What are the key sales KPIs for the Broadline Foodservice Distribution industry in 2027?

The key sales KPIs for the Broadline Foodservice Distribution industry in 2027 are Case-Fill Rate, Lines per Stop (Drop Size), Gross Margin per Case, Account Penetration Rate, Account Retention Rate, DSR Productivity (Sales per Rep per Day), Proprietary (Private-Label) Brand Penetration, **Street vs.

Contract Account Mix, and New Account Activation Rate**. Broadline foodservice distribution moves tens of thousands of food and non-food SKUs — center-of-plate proteins, produce, dairy, frozen, dry grocery, beverage, chemicals, and disposables — from regional distribution centers to restaurants, hotels, hospitals, schools, nursing homes, and other operators on tight, often overnight delivery windows.

Revenue is high-frequency and recurring: the same operators reorder two to five times a week, every week, for years. That structure means the business is won or lost on penetration, drop economics, service reliability, and margin mix inside an existing book — not on logo acquisition.

A sales team that watches only calls made and new accounts signed will badly misread its own health. The nine KPIs below are chosen for exactly how a broadline distributor earns and keeps revenue in 2027, against the competitive frame set by Sysco, US Foods, and Performance Food Group.

Direct Answer: The 9 Broadline Foodservice Sales KPIs

If you read nothing else, these are the nine sales KPIs every broadline foodservice distribution sales leader should be tracking in 2027:

1. Case-Fill Rate — the percentage of ordered cases delivered complete, on the scheduled drop, with no shorts or substitutions.
2. Lines per Stop (Drop Size) — the average number of distinct line items, and total cases, delivered per delivery stop.
3. Gross Margin per Case — profit dollars earned on each case after cost of goods, measured by category, not blended.
4. Account Penetration Rate — the estimated share of an operator's total food-and-supply purchasing the distributor captures.
5. Account Retention Rate — the percentage of revenue-producing accounts (and revenue dollars) retained year over year.
6. DSR Productivity — sales dollars, gross profit, and active accounts generated per District Sales Representative.
7. Proprietary (Private-Label) Brand Penetration — the share of case volume sold under the distributor's own controlled brands.
8. Street vs. Contract Account Mix — the revenue and margin split between independent "street" operators and national/contract accounts.
9. New Account Activation Rate — the share of newly signed accounts that reach a defined steady-state order volume within 90 days.

TL;DR

• The nine KPIs that matter most: Case-Fill Rate; Lines per Stop (Drop Size); Gross Margin per Case; Account Penetration Rate; Account Retention Rate; DSR Productivity; Proprietary Brand Penetration; Street vs. Contract Account Mix; New Account Activation Rate.
• What makes broadline foodservice distribution different: revenue is recurring and high-frequency; the cost to serve is fixed per stop; the margin is razor-thin (industry operating margins commonly sit near 1–4% of sales); and most growth comes from deepening existing accounts, not adding logos. Generic SaaS- or new-logo-style sales metrics miss the levers that actually move the number.
• The competitive frame: the three national broadliners — Sysco, US Foods, and Performance Food Group (PFG) — together control roughly 35–40% of U.S. broadline distribution, with hundreds of regional and independent distributors splitting the rest. Every KPI below is read in the context of that pricing and service pressure.
• How to use this: track all nine in your CRM and order-management system, review them on a fixed cadence (drop and service metrics weekly, penetration and margin mix monthly), and coach DSRs to the benchmark targets below rather than to raw activity counts.

This guide names the nine KPIs, defines each one precisely, gives a 2027 benchmark, explains how to act on it and how it commonly fails, and then closes with a counter-case section on when these KPIs mislead. It is written for sales leaders, RevOps teams, and DSRs at regional and national broadline distributors.

Why Broadline Foodservice Distribution Revenue Works Differently

Most sales-performance frameworks were built for businesses that close discrete deals: a pipeline of opportunities, a win rate, an average contract value, a sales cycle. Broadline foodservice distribution does not work that way, and the KPI set has to reflect the real economics.

Revenue is recurring and frequency-driven. A broadline distributor does not "win" a restaurant once. It wins a slice of that restaurant's order this week, and then has to win it again next week, and the week after. A mid-sized independent restaurant might place 150–250 orders a year.

The distributor's revenue from that account is the product of order frequency, lines per order, cases per line, and price per case — and a competitor's DSR is calling on that same operator trying to peel off categories. Retention and penetration, not acquisition, are the dominant growth levers.

