaknesses: Natural-channel attribution depth is limited compared to SPINS. The attribute layer that SPINS uses for natural products is absent or thinner in Circana. No loyalty or household demographics. A full Circana MULO contract typically runs $60,000–$150,000+ annually for a brand account — higher than SPINS for a comparable coverage footprint.
• When to use instead of SPINS: The primary case is when Whole Foods is a material part of the business. Circana carries Whole Foods directly; SPINS doesn't. A brand doing $2M+/year in Whole Foods is leaving a significant blind spot uncovered with SPINS-only data.

84.51° Stratum (Kroger-direct)

• What it measures: Loyalty-card-attached purchase behavior at Kroger and family of banners. Stratum is described by 84.51° as delivering insights from transactions made by one out of every two US households — a loyalty-attached transaction base that dwarfs what any panel could recruit.
• Granularity: Down to the household level (anonymized, with demographic attributes). Basket-level: what else was in the cart. Trip-level: the purchase occasion and trip type. This is qualitatively different data than what any syndicator produces.
• Strengths: Best-in-class for who is buying — demographic and household-segment attribution at Kroger. Basket behavior (what else the buyer picks up alongside your product). Loyalty-segment behavior over time — are trial buyers repeating, and at what rate? Banner-level performance at a speed and granularity that syndicated data can't match. The platform includes Stratum (analytics dashboards), Data Direct (raw data feeds), and newer self-serve capabilities including Data Orders (ad-hoc custom data pulls) and the AI-driven weekly summary "Agent Monday" launched in 2025.
• Weaknesses: Kroger-only; no cross-retailer comparison. The loyalty data covers only transactions where a loyalty card was used — it misses cash and unlinked transactions, which vary by store and category. Pricing is enterprise-tier with access gated behind a vendor agreement; the cost model involves both platform fees and, for Kroger Precision Marketing (KPM) campaigns, media spend minimums. Not a self-serve tool for small brands without a broker or retail relationship manager to facilitate access.

Kroger data sources comparison: question → source

A worked example — post-promo analysis at Kroger

A protein bar brand runs a temporary price reduction (TPR) at Kroger for four weeks in Q3. After the promo ends, the category director asks the two questions that always follow a promo: "Did it work?" and "Did it hold?"

SPINS / Circana answers "did it work" (from the syndicated read):

Syndicated read: the promo lifted volume 85–90% during the four promo weeks. Post-promo, sales returned to within 5% of pre-promo levels. No long-term pantry loading at the expense of post-promo recovery — a clean, efficient promo.

84.51° Stratum answers "did it hold" (from loyalty data):

• 38% of promo-period buyers were new to the brand at Kroger in the prior 26 weeks (trial buyers)
• Of those trial buyers, 29% made a second purchase within 8 weeks of their first promo purchase — a meaningful repeat rate given the category average is 22% for new buyers.
• The trial buyers who repeated were disproportionately from the King Soopers and Ralphs banners, where the household income and organic-buying behavior aligns with the brand's core buyer profile.
• 12% of promo-period buyers were lapsed brand buyers (bought 12+ months ago but not recently) — the promo recaptured some lapsed customers.

The Stratum answer tells the story the syndicated read can't: the promo worked in the right banners and converted 29% of new trial buyers to repeat — above category average. That's the data that goes to commercial leadership and to the Kroger buyer as proof the promo produced durable value, not just a volume spike.

84.51° Stratum: access and pricing realities

84.51° operates multiple data and media products under the Kroger Precision Marketing (KPM) umbrella. For CPG brand analysts, the relevant products are:

Stratum analytics platform — self-serve dashboards covering household behavior, basket, demographics, and brand-level KPIs at Kroger. Access requires a vendor agreement with 84.51° and typically involves either a subscription fee or per-query pricing depending on the tier. Brands without a direct relationship often access Stratum through their shopper-marketing agency or their broker's data services.

Data Orders — ad-hoc data pulls for custom analyses not covered by the standard dashboard. Useful when a specific question (e.g., "what demographic over-indexes on our brand in Q4 vs. Q3?") requires a cut that isn't pre-built. Data Orders are priced per request.

Data Direct — raw data feed integration for brands or agencies that want to run Kroger loyalty data through their own analytical infrastructure. Requires technical setup and a higher-tier vendor agreement.

