The Full Glossary
All 40 terms, in plain English.
Every definition from the explorer above, written out — what it means, how to judge it, the rookie mistake, and the question your VP will ask. Bookmark it; nobody remembers all 40.
The Table Metrics
Dollar Sales
Plain English: Total money through the register for this brand, in this geography, in this period. The number everyone quotes first — and the one that says the least on its own.
Is my number good? No 'good' absolute number — size depends on the category. What matters is trajectory (vs. year ago) and share (vs. the category). A big brand shrinking is in worse shape than a small brand doubling.
Rookie mistake: Quoting dollar sales without growth or share next to it. "We did $387M" means nothing until you say whether that's up, down, or losing ground to the category.
The question your VP will ask: "Is that growth coming from price, volume, or distribution?"
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Dollar % Change vs. Year Ago
Plain English: How much dollar sales grew or shrank versus the same period last year. The single most-watched number in any review.
Is my number good? Compare to the category, not to zero. This category grew +5.0% — growing +3% here means losing ground. Above category = gaining share; below = donating it.
Rookie mistake: Celebrating growth that's slower than the category. +3% in a +5% category is share loss wearing a party hat.
The question your VP will ask: "How does that compare to the category?"
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Unit Sales
Plain English: How many physical things sold — no pricing layer. The reality check behind every dollar number.
Is my number good? Judge the trend, not the level. Units up alongside dollars = real demand. Dollars up while units fall = price is doing the work, and that's fragile.
Rookie mistake: Never opening the units column. In an inflationary year, dollar growth with falling units is the most common hidden bad news in CPG.
The question your VP will ask: "Is the growth real — or just price?"
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Unit % Change vs. Year Ago
Plain English: Volume growth versus last year. Strip out price and this is what's left: are more things actually leaving shelves?
Is my number good? Positive = healthy demand. Negative while dollars grow = price-led growth (fragile). Negative alongside falling dollars = a brand in real decline.
Rookie mistake: Reporting dollar growth and unit decline in separate slides so nobody connects them. Put them side by side — the gap IS the story.
The question your VP will ask: "What happens to dollars if we can't take price again next year?"
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Average Price per Unit
Plain English: Dollars divided by units — what shoppers actually paid on average, promotions included. Not the shelf tag: the blended, real-world price.
Is my number good? No universal good number — compare to the brand's own year-ago price and to category position (value vs. premium). Watch the *change*: big jumps explain dollar growth; big drops explain 'volume wins.'
Rookie mistake: Confusing average paid price with shelf price. Heavy promotion drags the average down — a brand can raise shelf price and still show a falling average if it's deep in deals.
The question your VP will ask: "Are we growing because shoppers want us, or because we got more expensive?"
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%ACV Distribution
Plain English: The share of the market's stores that stock you — weighted by store size, so one supercenter counts far more than one corner shop. ACV = All Commodity Volume.
Is my number good? Rule of thumb: 80%+ = broadly distributed (growth must come from velocity); 40–80% = room to grow doors; under 40% = a distribution play, not a marketing play. Premium niche brands often sit low on purpose.
Rookie mistake: Treating share loss as a marketing problem before checking ACV. If distribution fell, you lost shelf — no campaign fixes that.
The question your VP will ask: "Are we in enough of the right doors — and what would one more point of ACV be worth?"
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Total Distribution Points (TDP)
Plain English: %ACV summed across every item you sell — breadth × depth in one number. Two brands at equal ACV are not equal if one has eight items on the shelf and the other has two.
Is my number good? Judge TDP change against sales change. Sales growing faster than TDP = stronger productivity. TDP growing faster than sales = you're adding shelf faster than demand — velocity is diluting.
Rookie mistake: Calling it momentum when sales grow exactly as fast as TDP. That's expansion, not demand — strip distribution out before you take a bow.
The question your VP will ask: "Is the new distribution actually productive, or are we just spreading the same demand thinner?"