The cost to serve is fixed per stop. Every delivery stop costs roughly the same to make — the truck, the driver's time, the fuel, the loading-dock labor — whether the operator buys 4 cases or 40. This single fact drives much of the KPI set. An account that orders below a minimum drop size is often unprofitable to serve no matter how good the gross margin percentage looks, because the delivery cost consumes the margin dollars.

This is why Lines per Stop and Cases per Drop are treated as first-class sales KPIs in this industry and almost nowhere else.

Margins are thin and category-dependent. Broadline distribution is a high-volume, low-margin business. Publicly reported gross margins for the large broadliners typically run in the high teens to roughly 20% of sales, and operating margins after warehouse, delivery, and SG&A costs commonly land in the 1–4% range.

Within that blended number, center-of-plate commodity proteins are aggressively price-shopped at very thin margin, while specialty items, produce programs, beverage, chemicals, disposables, and private-label goods carry meaningfully more profit. A blended margin number hides where the money is actually made — which is why Gross Margin per Case by category matters far more than a single percentage.

The competitive structure shapes every quote. The U.S. broadline foodservice distribution market in 2027 is led by three national players — Sysco, US Foods, and Performance Food Group — with regional distributors (and buying groups such as those affiliated with UniPro Foodservice) competing fiercely on the rest.

Operators routinely run multiple distributors against each other, holding a "primary" and one or more "secondary" suppliers and shifting categories between them based on price and service. Every KPI below is read against this reality: a distributor is not measuring itself in a vacuum, it is measuring its grip on accounts that are being actively courted by larger, lower-cost rivals.

The sales force is structured around routes and books. Field sales is carried by District Sales Representatives (DSRs), sometimes called Territory Managers or Marketing Associates depending on the company. Each DSR owns a book of accounts on a defined set of delivery routes. The DSR's job is not to "close" — it is to grow penetration, lift drop size, protect margin, onboard new accounts, and prevent churn across that book.

So DSR productivity, route density, and book growth are central performance measures.

Slotting and the catalog shape what a DSR can sell. A broadline distributor's warehouse has a finite number of pick slots, and every SKU that occupies one has to earn its place through velocity and margin. Slotting decisions — which items are stocked, which manufacturer-funded "slotting" or marketing dollars support a placement, how the catalog is curated — directly govern what a DSR can offer an operator and at what cost.

A KPI program that ignores the catalog will miss why a penetration play stalls: the DSR may be trying to cross-sell a category the DC does not slot competitively. The sales organization and the merchandising/category organization have to read the KPIs together. When penetration in a category lags across many DSRs at once, the cause is usually slotting and assortment, not selling effort.

Food-cost inflation distorts every dollar-based number. Broadline revenue is denominated in food dollars, and food costs move. A book that grows 5% in revenue during a year of 6% food-cost inflation has actually shrunk in real, case-volume terms. This is why several KPIs in this set are deliberately *unit-based* — Cases per Drop, Lines per Stop, Case-Fill Rate, gross profit *per case* — and why book-growth targets for DSRs are explicitly set "above food-cost inflation." A sales leader who reads only revenue charts during an inflationary year will badly overstate the team's performance.

The unit-based KPIs are the inflation-proof core of the dashboard.

Taken together, these six structural facts — recurring frequency-driven revenue, fixed cost per stop, thin category-dependent margins, an aggressive three-national competitive frame, a route-and-book sales force, and a slotting-constrained catalog inside an inflationary cost environment — are why broadline foodservice distribution needs its own KPI set rather than a borrowed one.

Every one of the nine KPIs below traces directly back to one or more of these facts.

The diagram below shows how these forces connect — and why the nine KPIs sit where they do.

Because of all this, the nine KPIs are organized into four jobs: serve the account reliably (Case-Fill Rate), make each stop economic (Lines per Stop, Gross Margin per Case), grow the grip on each account (Account Penetration, Private-Label Penetration, Street vs. Contract Mix), and manage the book and the funnel (Retention, DSR Productivity, New Account Activation).

The rest of this guide takes each one in depth.

The 9 KPIs That Matter Most

Each KPI below follows the same structure: what it measures, why it matters in broadline foodservice specifically, the 2027 benchmark or target, how to act on it, and the most common failure mode that quietly breaks the metric.

1. Case-Fill Rate

What it measures. Case-Fill Rate is the percentage of ordered cases that are delivered complete, on the scheduled drop, with no shorts, cuts, or unauthorized substitutions. It is usually calculated as cases delivered as ordered divided by cases ordered, measured per order, per route, per DC, and per account.

A close cousin, the "perfect order" rate, adds the conditions of correct invoice, correct timing, and undamaged product; some distributors track both.

