BEDROCK ANALYTICS

CPG Metrics Handbook v2.3

Channel-Wide · Cross-Retailer · Reference Guide

A working glossary of the CPG metrics we run on, taught from zero. Each entry covers what it means, how it's calculated, which pillar it lives in, what the buyer is really asking when they request it, and how a Bedrock analyst would use it in a real category conversation. Read it top-to-bottom for the full picture, or jump to whichever metric you're working with.
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Every CPG conversation runs on five pillars: Volume (how much did you sell?), Distribution (where are you on shelf?), Velocity (how productive is every store you're in?), Promotion (did the deal actually work?), and Pricing (where does your price land?). This handbook puts each metric in plain language — what it means, how it's calculated, what the buyer is really asking when they request it — so anyone reading a Bedrock chart can connect the number on screen to the decision it informs. These metrics apply across every channel — grocery, mass, club, c-store, drug, online. The retailer in the data shifts; the math doesn't.

Every metric is read against a time window. The window shapes the story. Use the shortest period that's still stable enough to read.

● L4W latest 4 weeks · momentum

● L13W latest quarter · trend

● L24W latest half · current activity

● L52W trailing year · annualized scale

● YTD calendar-year-to-date · planning

● W/E Week Ending · data refresh date

Rule of thumb: L24W or YTD for current performance, L52W only when annualizing an opportunity. Never mix windows in one chart without labeling.

Every metric in Bedrock has four columns: Current Period, Year Ago, Change vs. YA, and Pct. Change vs. YA. They turn a snapshot into a story.

Read pct change first, absolute change second. A 200% lift on a $100 base is a $200 win — interesting but small. A 10% lift on a $50M base is $5M — the real money. Both matter; the right answer depends on the question.

Negative YoY isn't always bad. Distribution can drop while velocity grows (you're shedding weak doors). Volume can fall while share grows (the category is shrinking around you). Always read at least two metrics together.

A common trap: % ACV at one retailer + % ACV at another retailer ≠ total % ACV. ACV is share-of-channel, not a stackable count. You can't add it across markets.

Even worse: the same brand will show different % ACV depending on the filter applied — brand-rollup ACV (every item under the brand) and 2-hero-SKU filter ACV produce different numbers. They're both correct, but they answer different questions.

Rule: pick one filter, apply it consistently across every market in a comparison, and label the filter in the chart eyebrow. The buyer will catch a mixed-filter chart.

Fast reference for the CPG language used throughout this handbook. Full definitions for the metric terms (ACV, TDP, etc.) appear in their own cards below.

● ACV: All Commodity Volume. The total dollar value of grocery/consumable sales in the market.

● TDP: Total Distribution Points. Sum of % ACV across all items in the brand's lineup.

● POD: Point of Distribution. One percentage point of ACV.

● SKU: Stock Keeping Unit. One distinct item (one flavor, one size, one pack count).

● UPC: Universal Product Code. The barcode-level identifier; one per SKU.

● EQ: Equivalent / Equivalized. Volume normalized to a standard pack size or single-serve unit.

● TPR: Temporary Price Reduction. A shelf-tag discount with no ad or display behind it.

● F&D: Feature & Display. A promotion supported by both an ad and a physical display.

● MULO: Multi-Outlet (grocery + drug + mass + club). The standard non-convenience channel cut.

● MULO+C: MULO plus convenience stores. The broadest channel cut.

● RMA: Retailer Market Area. A retailer's defined geographic footprint within a syndicated market.

● TA: Total Account. A retailer's full national footprint (e.g., Walmart Total US TA).

● W/E: Week Ending. The Saturday or Sunday date the data window closes.

● YA: Year Ago. The same time period in the prior year.

● YTD: Year-to-Date. From January 1 of the current calendar year through the latest available week.

● JBP: Joint Business Plan. The annual commercial plan between a brand and a retailer.

● Line Review: A retailer's periodic re-evaluation of which SKUs stay on shelf and which get cut.

● Modular / Planogram: The shelf diagram showing exactly where each SKU sits in a category section.

● Feature: An ad placement in a circular, weekly digital ad, or app.

● Display: A physical secondary placement (endcap, dump bin, pallet drop).

● Base Sales: Modeled sales as if no promotion had run. Provided by the syndicated data provider.

● Incremental Sales: Total Sales minus Base Sales. The volume attributable to promotion.

5 metrics · "How much did you sell?"

Pillar: Volume

DEFINITION

The total revenue a product generated, in dollars, across every store in the market over the time period. The most basic answer to "how much did we sell?", and the headline number on virtually every pitch deck.

CALCULATION

Total Dollar Sales = Σ (Units Sold × Price Paid)

Summed across every transaction in the defined market and time period. The "market" is whatever cut the data was pulled on — total US, a single retailer, a channel, a region.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How much have you sold?"

