Methodology
SPINS methodology for CPG analysts
Methodology guides for brand-side CPG analysts working in SPINS. ACV, TDP, share of shelf, MULO+, panel-coverage gotchas, and the syndicated-vs-Kroger-direct-data decisions that come up every quarter. Written for the analyst, not for the buyer.
Foundations
Plain-English definitions of the SPINS metrics and data sources every analyst should be able to explain in one sentence.
What is SPINS data?
What is SPINS data? SPINS is the leading syndicated retail data source for natural and wellness CPG. This is what it tracks and how brands use it.
What is ACV?
What is ACV? All Commodity Volume weights retail distribution by each store's total sales. Here's how to read it and where analysts get tripped up.
What is TDP (Total Distribution Points)?
What is TDP? Total Distribution Points sums the %ACV of every SKU a brand sells. What it tells you, and the trap of using it as a single metric.
What is MULO, and what SPINS' MULO+ adds
What is MULO? The CPG industry's Multi-Outlet aggregate. SPINS' MULO+ adds Natural Enhanced coverage. This is the difference and when to use which.
What is share of shelf?
What is share of shelf? It measures a brand's facings as a fraction of category facings. This is how it's tracked, what it explains, and what it doesn't.
Syndicated vs. panel data: what each measures
Syndicated vs. panel data: they answer different questions about CPG sales. Here's what each measures, where they overlap, and when to use which.
How SPINS product attribute tagging works
Product attribute tagging is how SPINS labels each UPC with claims and ingredients. How the attribution layer is built, and where it drifts.
What large CPGs do that small brands can copy
Large CPG teams are not smarter, they are instrumented. Five practices they run on a fixed calendar, and the version a three-person brand can run.
Methodology deep-dives
How to actually compute these metrics in real data: the steps, the math, the gotchas, and what the textbook leaves out.
ACV-weighted distribution across SPINS retailers
ACV-weighted distribution in SPINS captures both store count and store importance. How to calculate it across retailers without double-counting.
SPINS metrics decision tree: velocity, share, TDP
A SPINS metrics decision tree for velocity, share of shelf, and TDP: here's which metric answers which analyst question.
Decomposing TDP: ACV change vs. SKUs-per-door change
TDP can grow from new doors, new SKUs at existing doors, or store-mix shift. Each is a different commercial story. How to tell them apart.
Choosing a baseline period for SPINS post-promo lift
Pre-promo, year-over-year, or trend-adjusted? The baseline choice can swing a SPINS promo lift number by 30+ points. Here's how to pick.
Comparing brand performance across SPINS channels
Reporting +24% growth in Natural and +5% in MULO without weighting by channel size? You're misleading the CFO. Here's how to compare honestly.
SPINS panel coverage: projection & suppression
SPINS panel coverage explained: how SPINS projects from sample stores to the full channel, and how projection and suppression shape what you read.
SPINS vs. Circana vs. NielsenIQ, compared
SPINS vs. Circana vs. NielsenIQ: all three sell syndicated CPG data. From an analyst's chair, here's what each does well and where each falls down.
Broker sales reporting across a multi-brand book
How a CPG broker reports sell-through, distribution and promo lift across every brand they rep, and what to put in front of a principal at renewal.
Markdown optimization: when and how deep
Set markdown timing and depth off the sell-through curve: the trigger rule, the depth formula, and why the deepest cut is rarely the best one.
Measuring brand equity with retail scan data
Four measurable proxies for brand equity you can compute from scan data: price premium, promotional dependence, distribution ramp and repeat rate.
Measuring forecast accuracy without fooling yourself
MAPE, WMAPE and bias measure different failures. Here is which metric to use at which grain, and why a good accuracy score can still cost money.
Price elasticity in CPG: measure it, then use it
How to calculate price elasticity from retail POS data, why base and promoted elasticity differ by 3x, and where price thresholds break the math.
Price optimization models, compared
Rule-based, elasticity-based, competitive-response and ML price optimization models: what each optimizes, what it needs, and where it breaks.
Retail price index: how to calculate it
How to build a retail price index against a competitive set, which base to pick, and the weighting mistakes that make the number say the wrong thing.
Retail pricing strategies that hold together
How a retailer builds price architecture: price zones, KVI selection, margin mix across the basket, and the rules that keep the price file coherent.
Store clustering: how to build and test clusters
Store clustering groups stores by what their own POS says they sell. How to pick the features, choose the number of clusters, and validate them.
Category management
A working textbook on category management, one chapter per step: define the category, set its role, run the assessment, and win the shelf at the review.
The 8-step category management process
The eight-step category management process walked end to end: define, role, assessment, scorecard, strategy, tactics, implementation, and review.
How to define a category in retail
How to draw category boundaries in a retail set, and why the line you pick decides whose sales count in every number that follows.
Category roles: destination to convenience
The four category roles, destination, routine, seasonal, and convenience, and how a category role caps the shelf and promotion it can win.
How to run a category assessment
The category assessment, step 3: read dollars against units, share, velocity, and distribution to find where the shelf is actually leaking.
Building a category scorecard
The category scorecard, step 4: the sales, margin, unit, and share targets that decide which recommendations survive the category review.