Why it matters in broadline foodservice. An operator builds a menu and a prep plan around the assumption that the distributor will deliver what was ordered. When a case of chicken or romaine is short, the kitchen has a service problem that night — a missing menu item, an emergency cash-and-carry run, an unhappy guest.

Chronic shorts are the single fastest way to lose an account, because the operator does not experience a fill failure as a logistics statistic; they experience it as the distributor failing them in front of their own customers. In a market where Sysco, US Foods, and PFG are one phone call away, service reliability is the moat.

Case-Fill Rate is therefore a *sales* KPI, not just an operations KPI: it predicts retention and it shapes every penetration conversation.

2027 benchmark / target. Best-in-class broadline distributors target a 97–99% case-fill rate, with leading operations pushing toward 98.5%+. Anything chronically below 96% should be treated as an account-retention emergency. Track it by route and by account, not just company-wide — a 97.5% company average can easily hide a 91% route that is bleeding accounts.

A practical refinement: report a "trailing-4-week" fill rate per account rather than a single-week number, because a one-week shortage during a weather event or a commodity disruption is noise, while four consecutive sub-target weeks is a churn signal worth a save play.

How to act on it. Review fill rate by account in the weekly sales meeting alongside revenue. Flag any account whose trailing-4-week fill rate drops below threshold and have the DSR make a proactive call before the operator complains. Tie fill-rate root causes (DC out-of-stock, picking error, transportation cut) back to category buyers and the inbound supply team.

Use a recovered fill rate as a re-penetration story: an account that was shorted and then well-served is a candidate for a category-expansion conversation.

Common failure mode. Measuring fill rate against the *adjusted* order rather than the *original* order. If the system removes out-of-stock items at order entry and then measures fill against what remained, the metric reads 99% while the operator is furious about everything that got dropped.

Always measure against what the operator actually asked for. The second failure mode is averaging away the bad routes — a healthy company number that masks a few catastrophic territories.

2. Lines per Stop (Drop Size)

What it measures. Lines per Stop is the average number of distinct line items delivered per delivery stop; the closely related Cases per Drop measures total cases per stop, and dollars per drop measures revenue per stop. Together these describe drop size — the economic density of a single delivery.

They are calculated by dividing total lines (or cases, or dollars) by the number of delivery stops over a period, by route and by account.

Why it matters in broadline foodservice. This is the KPI that exists because the cost to serve is fixed per stop. Whether a truck delivers 6 cases or 60 cases to an account, the distributor pays nearly the same for the stop. So drop size directly determines whether an account is profitable to serve.

An account with a 3-case drop on a daily delivery is almost certainly losing the distributor money even at a healthy margin percentage. Lines per Stop is also a leading indicator of penetration and consolidation: when an operator moves from buying only produce to buying produce, proteins, and dry goods from one distributor, lines per stop climbs and the relationship deepens.

2027 benchmark / target. Healthy independent-restaurant drops commonly run 8–15+ lines and roughly $700–$1,500+ per stop, though this varies widely by segment (a hospital or large school account drops far larger; a small cafe far smaller). The target is less an absolute number than a *trend* and a *floor*: drop size should rise over time, and the distributor should set a minimum-drop or minimum-order policy (for example, a $300–$400 order minimum, or a delivery-fee schedule below a threshold) so that sub-economic drops are either grown or repriced.

How to act on it. Identify the bottom decile of accounts by drop size and route them to one of three outcomes: grow the drop through penetration (the DSR's job), change the delivery frequency (fewer, larger drops), or apply a small-order fee or minimum so the stop at least covers its cost.

Use Lines per Stop as a coaching metric for DSRs — a rep whose book has rising lines per stop is genuinely consolidating accounts. Pair this KPI with the cross-sell motion described in the Pulse cross-sell working session (st0052), where reps systematically map each account's unpenetrated categories.

Common failure mode. Chasing revenue growth by adding small accounts. A DSR who signs ten tiny cafes can show "new account" wins and revenue growth while quietly destroying route profitability, because every one of those stops loses money. Lines per Stop is the metric that catches this — but only if leadership actually reviews drop economics rather than just top-line revenue.

3. Gross Margin per Case

What it measures. Gross Margin per Case is the gross profit dollars earned on each case delivered, calculated as (selling price − cost of goods) summed across cases, then divided by case count — and, critically, broken out by category: center-of-plate protein, produce, dairy, frozen, dry grocery, beverage, chemicals/janitorial, and disposables/paper.