● You answer: Total Dollar Sales — the anchor of the entire conversation. Everything else (growth, share, margin, ROI) gets compared back to this number.

EXAMPLE · IN THE CATEGORY CONVERSATION

You sit down with a buyer and lead with "Year-to-date, we've done $36.5M at your chain." That single number anchors everything that follows. It tells the buyer the size of your business inside their four walls — not your national volume, not your factory output. From that anchor, every other metric in the meeting either expands the story (growth, share, lift) or qualifies it (Base vs. Promoted, distribution productivity). If you can't recite Total Dollar Sales to two significant digits cold, you don't get a second meeting.

Pillar: Volume

DEFINITION

The total number of physical units the product sold during the period. A "unit" depends on category — for beverages it's typically a can or bottle (or a multipack counted as one unit); for proteins it's a tray or pack; for produce sold by weight, it's a pound or kilogram. The data dictionary defines unit type per category; always confirm the unit definition before interpreting the number.

CALCULATION

Total Unit Sales = Σ (Units Sold per Transaction)

Dollar Sales ÷ Unit Sales = Average Price. The relationship links the two metrics and explains every "we did the same revenue but they sold five times the units" conversation. When pack sizes vary across the assortment (singles vs. multipacks vs. mega-packs), see EQ Sales (#3) for the normalized version.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How much physical product moved?"

● You answer: Total Unit Sales — the physical-volume answer. This is how buyers translate "revenue" into "shelf turns, foot traffic, basket size."

EXAMPLE · IN THE CATEGORY CONVERSATION

Two brands sit in front of the same buyer. Brand A: "$10M in sales." Brand B: "$10M in sales." Identical on paper. Now add units. Brand A did 1M units at a $10 average price. Brand B did 5M units at $2. The conversation transforms — Brand B moved five times the physical product, took up five times the shelf space, drove five times the foot traffic past the rest of the aisle. Buyers care about both numbers because their job is selling square footage, not selling dollars. Unit Sales is how you make the case that a low-ticket SKU is more valuable to the retailer than its revenue suggests.

Pillar: Volume

DEFINITION

Equivalent (EQ) Sales restates volume in a standardized unit size so brands with different pack configurations can be compared apples-to-apples. A 12-pack of 16oz cans does not equal a 24-pack of 8oz cans in physical product, even though both count as "one unit" in raw Unit Sales. EQ normalizes everything to a common baseline (typically a single-serve equivalent like an 8oz can, a single-serving bottle, or a defined ounce-equivalent).

EQ matters most in categories with wide pack variance — beverages, snacks, candy, frozen meals — where multipacks and mega-packs distort raw unit counts. It is what lets you say "Brand A moved 50% more equivalent units than Brand B" with a straight face when one brand sells 12oz singles and the other sells 6-pack sleeves.

CALCULATION

EQ Sales = Σ (Units Sold × EQ Conversion Factor per SKU)

The conversion factor depends on the category convention — typical conventions: beverages use an 8oz-equivalent or single-serve equivalent; salty snacks use a 1oz-equivalent; some categories use SSU (Standard Statistical Unit). Available in dollar (EQ Sales) and unit (EQ Units) versions, plus EQ Base, EQ Incremental, EQ Promoted, and EQ Price variants for the full promo split.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How do you compare to competitors with different pack sizes?"

● You answer: EQ Sales / EQ Units — volume normalized to a standard pack equivalent. The only fair way to compare a single-can brand to a multipack brand to a mega-pack value brand.

EXAMPLE · IN THE CATEGORY CONVERSATION

You're pitching a buyer with a 12-pack of 16oz cans. A competitor leads with a single 12oz can. Buyer looks at Total Units: competitor sold 53,387 units, you sold 10,000. On the surface, they crushed you. Now overlay EQ Sales. Your EQ Sales: 19,384 equivalent units (because each pack contains 12 single-serve equivalents). Competitor's EQ Sales: 53,387 (one can = one equivalent). The gap closes from 5x down to roughly 3x — still a real difference, but a fair comparison. EQ Sales is the only metric that lets you have an honest conversation about volume when pack sizes diverge.

Pillar: Volume

DEFINITION

Your brand's dollar sales as a percentage of total category dollar sales in the market. It's the headline competitive scoreboard — the answer to "how big are you relative to the category?". A 12% Dollar Share in proteins at a given retailer means twelve cents of every dollar spent on proteins at that retailer goes to your brand.

Share is what makes growth real. Total Dollar Sales can rise while Share is shrinking (you're growing slower than the category) — and Share can rise while Total Dollar Sales is flat (the category is shrinking around you, but you're holding strong). Always read them together.

