What is TDP (Total Distribution Points)?

TDP — Total Distribution Points

TDP stands for Total Distribution Points. It's a brand-level distribution metric that combines two things into one number:

TDP = ACV % × average number of SKUs carried per store

A brand with 60% ACV and an average of 4 SKUs per store has 240 TDP. A brand with 60% ACV and an average of 1 SKU per store has 60 TDP. Same store presence (ACV); different depth of presence (assortment). TDP captures both.

The intuition: distribution isn't just "are we on the shelf" — it's "how much of the shelf do we have." Adding a second SKU to every store you're already in is a distribution gain, even though your store count and ACV didn't change. TDP is the metric that registers it.

ACV vs. TDP: the difference between distribution breadth and depth

ACV alone answers: what fraction of category dollars happen at the stores carrying our brand? It's a yes/no per store, weighted by store importance.

TDP answers: across the stores we're in, how broad is our presence? Same brand, same stores, but two SKUs per store carries more shelf weight than one.

When to look at which:

• Use ACV when comparing total brand presence across markets, retailers, or time periods. ACV is the right "are we getting onto shelves" metric.
• Use TDP when assortment depth is the strategic question — line extensions, slot expansion, or new pack-size additions to existing doors.

A brand that grows from 60% ACV / 1 SKU to 60% ACV / 3 SKUs has tripled TDP without changing ACV. Pure ACV reports would miss this entirely.

How TDP is calculated in practice

The mechanics depend on what you're calling a "SKU" — typically the UPC level, but sometimes rolled up to a brand-line or pack-config level for executive dashboards.

A worked example with 5 SKUs and 4 stores:

• Stores A, B, C carry the brand → ACV (with category-dollar weighting) calculated separately. Assume ACV = 75%.
• Average SKUs per carrying store = (3 + 2 + 1) ÷ 3 = 2.0
• TDP = 75% × 2.0 = 150

Two notes about this calculation:

1. The SKU average is over carrying stores, not all stores. Store D doesn't drag the average down. This is a different normalization than some "SKUs per door" metrics use, so the number can look higher than expected.
2. The ACV input should be measured at the brand level, not the per-SKU level. If you compute ACV per SKU and average, you get a different (smaller, more correct-feeling but misleading) number.

Where TDP gets misused

The single biggest trap: using TDP as a one-number performance metric.

A brand can grow TDP three ways:

• Add new doors (ACV up, SKUs/door flat) → genuine distribution win
• Add SKUs to existing doors (ACV flat, SKUs/door up) → assortment win
• Lose small doors and gain large doors (ACV up via mix shift, SKUs/door flat) → quality-of-distribution shift

Each of these is a different commercial story. A TDP gain that's all SKU bloat in your existing doors is not the same as a TDP gain from new retailer onboarding — but the TDP report shows the same number. Always decompose: ACV change vs. SKU/door change.

The second trap: comparing TDP across categories. Categories with deep natural assortment (cereal, bars) tend to support more SKUs per brand per store than categories with narrow assortment (single-pack beverages). TDP comparisons across categories are noise unless normalized for category-typical SKU counts.

Using TDP to build the pitch for SKU expansion

TDP's most practical use for a brand-side analyst is building the internal and external case for a new SKU authorization at existing doors. The logic:

1. Where does the brand sit in TDP vs. the category leader? If the brand has 120 TDP and the category leader has 280 TDP at the same retailer, the gap is mostly assortment depth, not distribution breadth. That's an argument for a line extension review with the buyer.

2. Which stores are single-SKU outliers? If 70% of carrying stores have 2+ SKUs but 30% still carry only 1, those single-SKU stores represent the clearest assortment expansion opportunity. The brand is already authorized; the buyer just hasn't expanded the set yet.

3. What's the velocity of the second SKU vs. the first at stores that carry both? If stores carrying 2 SKUs show 15% higher total brand velocity per store than stores carrying 1 SKU, that's the data point for the expansion pitch: adding a second SKU lifts the first SKU's velocity, likely through category-adjacent placement or increased shopper familiarity.