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Velocity (Sales per Point of Distribution)
Plain English: How fast you sell where you're actually sold: dollars divided by distribution. The great equalizer — a small brand can beat a giant here, and retailers watch it when deciding who keeps the shelf.
Is my number good? Compare within the table: category-average velocity here is ~$1,016K per TDP. Well above = earning your shelf (or under-distributed); well below = at risk in the next category review.
Rookie mistake: Comparing velocities of brands at wildly different ACV without saying so. A brand in its best 30% of stores will out-velocity one in 90% — note the distribution gap or the comparison is meaningless.
The question your VP will ask: "If the retailer cut our slowest items tomorrow, which ones go — and what's our argument?"
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Dollar Share
Plain English: Your slice of the category's dollars. The scoreboard metric — moves slowly, hides everything interesting in the layers beneath it.
Is my number good? A share *point* in this category is worth ~$12.4M. Judge share by its trend and by where it's going: share lost to a premium rival means something different than share lost to private label.
Rookie mistake: Reporting share to two decimals while ignoring that the category itself is shrinking. 30% of a declining category is a melting iceberg with good optics.
The question your VP will ask: "Who exactly are we losing to — and in which channel?"
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Any Promo $ %
Plain English: The share of this brand's dollars sold with some kind of deal attached — the promo-dependence gauge.
Is my number good? Under 20% comfortable · 20–35% watch it · over 35% the brand may be training shoppers to wait for deals. Always sanity-check against the category norm.
Rookie mistake: Judging promo levels in a vacuum. If the whole category deals heavily, a 'high' number may simply be table stakes.
The question your VP will ask: "What happens to volume if we pull promo back 10 points?"
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The Data Itself
Syndicated Data
Plain English: Market data collected once by a research provider and sold to many subscribers — versus custom research done for one company. The shared scoreboard the whole industry argues from.
How to judge it: Coverage varies by provider and contract: channels included, retailers shared, market definitions. Always ask what your number does and doesn't include before you compare anything.
Rookie mistake: Assuming your 'Total US' equals someone else's 'Total US.' Different providers, different store lists, different totals.
The question your VP will ask: "Whose data is this, and what's not in it?"
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Retail Measurement / POS
Plain English: Store-side data built from point-of-sale scanner feeds: what sold, where, at what price. Answers 'what happened at the shelf.' Every column in this table is retail measurement.
How to judge it: Strong for sales, share, distribution, price, promo response. Silent on who bought and why — that's panel territory.
Rookie mistake: Calling POS data 'panel.' Panel means household consumer data — the two are different pipelines and their numbers never match exactly.
The question your VP will ask: "Is this a store-side read or a shopper-side read?"
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Consumer Panel Data
Plain English: Household-side data from people who record every purchase they make — answering who bought, how often, and what else is in the basket. The 'why' engine behind the POS 'what.'
How to judge it: Built from large opt-in household samples balanced to census demographics, then projected. Smaller samples than POS — treat small-brand panel reads with care.
Rookie mistake: Averaging POS and panel numbers when they disagree. Different lenses, different methods — quote them separately and explain the gap.
The question your VP will ask: "Are we losing buyers, or are buyers spending less?"
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Time & Trend
vs. YA (Year Ago)
Plain English: The comparison to the same period last year. The default anchor for every CPG trend, because it cancels out seasonality.
How to judge it: Always present. A number without a YA comparison is a fact without a verdict.
Rookie mistake: Saying 'up vs. last month' in a seasonal category. January vs. December tells you about holidays, not about your brand.
The question your VP will ask: "And how does that compare to a year ago?"
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L52W / L12W (Latest 52 / 12 Weeks)
Plain English: The two standard time windows: latest 52 weeks (the year-long view) and latest 12 weeks (the recent trend). Read together, they tell you if things are getting better or worse.
How to judge it: 12-week trend stronger than 52-week = improving. Weaker = deteriorating. That one comparison makes any analysis sound senior.
Rookie mistake: Reading only one window. A brand can be up +5% L52W and down -3% L12W — the year view hides the turn.