CALCULATION

Dollar Share = Brand Dollar Sales ÷ Category Dollar Sales × 100

The category definition matters. Share within total category will differ from share within a subcategory or segment. Always confirm the denominator the data is using before quoting a share number.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "What slice of my category are you capturing?"

● You answer: Dollar Share — the percentage of category $ sales your brand owns. The metric that turns "are you growing?" into "are you taking from competitors or just riding the category?".

EXAMPLE · IN THE CATEGORY CONVERSATION

You walk into a category review having grown Total Dollar Sales by 8% year-over-year. Sounds great — until the buyer pulls Dollar Share and sees it dropped from 12.0% to 11.3%. The category grew 15% that year. You grew, but you grew slower than the category, which means you actively lost share to faster-moving competitors. The buyer's question shifts from "congratulations on the growth" to "what's your plan to recapture share?". Total Dollars without Share is half a story; with Share it's the full picture of whether you're winning or just along for the ride.

Pillar: Volume

DEFINITION

Your brand's unit sales as a percentage of total category unit sales. The same idea as Dollar Share but counting physical product, not dollars. The interplay between Dollar Share and Unit Share is one of the most diagnostic comparisons in CPG.

When Dollar Share > Unit Share, you're commanding a premium — you're capturing a bigger slice of revenue than of volume, which means you're priced above category average. When Unit Share > Dollar Share, you're playing value — you're moving more units than your revenue share would suggest, which means you're priced below average. Same competitive footprint, fundamentally different pricing strategies.

CALCULATION

Unit Share = Brand Unit Sales ÷ Category Unit Sales × 100

Read Dollar Share and Unit Share together. The gap (or alignment) between them reveals more about your pricing position than any single price metric can. In categories with wide pack variance, compare against EQ Unit Share for the cleanest read.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "What share of physical product do you represent in my category?"

● You answer: Unit Share — your share of category volume. Always compare to Dollar Share: if Dollar Share is higher, you're priced premium; if Unit Share is higher, you're priced value. One sentence, full pricing strategy.

EXAMPLE · IN THE CATEGORY CONVERSATION

Two brands sit in the same category. Brand A: 12% Dollar Share, 8% Unit Share. Brand B: 8% Dollar Share, 12% Unit Share. They look like equals on competitive footprint, but they're running fundamentally different playbooks. Brand A is a premium player — capturing more revenue per unit, fewer units overall. Brand B is a value player — more units, lower revenue per. When a buyer asks "what's your strategy?", you can answer in one sentence using just these two numbers. And when you're proposing a price change, the gap between Dollar and Unit Share tells you how much room you have to move before you flip your category position.

6 metrics · "Where are you on shelf?"

Pillar: Distribution

DEFINITION

ACV stands for "All Commodity Volume" — the total dollar value of grocery and consumable sales flowing through the retailer or channel in scope. Percent ACV tells you what share of that total dollar volume runs through stores that carry your product. It's distribution weighted by store size, not by store count.

This is the most important distribution metric in CPG, and the one most people get wrong on first pass. A brand can be in 200 stores at 10% ACV (the 200 are small) or in 200 stores at 80% ACV (the 200 include the biggest doors in the chain). ACV tells you the quality of your distribution.

Critical pitfall: % ACV doesn't sum across markets — see the "ACV Doesn't Sum" note at the top of this handbook.

CALCULATION

% ACV = Σ ($ Volume of stores carrying the product) ÷ Σ ($ Volume of all stores in the market) × 100

Provided by Circana/Nielsen as a single 0–100 percentage. The market scope is defined by the data cut. Same brand will read different % ACV under different filters (brand-rollup vs. SKU-subset) — confirm the filter before quoting.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "Where are you on shelf in my channel today?"

● You answer: Percent ACV — the dollar-weighted measure of which doors are actually carrying you. Always read this before talking velocity or volume; it sets the size of the opportunity.

EXAMPLE · IN THE CATEGORY CONVERSATION

Two competing protein brands sit across the table from the same buyer. Brand A says "We're in 3,000 stores." Brand B says "We're in 3,000 stores." The buyer shrugs — store counts are equal. Then they pull % ACV. Brand A: 45% ACV. Brand B: 78% ACV. Same store count, but Brand B is in the supercenters and high-volume doors while Brand A is anchored in smaller locations. Now the conversation pivots: Brand A's argument becomes "give us your bigger stores," and Brand B's becomes "defend our high-quality footprint." ACV is the lens that turns "where are you?" into a strategy conversation.

Pillar: Distribution

DEFINITION

TDP combines two distribution ideas — how widely a brand is distributed (% ACV) and how many items it has on shelf — into one number. A brand with 4 items each at 60% ACV has 240 TDPs. TDP is how a buyer measures your total real estate in their channel.

Where % ACV asks "are you on shelf?", TDP asks "and how many of your items?". A single SKU at 100% ACV is 100 TDPs. Ten SKUs at 50% ACV each is 500 TDPs — five times the shelf presence.