It is tracked per case (a dollar figure) rather than only as a percentage, because in a fixed-cost-per-stop business, *margin dollars* are what cover the cost to serve.

Why it matters in broadline foodservice. Broadline is a thin-margin business, and the margin is wildly uneven across the catalog. Commodity center-of-plate proteins — boxed beef, chicken, pork — are the items operators price-shop most aggressively and the items competitors quote against; margins there are thin and volatile, swinging with commodity markets.

Specialty proteins, value-added and portion-controlled items, produce programs, beverage, chemicals, and disposables carry materially better margin. A distributor that watches only blended gross margin percentage cannot see whether a growing account is growing *profitably* or simply piling on low-margin protein volume.

Margin per case, by category, is what reveals the truth.

2027 benchmark / target. Blended broadline gross margins typically sit in the high teens to ~20% of sales; operating margins after delivery and SG&A commonly run 1–4%. The category targets matter more than the blend: protect commodity proteins from erosion below their thin floor, and push specialty, produce, beverage, and disposable/chemical categories to carry the profit (often 20%+ gross margin).

The goal is a rising *gross profit per stop*, achieved by mixing margin-rich categories into every account.

How to act on it. Build a margin-mix view by account and by DSR. Identify accounts that are large in revenue but thin in margin (heavy protein, light everything else) and target them for category cross-sell into produce, beverage, disposables, and private label. Give DSRs visibility into the margin of what they sell, and consider a compensation design that rewards gross profit dollars rather than pure revenue — the principles for comping a rep on the right number are covered in the Pulse comp-design library (q15).

Watch commodity protein margin daily during volatile markets so price increases pass through before they erode the book.

Common failure mode. Managing to a blended margin percentage. A distributor can hold "19.0% gross margin" steady while its mix silently rots — protein volume grows, high-margin categories shrink, and gross profit per stop falls even as the percentage holds. The percentage is a trap; margin dollars per case and per stop, by category, are the real signal.

4. Account Penetration Rate

What it measures. Account Penetration Rate is the estimated share of an operator's *total* food-and-supply purchasing that the distributor captures — sometimes called "share of stomach" or share of wallet. It is estimated by comparing what the account buys from the distributor against an estimate of the account's total purchasing (from menu analysis, operator interviews, segment benchmarks, or category-gap analysis).

It is also expressed as a category penetration count: how many of the eight-or-so broadline categories the account buys from this distributor.

Why it matters in broadline foodservice. Penetration is the single most important *growth* lever in this industry, because new logos are scarce and slow. An operator who buys only produce from a distributor is a fraction as valuable as one buying produce, center-of-plate, dry goods, beverage, chemicals, and disposables.

Deepening penetration grows revenue, lifts lines per stop, improves drop economics, raises switching costs, and insulates the account from competitive quotes — once a distributor supplies six of eight categories, a competitor pitching one category is a nuisance, not a threat.

2027 benchmark / target. Strong distributors target 60–75%+ share of wallet on their core "primary" accounts, and aim for every target account to buy from a majority of broadline categories. A useful operational target is "primary-distributor status" on as much of the book as possible — being the operator's main supplier rather than a secondary one.

The trend should always be upward; flat penetration on a key account is a quiet warning.

How to act on it. Run a category-gap analysis on every significant account: list the eight categories, mark which the distributor supplies, and assign the DSR to the biggest gap. Use the structured cross-sell working session (st0052) so reps map each customer's unbought categories deliberately rather than ad hoc.

Make penetration a standing review item — review revenue-mix and penetration KPIs monthly, since they move slowly and weekly noise drowns the signal.

Common failure mode. Estimating penetration once and never updating it, or confusing revenue growth with penetration growth. An account can grow revenue simply because the operator's own business grew, while the distributor's *share* of that account actually shrank because a competitor took two categories.

Penetration must be re-estimated periodically against the operator's real total spend.

5. Account Retention Rate

What it measures. Account Retention Rate is the percentage of revenue-producing accounts retained year over year — and, more importantly, the percentage of *revenue dollars* retained, since losing one large account hurts far more than losing several tiny ones. It is best tracked as both logo retention (count of accounts) and dollar/revenue retention, and often paired with a churn-revenue figure.

Why it matters in broadline foodservice. Because revenue is recurring and high-frequency, a lost account is not a one-time miss — it is a permanent stream of weekly orders gone, often for years. The recurring base is the foundation everything else builds on; growth math only works if the bucket is not leaking.

And restaurant-industry churn is real: independent restaurants close, change ownership, or switch primary distributors. Retention is the metric that tells a sales leader whether the team is defending the base or quietly refilling a leaking bucket with new logos. A team can post strong "new account" numbers and still shrink if retention is weak.