The question your VP will ask: "Is the recent trend better or worse than the annual number?"
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Trend Break
Plain English: The moment a steady trend changes direction or slope. Finding the week it happened — and what else changed that week — is half of diagnostic analytics.
How to judge it: Cross-reference against events: price changes, promo calendar, distribution gains/losses, competitor launches, weather, news.
Rookie mistake: Explaining a trend break with whatever your team did that month. Check the competitor and the calendar before claiming credit or taking blame.
The question your VP will ask: "What changed in the week this started?"
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Seasonality
Plain English: The predictable rhythm of a category through the year — soup in winter, sparkling water in summer. The reason vs.-YA comparisons exist.
How to judge it: Know your category's peak weeks cold. Volume comparisons that ignore them are noise.
Rookie mistake: Panicking over a 'decline' that's just the off-season, or crediting a 'win' that's just the peak.
The question your VP will ask: "Is this seasonal or structural?"
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Markets & Geography
MULO (Multi-Outlet)
Plain English: A common total-market definition combining grocery, drug, mass, club, dollar, and military channels. When a report says 'Total US MULO,' this is what it means.
How to judge it: Know which channels are in and out — notably, some club retailers don't share data into standard databases.
Rookie mistake: Comparing a MULO number against a different provider's multi-outlet number. Different store lists; the totals will never reconcile.
The question your VP will ask: "Which channels are in this number?"
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xAOC (Extended All Outlet Combined)
Plain English: Another provider's multi-outlet market definition — same idea as MULO, slightly different store list. The two most common national benchmarks in US CPG.
How to judge it: Treat MULO and xAOC as dialects of the same language. Learn both; never compare across them directly.
Rookie mistake: Trending a metric across a provider switch (MULO one year, xAOC the next) as if it's one continuous series.
The question your VP will ask: "Are these two numbers even from the same market definition?"
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Channel
Plain English: A retail format grouping: grocery, mass, club, drug, dollar, convenience, e-commerce. Brands perform very differently by channel — totals hide it.
How to judge it: Always be ready to split a total by channel. The 'national' story is usually two or three different channel stories stapled together.
Rookie mistake: Diagnosing a national decline without checking whether it's one channel (or one retailer) driving all of it.
The question your VP will ask: "Is this everywhere, or is it one channel?"
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Market / Geography
Plain English: The where of your data: total US, a region, a retailer, a city. Every metric in this table changes meaning when the geography changes.
How to judge it: Match the geography to the decision. A national number can't answer a retailer meeting; a retailer number can't answer a national strategy review.
Rookie mistake: Quoting your distribution as '92% ACV' in a meeting about one retailer where you're barely stocked.
The question your VP will ask: "Where is this true — and where isn't it?"
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UPC / SKU / Item
Plain English: The individual product level — one flavor, one size, one barcode. Brands are stories; items are facts. Aggregation choices decide which story you see.
How to judge it: When a brand number looks odd, drop to item level. One discontinued SKU can make a healthy brand look sick.
Rookie mistake: Analyzing a brand total without knowing items launched or died inside it during the period.
The question your VP will ask: "Is this the whole brand, or a few items driving everything?"
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Promotion & Price
Baseline Sales
Plain English: The estimate of what you'd sell with no promotion running — everyday demand at everyday price. The foundation the lift sits on.
How to judge it: Healthy brands grow baseline over time. Flat-to-down baseline with growing total sales = a brand becoming promo-dependent.
Rookie mistake: Treating total sales as demand. If baseline is shrinking under the promos, the brand is renting its volume.
The question your VP will ask: "What does our business look like with the promotions turned off?"
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Incremental Sales
Plain English: The extra sales a promotion generated above baseline — the part the deal actually caused. The number that justifies (or indicts) trade spend.
How to judge it: Compare incremental dollars to what the promotion cost. Plenty of deals move volume and still lose money.
Rookie mistake: Crediting a promo with all sales during the promo week. Most of that volume was coming anyway — only the lift above baseline is the promo's.