CALCULATION

TDP = Σ (% ACV of each item in the brand's lineup)

TDP can appear at the brand, manufacturer, or category level. Note that TDP is also the denominator for the Velocity metric "Sales per TDP" (#14) — the same number, different role.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How much total shelf presence do you have in my chain?"

● You answer: TDP — the full scope of your footprint, accounting for both store quality (% ACV) and assortment depth (item count) in a single number.

EXAMPLE · IN THE CATEGORY CONVERSATION

You're walking the buyer through your portfolio growth. Last year your brand had 3 items at 50% ACV — 150 TDPs. This year you added 2 SKUs and expanded distribution: 5 items at 65% ACV — 325 TDPs. That's a 117% gain in shelf presence year-over-year — a single number that bundles "you authorized more items" and "we got into more of your stores" into one digestible story. TDP is the metric that makes assortment expansion conversations win.

Pillar: Distribution

DEFINITION

The raw count of stores that registered at least one sale of the product during the time period. The key word is selling, not authorized or stocked. A store can be in your authorization list, have inventory in the back room, and still ring zero sales — those stores are excluded here.

CALCULATION

# Stores Selling = count of distinct stores with ≥ 1 unit sold in the period

Compare to the retailer's total authorized footprint to identify "phantom doors" — stores that should be selling but aren't.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How many of my stores are actually moving your product?"

● You answer: # of Stores Selling — the unweighted door count. Pair it with the buyer's authorized count to see if any stores are missing the product or sitting on dead inventory.

EXAMPLE · IN THE CATEGORY CONVERSATION

The buyer hands you their authorization file: "You're approved in 4,500 of my stores." You check your data and see # of Stores Selling = 4,121. There's a 379-store gap — almost 9% of your authorized doors aren't moving any product. Now you have three possibilities to investigate: shelf execution failure (you're authorized but the product never got onto the planogram), out-of-stocks (the product was on shelf but supply gaps killed sales), or a regional demand issue. # of Stores Selling is how you find the difference between what's on paper and what's in carts.

Pillar: Distribution

DEFINITION

# of Stores Selling expressed as a share of all stores in the market. Unlike % ACV, this is unweighted — every store counts equally, whether it's a flagship supercenter or a small-format store. It's the cleanest measure of raw penetration.

The interplay between % Stores Selling and % ACV is one of the most useful diagnostics in CPG. They should track together; when they diverge, something interesting is happening.

CALCULATION

% Stores Selling = # of Stores Selling ÷ Total Stores in Market × 100

Different from % ACV: % Stores Selling counts doors equally; % ACV weights doors by dollar volume.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "What's your raw penetration across my chain?"

● You answer: % of Stores Selling — door count as a share of the chain. Always compare against % ACV: if % ACV exceeds % Stores Selling, you're in the bigger stores; if it's reversed, you're stuck in smaller doors.

EXAMPLE · IN THE CATEGORY CONVERSATION

You're in 83% of stores but at 91% ACV. The 8-point gap tells the story: the stores you're missing are small-format locations that don't move much volume anyway. You can comfortably argue this is a healthy distribution profile — you're in the doors that matter. Compare to a brand that's 91% Stores Selling but only 72% ACV — they're in more doors but the wrong ones. They look broad on paper, but they're missing the high-volume stores where the category actually wins. Two numbers, four words of analysis, complete picture.

Pillar: Distribution

DEFINITION

The average number of distinct SKUs the brand sold per store during the period. If you have 8 total SKUs in your lineup but Average # of Items is 5.5, the typical store is carrying about two-thirds of your assortment.

This is your assortment compliance metric. The gap between your authorized SKU count and the average actually-stocked count is a direct measure of in-store execution.

CALCULATION

Avg # of Items = Σ (Distinct SKUs sold per store) ÷ # of Stores Selling

A SKU is counted in a store if it rang at least one sale. The metric is sensitive to time window — short windows can understate the true average because of low-velocity SKUs that didn't sell that week.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How many of your SKUs are actually on shelf per store?"

● You answer: Avg # of Items — the typical SKU count per door. The delta between this and your authorized SKU count is where the buyer learns whether your reps are executing the modular as promised.

EXAMPLE · IN THE CATEGORY CONVERSATION

You sold the buyer on a 6-SKU set during the last line review. Six months later, your data shows Avg # of Items = 4.2. That means the average store is carrying about 70% of what was authorized. The buyer's first reaction will be skeptical — but you can turn it: "Two of our six SKUs are velocity laggards we already flagged for review. Looking at the four we're confident in, every store has them. Let me come back with a swap proposal for the bottom two so we can drive the average closer to 6." This metric is how you head off the "your SKUs aren't earning their space" conversation before the buyer brings it.