2027 benchmark / target. Well-run broadline distributors target 90%+ annual account retention, with dollar retention ideally higher (because they protect their largest accounts most fiercely). Independent-restaurant-heavy books will see more natural attrition from closures; contract-account-heavy books should retain at a higher rate but face periodic competitive rebids.

For broader context on what an acceptable retention/churn rate looks like across business models, see the Pulse churn-benchmark entry (q104).

How to act on it. Build an account-health score combining fill rate, order-frequency trend, penetration trend, margin, and DSR contact recency — then run a renewal-risk review that catches at-risk accounts 90 days before they leave, as laid out in the Pulse renewal-risk forecast session (st0042).

Treat any account with declining order frequency as at-risk *before* it stops ordering entirely. Assign save plays: a service-recovery call, a pricing review, a senior-relationship visit.

Common failure mode. Measuring retention only by logo count, so the loss of one $400K hospital account looks identical to the loss of one $8K cafe. Always weight retention by revenue. The second failure mode is detecting churn too late — an account rarely sends a cancellation notice; it simply orders less, then less, then stops.

Without an order-frequency early-warning signal, the metric only confirms the loss after it is irreversible.

6. DSR Productivity

What it measures. DSR Productivity is the output of each District Sales Representative — measured as sales dollars, gross profit dollars, active account count, cases, and book growth per rep. The most useful single version is gross profit dollars per DSR per period, because revenue alone rewards low-margin volume.

Supporting cuts include sales per route, accounts per DSR, and new accounts activated per DSR.

Why it matters in broadline foodservice. The DSR is the unit of sales capacity in broadline. With limited new logos available, the productivity of the existing field force — how much penetration, margin, and book growth each DSR drives — is the primary measure of sales-team performance.

DSR productivity also governs the economics of the sales org: a DSR carries a fully loaded cost, and that cost has to be covered by the gross profit their book generates. Route density matters here too — a DSR whose accounts are geographically clustered spends more time selling and less time driving, which lifts productivity directly.

2027 benchmark / target. Benchmarks vary widely by company and segment, so the target is best set internally: every DSR's book should be growing year over year above food-cost inflation, gross profit per DSR should be rising, and each DSR should carry a book whose gross profit comfortably exceeds their fully loaded cost with a healthy multiple.

Set a clear floor and a clear "healthy" band, and manage the distribution of reps against it rather than just the average.

How to act on it. Review each DSR's book growth, gross profit, penetration trend, and new-account activation quarterly. Coach the bottom cohort on the *specific* KPI dragging them — usually penetration or drop size, rarely activity. Use territory design to improve route density so reps spend time selling, not driving; the Pulse territory-plan working session (st0048) gives a repeatable structure for rebalancing books.

When a rep inherits or hands off a book, adjust expectations and comp deliberately — the mechanics of comping a rep who inherits an existing book are covered in the Pulse library (q15).

Common failure mode. Measuring DSRs on revenue alone. A rep who pumps low-margin commodity protein can top the revenue leaderboard while generating less gross profit than a quieter rep with a well-penetrated, margin-rich book. The other failure mode is judging DSRs on activity (calls, visits) rather than book outcomes — activity is an input, and in a recurring-revenue business the outputs (penetration, margin, retention, book growth) are what should drive coaching and comp.

7. Proprietary (Private-Label) Brand Penetration

What it measures. Proprietary Brand Penetration is the share of case volume (and gross profit) sold under the distributor's own controlled or private-label brands rather than national/manufacturer brands. The large broadliners all run extensive private-label portfolios — for example, Sysco's family of proprietary brands and US Foods' "Exclusive Brands" — and regional distributors run their own.

It is measured as private-label cases ÷ total cases, and as private-label gross profit ÷ total gross profit.

Why it matters in broadline foodservice. Private-label cases do two things at once. First, they carry higher gross margin than comparable national brands, because the distributor controls sourcing and there is no national-brand marketing premium. Second — and just as important — they are not directly price-comparable: a competitor cannot quote a line-for-line price against a brand the operator can only buy from one distributor.

Every case of private label an operator buys is a case that is harder for a rival to peel away. Private-label penetration therefore lifts margin *and* deepens the moat, which is why it is a core sales KPI and a standard DSR coaching target.

2027 benchmark / target. A common target band is 30–50% of case volume in proprietary brands, with leading distributors at the top of that range. The benchmark should be set per category — private-label conversion is far easier in dry grocery, chemicals, disposables, and some center-of-plate items than in branded beverage, where operators demand specific national brands.