Category strategies, and when to use each
The category strategy archetypes, traffic, transaction, profit, cash, excitement, image, and turf defense, and how to pick the one that fits.
Assortment planning in category management
Assortment and SKU rationalization, the biggest tactical lever: how to cut, add, and defend items with velocity, TDP, and incrementality.
Category pricing and price architecture
Pricing tactics for category managers: price ladders, gaps, key value items, and price architecture that grow category dollars without eroding margin.
Planograms and shelf space to sales
Planograms and space-to-sales: how to allocate facings by performance, not fair share, and defend the shelf move with share-of-shelf math.
Promotion planning for category managers
Promotion planning at the category level: build a calendar around lift and baseline, avoid cannibalization, and promote to grow the whole set.
Implementing a category plan and reset
Step 7: turning a category plan into a shelf reset, discontinued-SKU sell-down, promo load, and the compliance check that proves it happened.
The category review meeting, step by step
The category review: the twice-a-year meeting where the scorecard meets actuals, the buyer decides the reset, and evidence beats opinion.
The category captain and validator roles
The category captain, validator, and buyer: who gets the data, who builds the plan, and how retailers keep the captain from self-dealing.
Evaluating promotions after they run
Most promotion post-mortems measure the wrong thing. Here is how to separate lift from baseline, account for the costs that hide, and rank what to repeat.
Food trends on TikTok: from trend to order
A viral food trend reaches your scan data weeks after it peaks online. How to read the lag, and turn a TikTok trend into an order you can place.
Where to get help with assortment decisions
A guide to who helps with retail assortment, what each source is good at, what it costs, and whose interest each one actually represents.
Retailer & channel guides
Retailer-specific quirks: Kroger banners, Sprouts coverage, Whole Foods Natural, Costco gaps, KeHE/UNFI movement.
Kroger banner vs. total in SPINS aggregates
Kroger banner data in SPINS: total-store reads hide banner-level performance. Here's how Ralphs, King Soopers, Fred Meyer, and Harris Teeter differ.
Monitoring Kroger banner performance in SPINS
How to monitor Kroger banner performance week-over-week: what signals matter, what's noise, and when banner divergence becomes a brand decision.
SPINS vs. 84.51° Stratum vs. Circana for Kroger data
SPINS, 84.51° Stratum, and Circana cover Kroger differently. Here's which Kroger data source answers which analyst question and where the gaps are.
Reconciling Kroger promo lift across SPINS & scan
SPINS, 84.51° Stratum, and scan data each tell a different story about the same Kroger promo. Here's how to reconcile them without picking favorites.
Sprouts in SPINS vs. the vendor portal
Sprouts gives vendors their own portal, but SPINS' read of Sprouts shows cross-retailer context the portal can't. Here's what each surfaces and hides.
Whole Foods in the SPINS Natural channel
Whole Foods doesn't report POS data to SPINS, but the Natural channel reads still tell you a lot about WFM's category context. Here's how to use them.
Costco and club performance: the SPINS coverage gap
Costco sits outside the standard syndicated universe, so SPINS gives you no Costco read. Here's how brands triangulate Costco performance.
Reading KeHE and UNFI movement data in SPINS
KeHE and UNFI distributor flow is what SPINS uses for independent natural retailers, but it's shipment data with quirks. Here's how to read it cleanly.
On-Shelf Availability Benchmarks: Kroger 2026
Real Kroger scan data on on-shelf availability and velocity: how often items go out of stock at the shelf, and how fast they sell per store per week.
Retail operations
For the retail side of the desk: supplier scorecards, store-level ordering and replenishment, assortment productivity, and the reporting that carries it to a board.
Building a retail supplier scorecard
The weighted five-line scorecard that turns a supplier review from an argument about anecdotes into a graded conversation about fill rate and velocity.
Supplier performance metrics that survive scrutiny
How to compute OTIF, velocity index, on-shelf availability, and promo ROI so the numbers hold up when a supplier disputes them in the room.
How to choose a retail supplier
A weighted selection framework for retail buyers: landed cost, service capability, category fit, and the reference checks that predict performance.
Vendor management best practices for retail
Running the supplier relationship after the contract: review cadence, the escalation ladder, and what to do with a vendor who stays red.
The retail purchasing process, end to end
The 28-day retail purchasing cycle: demand review, negotiation, PO issue, receiving, and the performance review that gets squeezed to nothing.
How to prevent over-ordering in retail
Over-ordered lines are invisible in most order screens because the recommendation is a net number. How to surface them and stop paying for them.
Retail replenishment guidance that stores follow
Setting par levels, safety stock, and review cycles per item class, and why a single chain-wide weeks-of-supply target breaks at both ends of the range.
How to reduce overstock in retail
Overstock is the residue of ordering decisions made weeks earlier. How to find it before markdown season, clear it in order, and stop refilling it.
Store-level inventory visibility, and what breaks it
Chain-level inventory numbers hide the store-level truth. Why perpetual inventory drifts, how to detect the drift, and what visibility actually enables.