Pillar: Distribution

DEFINITION

The count of weeks within the time period during which the product had at least one sale. In a YTD pull spanning 20 weeks, a perfect-distribution product reads 20 of 20. Anything less signals a gap — most commonly an out-of-stock, but also a distribution drop, a discontinuation event, or a seasonal SKU.

CALCULATION

# Weeks Selling = count of weeks with ≥ 1 unit sold across the brand

Read at the brand or item level. Item-level # Weeks Selling is the cleanest out-of-stock indicator — if a single SKU drops from 20/20 to 12/20, you have a supply problem on that item.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "Are you in-stock every week? Any execution issues?"

● You answer: # of Weeks Selling — at the SKU level, the cleanest read on supply-chain reliability. Any item below the full period count signals an investigation worth doing before the buyer asks.

EXAMPLE · IN THE CATEGORY CONVERSATION

You walk in confident. The buyer pulls your data and says, "One of your hero SKUs only sold in 14 of the last 20 weeks. What happened?" If you don't already know, you've lost the meeting. If you do — "Yes, our co-packer had a 6-week capacity issue in Q1. It's resolved, and we'll cover the volume gap with a Q2 promo replacement." — you keep the relationship. # of Weeks Selling is the metric that surfaces the questions buyers ask before they ask them. It's also worth watching as a data integrity check: a drop in # Weeks Selling without a known supply event is a signal to investigate the data pipeline before you investigate operations.

5 metrics · "How productive is every store you're in?"

Pillar: Velocity

DEFINITION

A "Point of Distribution" is one percentage point of ACV — the share of the channel's dollar volume flowing through stores selling your product. If your product is in stores together representing 40% of the channel, you have 40 Points of Distribution.

Sales per Point of Distribution tells you how much revenue (or how many units) you generate for every percentage point of that distribution. It's a productivity score that strips out the size of your retail footprint, so you can compare a brand in 10% of the channel against one in 90% on a level playing field.

CALCULATION

$ Sales per POD = Total Dollar Sales ÷ % ACV Distribution

Available in dollar and unit versions. The denominator is on a 0–100 scale; a product in stores representing half the market has a POD value of 50.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How productive are your existing doors?"

● You answer: Sales per POD — revenue per percentage point of ACV. Strips out footprint size; lets a small brand make the productivity case against a larger competitor.

EXAMPLE · IN THE CATEGORY CONVERSATION

You want the buyer to expand your distribution. Today you're in 30% of their stores and generated $3M — that's $100K per POD. Your closest competitor is in 90% of stores and did $6M — only $67K per POD. Their dollar number is bigger, but you're 50% more productive per door. The argument writes itself: "Give us the other 70% of your store base and at our current velocity we'd do roughly $10M — without cannibalizing your existing partner." Sales per POD is how small brands punch above their weight in a distribution expansion conversation.

Pillar: Velocity

DEFINITION

Total sales normalized per million dollars of market opportunity. Same productivity question as Sales per POD, but expressed on a different denominator scale — useful when comparing performance across markets of wildly different sizes (e.g., between retailers, between regions, or between channels).

CALCULATION

$ Sales per Million = Total Dollar Sales ÷ (Category $ ACV × % ACV Distribution) × 1,000,000

Available in dollar and unit versions. The exact denominator depends on the syndicated data provider's convention; the concept is the same: normalize sales to the dollar value of the distribution you have access to.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How do you perform across retailers of different sizes?"

● You answer: Sales per Million — productivity normalized to opportunity size. The fair-comparison metric across retailers, channels, and regions.

EXAMPLE · IN THE CATEGORY CONVERSATION

A brand manager wants to compare how a SKU performs across two retailers of very different sizes. Comparing raw dollars makes the bigger retailer always look better — even if the SKU is actually dragging there. Sales per Million strips out the size difference. If the SKU indexes higher per million at the smaller retailer, you're getting more revenue from every million dollars of opportunity there — a sign the SKU is a stronger fit at that retailer and underperforming at the larger one relative to its potential. That insight never shows up in raw totals.

Pillar: Velocity

DEFINITION

Sales per TDP is the cleanest measure of per-item-per-distribution productivity. It controls for both how many items you sell and how widely you sell them — making it the fairest item-level comparison across competitors of different sizes and assortment depths.

If Sales per POD answers "how productive are your doors?", Sales per TDP answers "how productive is each SKU within each point of distribution?". The former is brand-level; the latter is item-level.

CALCULATION

$ Sales per TDP = Total Dollar Sales ÷ TDP

Available in dollar and unit versions. Base variants strip out promotional lift — useful when you want to know how productive each TDP is at everyday shelf-price velocity.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "Is every SKU pulling its weight? Should I rationalize any?"