Track the trend; private-label share should climb steadily as DSRs convert national-brand lines.

How to act on it. Make private-label conversion an explicit DSR play: for every significant account, identify the national-brand lines with a strong private-label equivalent and run a side-by-side spec-and-price comparison with the operator. Support conversion with samples and culinary support.

Report private-label penetration by DSR and by account, and recognize reps who convert. Be disciplined about *which* lines to convert — push where the operator is price-sensitive and brand-indifferent; do not push where the brand is part of the operator's own value proposition.

Common failure mode. Pushing private label so hard that the DSR damages the operator relationship — substituting a private-label item the operator does not want, or converting a line where brand genuinely matters to the menu. Penetration that comes from pressure rather than a real spec-and-price case erodes trust and shows up later as churn.

The metric should be grown through genuine value, not coerced.

8. Street vs. Contract Account Mix

What it measures. Street vs. Contract Account Mix is the split of revenue, case volume, and gross profit between two structurally different account types. Street accounts are independent operators — single restaurants, small local chains, independent caterers — sold and priced by the local DSR.

Contract / national accounts are large multi-unit chains, healthcare systems, school districts, and corporate-managed accounts purchased centrally, often through a corporate agreement, GPO, or RFP, with negotiated cost-plus pricing. The KPI is the percentage of the book in each, by revenue and by margin.

Why it matters in broadline foodservice. The two account types have opposite economics, and the *mix* is a strategic KPI. Street accounts carry much higher gross margin — they are sold relationship-by-relationship, the DSR sets price, and they buy across categories — but they are smaller, more volatile (independents open and close), and more expensive to serve per dollar.

Contract accounts carry lower margin — pricing is negotiated, often cost-plus, and rebid periodically — but they deliver large, predictable, dense volume that fills trucks and absorbs fixed DC and route cost. A book that is all street is high-margin but fragile and hard to scale; a book that is all contract is large but thin and exposed to rebids.

The mix KPI tells leadership whether the business is balanced. The national broadliners — Sysco, US Foods, PFG — explicitly manage and report this street-vs.-national balance because it is central to profitability.

2027 benchmark / target. There is no universal "right" ratio — it depends on the distributor's strategy, DC footprint, and market. The discipline is to *set* a target mix and manage to it: many profit-focused regional distributors deliberately protect a substantial share of high-margin street volume (often aiming for street to be a large share of *gross profit* even if contract is a large share of *revenue*).

Watch the trend — a book drifting heavily toward low-margin contract volume can grow revenue while shrinking profit.

How to act on it. Report revenue *and* gross profit by account type every month, and watch the gross-profit mix, not just the revenue mix. If contract volume is growing while gross profit stagnates, rebalance: invest DSR capacity in street-account acquisition and penetration. Price contract bids with eyes open — know the true cost to serve before agreeing to a cost-plus number.

Use street accounts as the margin engine and contract accounts as the volume base that keeps trucks and DCs efficient.

Common failure mode. Chasing a large national or GPO contract for the revenue headline without modeling the margin and cost-to-serve. A big contract win that prices below the real cost to serve, or that crowds out higher-margin street capacity, can make the company *less* profitable while making the revenue chart look great.

The mix KPI — read in gross-profit terms — is the guardrail against that mistake.

9. New Account Activation Rate

What it measures. New Account Activation Rate is the share of newly signed accounts that reach a defined steady-state order volume within a set window — commonly 90 days. "Activation" means the account is ordering at its expected frequency, across the expected categories, at the expected drop size — not just that a first order was placed.

It is calculated as activated new accounts ÷ total new accounts signed in the period.

Why it matters in broadline foodservice. Signing an account is not winning it. A new account that places one order and then drifts back to its previous distributor is a *cost* — onboarding labor, a new route stop, credit setup, samples — not a customer. In broadline, the first 90 days decide whether a new account becomes a real, penetrated, recurring relationship or a stillborn line on the new-business report.

Activation rate measures whether onboarding actually converts a signature into volume, and it is the honest counterpart to the new-account count: a team can sign plenty of logos and still grow nothing if those accounts never activate.

2027 benchmark / target. A reasonable target is 70–85% of new accounts reaching defined steady-state volume within 90 days, with the strongest onboarding programs at the top of that band. Set the steady-state definition per segment so the metric is meaningful (a hospital account's steady state is very different from a cafe's).

How to act on it. Build a structured 90-day onboarding playbook: a defined first-order experience, an early service-quality check (fill rate on the first several drops is decisive), a category-expansion plan from week one so the account does not stall as a single-category buyer, and a 30/60/90-day DSR check-in cadence.