The question your VP will ask: "Was that promotion actually profitable?"
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Promotional Lift
Plain English: Incremental as a multiple or percent of baseline — how hard the promotion punched. A 2.0x lift means promo weeks sold double the everyday rate.
How to judge it: Lift varies hugely by category and tactic. Trend your own lifts over time: declining lift = shoppers tuning out the deal.
Rookie mistake: Chasing the highest-lift tactic without asking what it costs or whether it just pulls forward next week's purchases.
The question your VP will ask: "Is the lift real growth or borrowed from next month?"
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Any Promo $ %
Plain English: The share of your dollars sold with some kind of deal attached. The promo-dependence gauge.
How to judge it: Rule of thumb in this table's coloring: under 20% comfortable, 20–35% watch it, over 35% the brand may be training shoppers to wait for deals.
Rookie mistake: Ignoring that competitors' promo levels set shopper expectations — your 'high' might be the category's normal. Check the category average first.
The question your VP will ask: "What happens to volume if we pull back promo 10 points?"
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TPR (Temporary Price Reduction)
Plain English: A price cut without display or ad support — the quietest promo tactic. Shows up in data as a dip in average paid price.
How to judge it: Cheapest to run, weakest lift. Fine for staying competitive; rarely a growth engine.
Rookie mistake: Interpreting a falling average price as brand weakness when it's a planned TPR week. Check the promo calendar before diagnosing.
The question your VP will ask: "Is that price drop strategy or erosion?"
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Feature & Display
Plain English: The heavyweight promo tactics: retailer ad ('feature'), special in-store placement ('display'), or both. Where the big lifts come from.
How to judge it: Feature + display together typically out-lifts either alone by a wide margin. Quality of execution (where the display sits) moves the number as much as the tactic.
Rookie mistake: Comparing two promotions' lifts without checking whether one had display support and the other was a bare TPR.
The question your VP will ask: "What support did we actually get in-store?"
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Everyday vs. Promoted Price
Plain English: The two prices every brand really has: the regular shelf price and the deal price. Average paid price blends them — these two pull it apart.
How to judge it: Watch the gap. A widening gap between everyday and promoted price trains shoppers to never pay full price.
Rookie mistake: Setting strategy off the blended average. A $2.25 average can be $2.79 everyday and $1.99 on deal — two different businesses.
The question your VP will ask: "What does a loyal shopper actually pay for us?"
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Shopper (Panel) Metrics
Penetration
Plain English: The percent of households that bought your brand at least once in the period. The width of your buyer base — a panel metric, not a store metric.
How to judge it: Compare to category penetration and to your own year ago. Growing brands almost always grow penetration first.
Rookie mistake: Pitching frequency plays when penetration is the problem (or vice versa). Width and depth need different medicine.
The question your VP will ask: "Are we reaching new households or squeezing the same ones?"
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Buy Rate
Plain English: Average spend per buying household over the period — penetration's partner. Sales = buyers × buy rate, which is the panel decomposition in one line.
How to judge it: Decompose it further: trips per buyer × spend per trip. Each layer has a different fix.
Rookie mistake: Reporting buy rate without saying whether it moved because of trips or basket size.
The question your VP will ask: "Is spend-per-buyer up because of more trips or bigger baskets?"
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Purchase Frequency
Plain English: How many times the average buyer bought you in the period. The habit metric — loyalty's pulse.
How to judge it: Falling frequency with stable penetration = buyers drifting; the brand is becoming an occasional choice. Catch it early — it's cheaper to fix than lost buyers.
Rookie mistake: Missing that 'flat sales' can hide buyers becoming less frequent while new trial papers over it. The mix matters.
The question your VP will ask: "Are our buyers coming back as often as last year?"
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Trial & Repeat
Plain English: Trial = first-time buyers; repeat = those who came back. The two-step verdict on any new product: trial proves the marketing, repeat proves the product.
How to judge it: High trial + low repeat = the product disappoints (or the price shocked at re-purchase). Low trial + high repeat = a marketing/awareness problem with a good product underneath.