● You answer: Sales per TDP at the SKU level — the fairest cross-item comparison. Outliers on the low end are the candidates for rationalization (or repositioning).

EXAMPLE · IN THE CATEGORY CONVERSATION

A buyer asks the most dangerous question in CPG: "You have 8 SKUs on my shelf. Should I drop two?" If you only know dollar sales, you can't answer well — your big SKUs will look great and your small SKUs will look weak, but you'll have no way to compare. Now bring in Sales per TDP. SKU A: $50/TDP. SKU B: $52/TDP. SKU C: $9/TDP. SKU D: $11/TDP. Suddenly the answer is obvious: "Drop C and D. They're underperforming the assortment by 5x, and the shelf space they're taking would generate more revenue rotated into a new flavor or a multipack of SKU A." Sales per TDP is how you survive line reviews.

Pillar: Velocity

DEFINITION

The average sales generated by each store that actually sold the product at least once during the period. The crucial word is "selling" — this denominator excludes stores in the retailer's footprint that could have carried the product but didn't, and it excludes stores that were stocked but never rang a sale (a sign of execution failure or zero demand).

CALCULATION

$ per Store Selling = Total Dollar Sales ÷ # of Stores Selling

Available in dollar and unit versions. Compare to a hypothetical "$ per Store Authorized" to see what share of your authorized doors are actually moving product.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How much does each of my stores actually generate for you?"

● You answer: Sales per Store Selling — average revenue per active door. The number that makes the case for facings, expansion, or premium placement.

EXAMPLE · IN THE CATEGORY CONVERSATION

You walk into a category review. The buyer says, "You're in 3,000 of my stores." You say, "Yes — and Sales per Store Selling is $8,860." That single number is your weapon. If the average competitor is doing $3,000 per store selling and you're doing $8,860, you can argue for more facings, better placement, or expansion into the remaining doors — because every additional store you add will perform like an $8,860 store, not a $3,000 one. This metric is how reps win shelf battles without ever having to badmouth a competitor: "Our doors are simply more productive than the rest."

Pillar: Velocity

DEFINITION

The single most important velocity number in CPG. It tells you how much one store, on average, rings up in one week — for your brand. Normalizes for time, footprint, and item count all at once, which is why every category manager and every buyer reaches for it first.

The family has variants for total sales vs. base-only sales (excluding promo lift), and per-item versions for evaluating SKU productivity inside an assortment.

CALCULATION

$ per Store per Week = Total Dollar Sales ÷ # of Stores Selling ÷ Weeks in Period

The per-item variant divides by an additional factor — the average number of items each store carried — to express the velocity of a single SKU in a single store in a single week.

THE SIX VARIANTS

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "What's your everyday velocity? Are you really moving without all the promo?"

● You answer: Sales per Store per Week — pair total with the Base variant. A tight gap between the two means the brand is moving at full price, not renting velocity through discounts.

EXAMPLE · IN THE CATEGORY CONVERSATION

Brand walks into a category review at $615 per store per week. Buyer pushes back: "That's because you were on promo every other week." Brand pulls up Base $/Store/Week = $612. Game over — the buyer just learned that this brand barely needs promotion to hit that velocity. Same store, same week, but only $3 of the $615 comes from promotional lift. Compare to a brand doing $500/store/week with a Base of only $300 — that brand's whole story is built on the deal. Sales per Store per Week with its Base variant is the lie-detector test of any pitch deck.

4 metrics · "Did the deal actually work?"

Pillar: Promotion

DEFINITION

Base Sales represent what the product would have sold at its everyday, non-promoted shelf price — the "do nothing" volume. It is not a number you can read off a register; it's a modeled estimate produced by Circana/Nielsen, which holds aside promotional weeks and uses the steady-state velocity to project what would have happened without any deal activity.

CALCULATION

Base Sales = Total Sales − Incremental Sales

Available in dollar and unit versions. Base is the syndicated data provider's modeled output — not a direct measurement. Different providers use slightly different models; the concept is identical: strip out the promotional bump and look at the trend underneath.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "What does your business look like without the deals?"

● You answer: Base Sales — the modeled non-promoted baseline. The buyer's measure of whether you have real everyday demand or are renting volume from trade dollars.

EXAMPLE · IN THE CATEGORY CONVERSATION

A buyer doesn't want to fund growth that disappears the moment promo stops. So they always ask the same question: "What does your business look like without the deals?" Your answer is Base Sales. If your Base Dollar Sales is $93M and your Total is $94.5M, you're a stable brand with healthy everyday demand — only $1.5M of your business depends on promotional activity. Now imagine you said Base = $30M on $94.5M total. Two-thirds of your revenue depends on discounts. That's a much harder pitch — the buyer correctly suspects you're renting volume, not building a brand.