Measure activation by DSR and by the source of the new account. Treat a stalled new account as urgently as an at-risk existing account.

Common failure mode. Celebrating the signature and moving on. The DSR books the new account, the new-business number ticks up, and attention shifts to the next prospect — while the new account, poorly served on its first few drops or never expanded past one category, quietly reverts.

Without an activation metric, the new-account report looks healthy while net growth is flat. The fix is to make activation, not signing, the metric that counts.

How the 9 KPIs Connect

The nine KPIs are not a checklist of unrelated numbers — they form a connected operating system. Service reliability protects the base; drop economics and margin mix make the base profitable; penetration and private label grow the grip on each account; retention defends it; and DSR productivity plus activation drive net new growth.

The diagram below shows the chain.

Read the chain in one sentence: a distributor activates new accounts, serves them reliably, penetrates them across categories, converts lines to private label for margin, balances street and contract volume, retains the base, and measures the whole thing through DSR gross-profit productivity. Break any link and the others weaken — great penetration with poor fill rate still churns; great fill rate with thin drops still loses money; great drop size with a bad street/contract mix still erodes profit.

Benchmark Summary Table

The table below consolidates the 2027 targets for quick reference. Treat the ranges as direction, not gospel — segment, region, and account mix shift every number.

KPI-to-Lever Mapping

Each KPI maps to a specific operating lever and a specific owner. The table below makes that explicit so a sales leader can route a problem to the right place.

Segment Variation: One KPI Set, Different Targets

Broadline distributors serve very different operator segments, and the same nine KPIs carry different targets in each. The table below shows how the emphasis shifts.

The lesson: do not set one company-wide target for every KPI and judge all DSRs against it. A DSR with a healthcare-heavy book and a DSR with an independent-restaurant book should be coached to different penetration, margin, and drop-size numbers — even though both are managed through the same nine KPIs.

There is also a seasonality dimension that segment-blind targets miss. Education accounts collapse in summer and surge in the fall; resort and banquet hospitality swings with the local tourism calendar; many independent restaurants see predictable Q4 and holiday peaks. A DSR whose book skews to education will show a "retention" and "drop-size" dip every summer that is not a performance problem at all — it is the calendar.

KPI dashboards should therefore compare each metric against the same period a year prior, not against last month, for any seasonally exposed segment. Reading a September education-account drop-size number against July's will manufacture a false alarm; reading it against the prior September tells the truth.

A final segment nuance concerns credit and payment behavior, which sits adjacent to the sales KPIs but shapes them. Independent street accounts carry more credit risk than established contract accounts; a distributor that grows street penetration aggressively also grows its accounts-receivable exposure.

Some distributors track days-sales-outstanding and bad-debt rate by DSR alongside the nine sales KPIs, because a DSR who books fast-growing street volume that does not pay on time is not creating the value the revenue line implies. Credit discipline is not one of the nine core sales KPIs, but it is the guardrail that keeps the street-account growth those KPIs encourage from turning into a write-off.

Operator Order-Frequency and Account-Health Reference

Because retention failures show up first as declining order frequency, it helps to have a shared definition of healthy vs. at-risk behavior. The table below is a practical account-health reference.

A composite account-health score built from these signals is the engine of the renewal-risk review described in (st0042), and it is what turns retention from a lagging report into a 90-day early-warning system.

How to Track These KPIs in Your CRM and Order System

Most broadline foodservice distribution teams can track all nine KPIs with a standard CRM plus the order-management/ERP system already in place — the work is in configuring fields and reports deliberately, not in buying new software.

1. Capture the right fields on every account and order. Account type (street vs. contract), segment, route, delivery-day pattern, primary-vs-secondary distributor status, and category flags on order lines. Without these, penetration, mix, and drop-size KPIs can only be estimated.
2. Pull drop and fill data from the order system, not from memory. Lines per Stop, Cases per Drop, and Case-Fill Rate live in the order/warehouse system. Integrate that data into the sales reporting layer so DSRs see drop economics and fill rate next to revenue.
3. Build one KPI dashboard, segmented three ways. One dashboard with all nine KPIs, sliced by DSR, by route/territory, and by operator segment. Make it the single source of truth in every pipeline and book review.
4. Set the review cadence and stick to it. Service and drop metrics (Case-Fill Rate, Lines per Stop) weekly; margin mix and penetration monthly; retention and DSR productivity quarterly. Fast metrics catch operational problems; slow metrics catch strategic drift.
5. Coach to the benchmark, not to activity. Compare each DSR against the segment-appropriate benchmark and route coaching at the single KPI most off-target. For deciding when a distributor has outgrown spreadsheet/CRM reporting and needs a dedicated forecasting or analytics tool, the trade-offs are covered in the Pulse library (q108).
6. Tie KPIs to comp carefully. Reward gross profit dollars and book growth, not raw revenue, so DSRs are not incentivized to pump low-margin protein volume — see (q15) on comping reps against the right number when they carry an existing book.