Agent Monday — 84.51°'s AI-powered weekly digest that summarizes brand performance at Kroger automatically. Launched in 2025, it is part of the Stratum platform and provides a pre-synthesized view of key weekly metrics without manual report-building.

Pricing context: 84.51° pricing is not publicly disclosed and is negotiated through the vendor agreement process. Practically, brands with less than $5M in annual Kroger sales often find the platform cost challenging to justify relative to the investment. Brands above $10M/year in Kroger revenue typically find the ROI straightforward. Shopper marketing investment through KPM (Kroger's media network) can offset some platform access costs in the KPM program structure — brands running meaningful KPM campaigns often get Stratum access bundled.

A practical pattern

Most Kroger-serious brands end up with two of these three sources:

• A syndicator (SPINS or Circana, or both for natural+conventional brands) as the always-on cross-retailer read — what's happening at Kroger in the context of every other retailer. This is the weekly category and sales reporting surface.
• 84.51° Stratum for buyer-side strategic work — quarterly or campaign-driven, focused on who's buying and what else they buy. Drives innovation, segmentation, and shopper marketing.

A brand that has only a syndicator is missing buyer attribution and real-time read. A brand that has only Stratum is Kroger-myopic with no comparative benchmark against the rest of the category landscape.

The phased approach for a brand growing into Kroger:

• Early stage (< $5M Kroger): SPINS for Kroger in the same report as all other retailers. Stratum not yet cost-justified. Use the Kroger total read as the primary Kroger metric.
• Growth stage ($5–$15M Kroger): Add SPINS banner-level add-on to separate King Soopers/Ralphs performance from the mainstream banners. Consider Stratum access through a broker or agency for key campaigns.
• Established stage ($15M+ Kroger): Direct Stratum vendor agreement justified by the data value. SPINS or Circana as cross-retailer benchmark. Potentially both syndicators if the brand spans natural and conventional channels.

Where the gaps are

Two specific gaps no source closes:

1. Cross-retailer buyer behavior. 84.51° Stratum tells you who's buying at Kroger. It can't tell you whether the same household is also buying at Whole Foods, Sprouts, or Costco. For cross-retailer household behavior, you need a household panel (NielsenIQ Homescan, Numerator) — see Syndicated vs. panel data. This matters for brands asking "is our Kroger buyer also buying us at natural channel retailers?" or "when we get authorized at Sprouts, will we cannibalize our Kroger volume?" Panel data is the only source that answers these questions cleanly.

2. Shelf-execution vs. data-reported sales gap. None of these sources tell you if your product was actually on the shelf when the shopper looked. Out-of-stocks at Kroger are real — a fast-moving SKU in a mid-size banner can go OOS for days between replenishment cycles. For execution monitoring, shelf data (audits, image recognition) is needed on top of the transaction data — see What is share of shelf?.

Doing this in Scout

Scout's primary surface for Kroger is the SPINS extracts your team uploads weekly — the cross-retailer, cross-channel context for "how's Kroger doing relative to every other retailer we sell in." For 84.51° data, Scout supports customer-uploaded Stratum exports (including the Sherlock Matrix Export format), so brands that pay for Stratum can layer the loyalty-attached insights into the same dashboard surface as their syndicated reads. Direct API feeds with 84.51° aren't wired today; the integration model is upload-driven. The goal is one analytical surface for a Kroger read that spans both syndicated category context and loyalty-attached buyer behavior, rather than flipping between the Stratum portal and a SPINS spreadsheet.

Summary + further reading

• SPINS, Circana, and 84.51° Stratum measure different aspects of Kroger performance — none substitutes for the others.
• SPINS is right for cross-retailer comparison in a natural+conventional brand; Circana is right for conventional-only brands or any brand where Whole Foods matters; 84.51° Stratum is right for buyer attribution, basket behavior, and post-promo analysis.
• Most Kroger-serious brands end up with a syndicator + Stratum, scoped to different cadences and use cases. The $10M+ Kroger revenue threshold is the rough point at which direct Stratum access is cost-justified.
• Neither syndicated data nor Stratum covers cross-retailer buyer behavior or shelf execution — household panel and shelf audit data fill those gaps.

Related: Reading Kroger total-store performance in SPINS · SPINS vs. Circana vs. NielsenIQ