Pillar: Promotion

DEFINITION

The sales that happened because of a promotion — and only because of it. Incremental Sales is the volume above and beyond what would have sold at everyday shelf price. It is the true return on every dollar of trade spend.

Critical distinction: Promoted Sales ≠ Incremental Sales. A lot of what sells during a promotion would have sold anyway. Incremental isolates the lift.

CALCULATION

Incremental Sales = Total Sales − Base Sales

Available in dollar and unit versions. Incremental is essentially always positive during a promotional window. Where you sometimes see surprising or negative values is in post -promo periods — a heavy deal can pull future demand forward, leaving the following weeks softer than the modeled Base.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "Did the promotion actually pay for itself?"

● You answer: Incremental Sales — the true new volume generated above baseline. The ROI denominator for every trade dollar spent.

EXAMPLE · IN THE CATEGORY CONVERSATION

You ran a four-week feature ad. During those four weeks, you sold $2M of product. Promoted Dollar Sales = $2M. Buyer is impressed. Then they ask the right question: "How much of that was incremental?" Your data says Incremental Dollar Sales = $400K. The other $1.6M would have sold anyway, just at full price. Now the buyer is doing the trade math: "You gave up margin on $2M of product to gain $400K of true new volume." Every promotion has to pass that test. If Incremental is high relative to the discount you took, the promotion was a win. If Incremental is low, you funded a discount on volume that was already yours. Incremental is the only number that tells you which one happened.

Pillar: Promotion

DEFINITION

Total sales that occurred while the product was on some form of promotion. This is the gross "with deal" number, before you isolate what was truly incremental. Promoted Sales is split by the type of promotional tactic in effect — Display, Feature, Feature & Display together, or a TPR (Temporary Price Reduction) alone.

CALCULATION

Promoted Sales = Σ Sales while any promo flag was active

Each variant filters to a specific tactic flag. Promoted Sales is gross sales during promo periods (mostly base, some lift); Incremental Sales isolates only the lift.

THE FIVE VARIANTS

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How does each promotional tactic perform for you?"

● You answer: The Promoted Sales family — sales split by tactic. Pair with Incremental Sales to compute efficiency per tactic (which tactic delivered the most lift per dollar of discount).

EXAMPLE · IN THE CATEGORY CONVERSATION

You're proposing next year's promo calendar. The buyer wants to know which tactic to run. You pull last year's variants: Promoted with Feature & Display drove $3.1M. Promoted with TPR only drove $300K. On the surface, Feature & Display crushed it. But then you overlay Incremental: F&D was $700K incremental on $3.1M (23% of sales were truly new), while TPR was $280K incremental on $300K (93% incremental). Per dollar of promotional cost, the humble TPR was actually more efficient. That's the conversation the variants enable — and it's how trade dollars stop getting wasted on splashy support that mostly subsidizes loyal customers.

Pillar: Promotion

DEFINITION

Percent Lift over Base expresses Incremental Sales as a percentage of Base Sales. It's the standardized score for "how much did this promotion juice the business above the baseline?" — and it's how brands compare promotions across SKUs, retailers, weeks, and tactics on a single scale.

CALCULATION

% Lift over Base = (Incremental Sales ÷ Base Sales) × 100

Available in dollar and unit versions. A negative % Lift means the promotion cannibalized base business or that base sales fell during the promo period — a red flag worth investigating.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "Compare these three promotions for me — which one worked best?"

● You answer: % Lift over Base — the universal apples-to-apples scoring metric. Works across SKUs, retailers, weeks, and tactics. Higher = better, with diminishing returns past ~100% lift.

EXAMPLE · IN THE CATEGORY CONVERSATION

You're in a Joint Business Planning (JBP) session, and the buyer wants to compare the ROI of your last three promotions. You can't just stack the dollar totals — each promotion was on different SKUs, in different weeks, at different price points. So you bring up % Lift over Base. Promo A: +34% lift. Promo B: +82% lift. Promo C: −2% lift. The conversation writes itself. Promo B was a hit — run it again. Promo A was solid. Promo C was a failure that you'd never have spotted from the dollar totals alone. % Lift is the universal yardstick that makes promotions comparable, so you and the buyer can stop arguing about which deal "felt" successful and start running the ones that actually were.

3 metrics · "Where does your price land?"

Pillar: Pricing

DEFINITION

The blended price a shopper paid per unit, on average, over the period. Average Price is not a sticker price — it's the result of every transaction divided into every unit sold. If half the units sold full-price at $5 and half sold on promotion at $3, the Average Price is $4.

The family has seven variants because retailers run several types of promotions, and we often need to isolate the realized price under each tactic. Together they tell the full story of how a brand prices itself — both at everyday shelf and when supported with promotional activity.