Rookie mistake: Calling a launch a success on trial alone. Launch-year volume is bought; repeat-year volume is earned.
The question your VP will ask: "Of the people who tried it, how many came back?"
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Basket Analysis
Plain English: What else is in the cart when shoppers buy you — from panel data. Reveals partners, occasions, and who your shopper really is.
How to judge it: Use for retailer stories ('our buyers' baskets are 22% bigger') and cross-promo ideas. Directional, not gospel — samples thin out fast at item level.
Rookie mistake: Trying to do basket analysis from store-side POS. Baskets are household-level — panel territory.
The question your VP will ask: "What's our shopper's basket worth to the retailer?"
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Reading & Reporting
Share Point
Plain English: One percentage point of category share. Useful because it converts share talk into money: in this fictional category, a point ≈ $12.4M.
How to judge it: Always know what a share point is worth in dollars in your category — it turns 'we lost 0.5 share' into a budget conversation.
Rookie mistake: Confusing share points with percent change. Going from 20% to 21% share is +1 point but +5% relative growth — say which you mean.
The question your VP will ask: "What's a share point worth in dollars here?"
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Fair Share
Plain English: The benchmark of proportionality: if you hold 20% of the category, you'd 'expect' 20% of any retailer, channel, or segment. Gaps versus fair share are where opportunity stories live.
How to judge it: Under-indexing somewhere isn't automatically bad — but it's always worth an explanation. Fair-share gap analyses make excellent retailer pitches.
Rookie mistake: Treating fair share as an entitlement. It's a conversation starter, not a law of physics.
The question your VP will ask: "Where are we under-indexed versus our national share?"
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Cannibalization
Plain English: When your new item's sales come out of your own existing items instead of competitors'. The launch killjoy question.
How to judge it: Estimate by watching your existing items' trend through the launch. Some cannibalization is normal — 100% sourcing from yourself is a flavor swap, not growth.
Rookie mistake: Reporting a launch's sales as all-incremental without checking what happened to the rest of your line.
The question your VP will ask: "Where did the new item's volume actually come from?"
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Distribution Void
Plain English: A specific place your product should be but isn't — a retailer, region, or channel gap. The most concrete, actionable output a distribution analysis produces.
How to judge it: Rank voids by the sales you'd plausibly gain (use velocity in comparable stores), not by count of stores.
Rookie mistake: Handing sales a list of 400 voids with no prioritization. Three big ones with dollar sizes attached gets action.
The question your VP will ask: "What are our three most valuable gaps?"
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Index (vs. 100)
Plain English: A ratio × 100 against a benchmark: 100 = exactly at benchmark, 120 = 20% over, 80 = 20% under. CPG reporting's favorite shorthand.
How to judge it: Indexes under ~90 or over ~110 are usually worth a sentence; hovering near 100 usually isn't. And an index without its base sizes can mislead — 200 index on a tiny base is still tiny.
Rookie mistake: Quoting an impressive index without the absolute number. 'We index 250 with millennials' might be 40 households in the sample.
The question your VP will ask: "Index against what, and how big is the base?"
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Projection / Sample
Plain English: Syndicated numbers aren't a census — they're built from reporting stores and panel households, then projected to the total market. Good estimates, not literal counts.
How to judge it: Treat small numbers (tiny brands, short periods, narrow geographies) with extra care — projection error is proportionally larger there.
Rookie mistake: Arguing over a 0.3% movement in a small brand's small market. That can be sampling noise, not news.
The question your VP will ask: "Is that movement real or within the noise?"
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The 'So What'
Plain English: Not an official metric — the discipline of ending every analysis with an implication or action. Data → driver → decision. The whole reason the other 29 terms exist.
How to judge it: If your last sentence doesn't contain a verb someone could act on, you've written a chart caption, not an insight.
Rookie mistake: Presenting ten correct numbers and zero recommendations, then wondering why the meeting moved on without you.
The question your VP will ask: "Okay — so what do you want me to do about it?"
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