Assortment optimization for retail buyers
Where the cut line actually falls, why the bottom three deciles are not automatically deletable, and how to add without duplicating what already sells.
Shelf space optimization with space-to-sales
Using a space-to-sales index to find over-spaced and starved categories, and why moving to a pure index is the wrong answer for most sets.
Improving sales per square foot in retail
Why the lowest-returning department is usually the largest, how to compare departments fairly, and which moves actually raise sales per square foot.
Building a retail KPI dashboard
Which metrics belong at store, category, and executive level, why each tier needs a different clock, and how to keep a dashboard from becoming wallpaper.
Retail executive dashboards and board reporting
What belongs in a weekly executive read versus a quarterly board pack, and why reprinting the operating dashboard for a board is the standard failure.
Getting usable data out of a c-store back office
How to get analysable data out of a convenience back office: what each export contains, the joins that break, and the checks to run before trusting it.
How to audit a convenience store pricebook
A five-pass method for auditing a c-store pricebook: find stale costs, orphaned promos, unknown UPCs and tag mismatches before they reach a report.
PDI alternative: replace the system or the reports?
Most operators searching for a PDI alternative are unhappy with the reporting, not the system of record. Here is how to tell which problem you have.
Replenishment planning that survives contact
Replenishment planning decides what to order, when, and how much. Here is the arithmetic, the four inputs that break it, and how to tell which broke.
Retail allocation: splitting one buy by store
How to split a single buy across stores: category demand scores, shelf capacity and pack rounding, the holdback, and reallocating on two weeks of data.
Retail audit: what POS answers, what needs a visit
Which retail audit checks POS answers without a store visit, which need a person in the aisle, and a 22-line checklist annotated with the split.
Retail seasonal planning off your own POS data
Build a seasonal index from your own POS history: when to pre-build, which week actually peaks, and the week to stop ordering for the season.
Tobacco buydown calculation, worked
A tobacco buydown pays per unit sold at the promoted price, not per invoice. How to compute it, reconcile it, and carry the timing gap honestly.
Vertical guides
Category-specific coverage: what SPINS sees (and misses) for pet, wellness & beauty, and beverage alcohol brands.
SPINS for Pet brands: coverage and gaps
SPINS has natural-channel pet coverage but Pet specialty (PetSmart, Petco, Chewy) sits outside the syndicated surface. Here's how Pet brands use SPINS.
SPINS for Wellness & Beauty: coverage gaps
Wellness and Beauty in SPINS have strong natural-channel attribution but Sephora, Ulta, and DTC sit outside. Here's where SPINS fits the brand journey.
SPINS for Beverage: the alcohol / non-alcohol split
SPINS' Beverage coverage diverges sharply between alcoholic and non-alcoholic. The regulatory environment shapes what's available. Here's the split.
Defending share of wallet against quick service
A method for measuring which occasions a c-store is losing to QSR and responding: occasion mapping, attach diagnosis and the traffic-versus-basket test.
Responding to GLP-1 demand shifts in assortment
What the GLP-1 research does and does not license you to conclude, and a method for testing whether the predicted shift is visible in your own categories.
How quick-service restaurants make money
A structural breakdown of QSR unit economics: prime cost, throughput, franchise fees and menu mix, and what each one means for a competing c-store.
AI & tooling
What AI-native analytics actually means for the CPG analyst stack, and how to evaluate vendor pitches without falling for the demo.
The AI-native CPG analyst stack: four layers
The working CPG analyst stack in 2026 has four layers: source, modeling, analysis, distribution. What goes in each, and where one tool wrecks the rest.
What is agentic AI for CPG analysts?
Agentic AI for CPG analytics is a specific claim, not a buzzword. This is what the term means once it touches SPINS data and a category-review deadline.
AI-native dashboards vs. BI: a buyer's guide
Most AI-for-CPG demos look the same in 30 minutes. Eight questions to put to a vendor that separate AI-native dashboarding from AI bolted onto BI.
Why "ask your data" is the wrong frame for CPG
"Ask your data" sells in a demo. For real CPG analyst work on SPINS data, it's the wrong frame. Here's what to ask for instead.
Buyer decisions
The tradeoffs that come up when you're picking tools: SPINS portal vs. dashboards, the spreadsheet tax, what to budget for.
SPINS portal vs. dashboard tools: what you give up
The SPINS portal does several things well. Five specific things it doesn't, and what a working CPG analyst loses by staying portal-only.
The hidden time cost of Excel-driven SPINS reporting
Excel SPINS reporting eats hours. Here's the visible plus invisible cost for one analyst over one year, with the math shown.
Gas station permits: the fuel-side stack
Gas station permits split into three systems with independent clocks: the inside-store stack, the underground tank system, and the dispensers at the pump.
How to get your product into retail stores
The real path onto a retail shelf: distributor versus direct, what a buyer needs to see, category review timing, and what the first year actually costs.
Licensing and permits for a new convenience store
The permit stack a new convenience store works through, which agency issues each, what order to file in, and the three that are commonly misunderstood.
Who can analyze your promo data? Five real options
In-house analyst, broker, consultant, TPM software, or AI platform? What each costs, when each fits, and the questions that separate them.