CALCULATION

Average Price = Total Dollar Sales ÷ Total Unit Sales

Each variant uses the same formula but filters numerator and denominator to a specific promotional state (e.g., units sold while on a Feature ad). The "Base" variant filters to sales with no promotional support — effectively the everyday shelf price. For categories with wide pack variance, see EQ Price (#22) for the pack-normalized version.

THE SEVEN VARIANTS

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "How aggressive are you on price? What's the read on your promo discipline?"

● You answer: Average Price with the Base/Promoted splits — reveals whether the brand is protecting price equity or buying volume through discounts. A small gap between Base and Promoted = brand strength. A wide gap = promo dependency.

EXAMPLE · IN THE CATEGORY CONVERSATION

You're presenting your beef entrée line. Average Price = $11.27. Buyer asks, "How aggressive are you on promo?" You pull up the variants. Base = $11.32. Promoted = $11.21. The buyer sees that even when you discount, you barely move price — you're protecting the brand. Compare that to a competitor whose Base is $9.00 but Feature & Display Promoted Price is $5.50 — that brand is buying volume through discounts. The Average Price family is how a buyer reads your pricing philosophy without you having to explain it.

Pillar: Pricing

DEFINITION

The Equivalent Price — the price per standardized unit (e.g., per 8oz can equivalent, per 1oz of snack, per single-serve) rather than per the as-sold pack. EQ Price is the only honest way to compare pricing across brands selling different pack configurations.

A 12-pack and a single can might both be "one unit" in raw data, but the shopper is buying twelve times the product in the multipack. Without EQ Price, the multipack looks expensive ($15 vs. $2). With EQ Price, both come out to roughly $1.25 per can — the actual apples-to-apples read.

CALCULATION

EQ Price = Total Dollar Sales ÷ EQ Total Unit Sales

Same formula structure as Average Price, but the denominator is in equivalized units. EQ Price is most useful in categories with wide pack variance (beverages, snacks, candy). Like Average Price, it has Base / Promoted / Display / Feature / F&D / TPR variants where the syndicated data provider tracks them.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "Are you actually priced higher than the value brand, or does it just look that way?"

● You answer: EQ Price — the per-standard-unit price. The number that strips out pack-size effects and reveals true pricing position.

EXAMPLE · IN THE CATEGORY CONVERSATION

You sell a premium energy drink in a 16oz can at $3.49 per can. A competitor sells a 12-pack of 12oz cans at $15.99. On the shelf, the multipack looks dramatically cheaper. But run the EQ math: your EQ Price (per 8oz) = $1.75. Their EQ Price (per 8oz) = $0.89. They're roughly half your price per ounce, not 1/4 like the shelf tag suggests. Now you have a real conversation: "Yes, we're priced 2× per equivalent serving — that's our premium positioning. Here's the velocity data showing shoppers pay the premium." EQ Price is how you avoid getting blindsided in a price-gap conversation.

Pillar: Pricing

DEFINITION

The realized price during periods when no promotional flag was active — display, feature, or TPR. It is a direct observation: the average price across the weeks where the product was being sold purely at everyday shelf price.

This is close to, but methodologically distinct from, Average Price – Base (#21). Average Price – Base is a modeled baseline — it uses the syndicated data provider's algorithm to extract the implied non-promoted price even from weeks where some promotional activity ran. Non Promoted Price is observed — it's the actual realized average during clean (non-promo) weeks. They're usually very close. When they diverge meaningfully, the gap is worth investigating: it usually points to a modeling assumption that doesn't match the brand's actual behavior.

CALCULATION

Non Promoted Price = Σ ($ sales in non-promo weeks) ÷ Σ (units in non-promo weeks)

Read alongside Average Price – Base. If they match within a few cents, the Base model is well-calibrated for this brand. If Non Promoted Price is materially higher than Base, the Base model is over-correcting (subtracting more "implied lift" than the brand actually has). If lower, it's under-correcting.

THE BUYER ASKS · YOU ANSWER

● Buyer asks: "What's your actual everyday price — not the modeled one?"

● You answer: Non Promoted Price — the directly observed price during clean weeks. The audit-trail version of "everyday price" that doesn't depend on any model assumption.

EXAMPLE · IN THE CATEGORY CONVERSATION

A buyer is skeptical of your modeled Base numbers. "How do I know your 'base price' isn't just whatever Circana decides it should be?" Fair question. You bring up the comparison. Average Price – Base: $3.51. Non Promoted Price: $3.51. Identical to the cent. "Here's the observed price in weeks when we ran zero promo, and here's the modeled base. They agree." Now the buyer trusts both numbers. Non Promoted Price is the credibility check on the entire Base/Incremental framework — and on the rare occasion where they diverge, you've spotted a data-quality issue worth flagging before it shows up as a surprise in someone else's deck.

Bedrock Analytics · CPG Metrics Handbook v2.3 · Last updated June 2026 · Owner: Analytics Team