A wellness supplement brand used exactly this pattern with a national natural-chain buyer: 68% of stores carried the original SKU at $38/store/week; the 22% of stores also carrying the new flavor averaged $51/store/week for the original SKU. The incremental shelf slot was lifting both items. That data won the chain-wide rollout of the second SKU.

TDP benchmarks by category

There's no universal "good TDP," but knowing category norms prevents wrong comparisons:

The benchmark question to ask is not "is our TDP good" but "is our TDP/store in line with our velocity/store" — a brand with 240 TDP and $25/store/week total velocity is carrying SKUs that aren't selling. A brand with 80 TDP and $140/store/week is moving product efficiently and likely has room to pitch for more SKUs.

Multi-year TDP analysis

TDP's compounding effect becomes visible over a 2–3 year window. A natural snack brand's TDP trajectory at Sprouts over 36 months:

The distribution story here is almost entirely in SKUs/door after Q2 2024. ACV barely moved from 61% to 63%; TDP went from 110 to 176. If the brand had only tracked ACV, they'd have concluded growth stalled. TDP shows the real picture: they're deepening their shelf presence at the stores they're already in, which is the right play when ACV is approaching saturation.

TDP per turn: the assortment-efficiency check

A subtler use of TDP is testing whether the brand's assortment is pulling its weight per SKU. The diagnostic: pair TDP with category turn rate and brand velocity to see whether each incremental SKU is adding velocity or diluting it.

The calculation: brand velocity ÷ (TDP ÷ category-typical turn). A brand with 200 TDP at $90/store/week in a category where leaders run roughly 6 unit-turns per SKU per week is moving about $90 ÷ (200 ÷ 6) = $2.70 per SKU-store-turn — slightly below the category benchmark for a typical mid-tier brand. A brand at 80 TDP and the same $90/store/week velocity is at $90 ÷ (80 ÷ 6) = $6.75 per SKU-store-turn, materially more efficient on a per-SKU basis.

The strategic implication: the higher-TDP brand is carrying more SKUs without proportional velocity gain. Either the line extensions are cannibalizing the original or the assortment is broader than the demand justifies. The lower-TDP brand has shelf-efficiency upside — adding a second SKU at carrying doors would likely lift total brand velocity per door at a better ROI than the higher-TDP brand's marginal SKU. This is the read that decides whether the next move is "add SKUs" or "rationalize and grow per-SKU velocity."

This is the test that buyer-facing pitch decks rarely run, but category-managing retailers absolutely run on their side. A brand walking into a category review at Sprouts or Whole Foods asking for a 3rd SKU at every carrying door should be able to demonstrate that their current 2-SKU stores are not cannibalizing — that the 2nd SKU added genuine velocity rather than dividing the existing velocity across two facings. Without that evidence, the buyer's default answer is "the math doesn't work for me, come back next reset."

For brands at the lower-TDP end of the category, the pitch is straightforward — efficient on shelf, room to grow. For brands at the higher-TDP end, the buyer's default question is "show me the velocity-per-facing trend over the last 24 months," and the answer needs to be defensible across cohorts of stores that added SKUs at different times. Anything less reads as a brand asking for shelf without doing the work to earn it.

Doing this in Scout

Scout exposes TDP as a column alongside its components — ACV, average SKUs per carrying store, and per-store velocity — on every brand and retailer cut from your SPINS extracts. The decomposition is in the default view, so "TDP up 12%" is a glance away from "added doors vs. added SKUs at existing doors." For the SKU-expansion pitch use case, Scout's store-level view lets you segment the carrying stores by SKU count and compare velocity between 1-SKU and 2-SKU stores directly, which is the data that makes the expansion argument to a buyer.

Summary + further reading

• TDP combines ACV and average SKU count per carrying store into a single distribution-and-depth metric.
• It's a useful summary metric — but only when paired with the decomposition into door-count change vs. SKUs-per-door change.
• Cross-category TDP comparisons are noisy without normalization for category-typical assortment depth.
• The SKU-expansion pitch is where TDP earns its keep: if 2-SKU stores outperform 1-SKU stores on total brand velocity, that's the data argument for authorization.

Related: What is ACV? · Velocity vs. share vs. TDP — which to use when