Counter-Case: When These KPIs Mislead

Every KPI in this guide can be gamed, misread, or followed off a cliff. A disciplined sales leader treats the nine numbers as instruments, not as the destination. Here is where they mislead — and what to do about it.

Case-Fill Rate measured against the wrong baseline lies cheerfully. As noted in KPI 1, measuring fill against the *adjusted* order (after out-of-stocks are stripped at order entry) produces a beautiful number and a furious operator. The deeper trap: a 98% company average can contain a 90% route quietly losing its accounts.

Always measure against the original order, and always read fill rate by route and by account — never as a single company number.

Lines per Stop can be inflated by splitting orders. A DSR or a system that splits one logical order into multiple invoices, or that encourages an operator to order tiny quantities of many SKUs, can lift "lines" without lifting real penetration or profit. Read Lines per Stop alongside *dollars and cases per drop* and *gross profit per stop* — line count alone is gameable.

Gross Margin percentage hides a rotting mix. This is the most dangerous illusion in the set. A distributor can hold a flat blended gross-margin percentage for a year while protein volume grows and high-margin categories shrink — gross profit *per stop* falls the whole time. Manage to gross profit dollars per case and per stop, by category.

The percentage is a comfort blanket, not a control.

Penetration estimates drift, and high penetration can mean a shrinking pie. Penetration is an *estimate* of share of an operator's total spend. If the estimate is stale, the KPI is fiction. Worse, 70% penetration of an operator whose own business is shrinking is worth less than 50% penetration of a thriving one.

Re-estimate penetration periodically, and weight it by the account's absolute size and growth.

Retention rate by logo count hides where the real loss is. Losing one large healthcare or contract account can be invisible in a 92% logo-retention number while devastating revenue. Always report dollar-weighted retention next to logo retention — and remember retention is a *lagging* indicator.

By the time it moves, the account is gone; the order-frequency early-warning signal is what you actually act on.

DSR Productivity on revenue rewards the wrong behavior. A revenue leaderboard crowns the rep who moves the most low-margin commodity protein. Measure DSRs on gross profit dollars and book growth. And do not over-index on activity metrics (calls, visits) — in a recurring-revenue business, activity is an input, and a high-activity rep with a stagnant, poorly penetrated book is underperforming regardless of how busy they look.

Private-Label Penetration can be pushed past the point of value. A DSR chasing a private-label target can substitute brands the operator does not want or convert lines where brand genuinely matters to the menu. That manufactures short-term penetration and long-term churn. Private-label share should grow through genuine spec-and-price cases, not pressure — a high private-label number bought with operator resentment is a future retention problem.

Street vs. Contract Mix read in revenue terms invites a bad contract. A large national or GPO contract makes the revenue chart soar — and can quietly make the company less profitable if it is priced below the true cost to serve or crowds out higher-margin street capacity. Always read the mix in *gross profit* terms, and model cost-to-serve before signing a contract bid.

New Account Activation can be defined loosely enough to be meaningless. If "activation" means "placed one order," the metric is just a restated new-account count. Define activation as genuine steady-state volume across expected categories, segment by segment, or the number tells you nothing.

The macro counter-case: the KPIs assume the operator base is stable. All nine KPIs are inward-looking — they measure the distributor's execution against its existing accounts. They do not, on their own, capture a contracting restaurant economy, food-cost inflation compressing operator budgets, labor shortages closing independents, a major chain re-bidding its national contract, or a competitor opening a new DC in the market.

A distributor can post nine green KPIs and still shrink because the market moved. The nine KPIs tell you whether you are executing well; they do not tell you whether you are executing well in a *growing* market. Pair them with external signals — restaurant-segment health, operator-closure rates, competitive DC activity, commodity-cost trends — and treat the KPI dashboard as a diagnosis of execution, not a substitute for market judgment.

The honest summary of the counter-case: the nine KPIs are the right nine, and they will make a broadline sales team materially better at seeing itself. But every one of them rewards a literal-minded version of the behavior it measures, and several of them are lagging or estimated.

Use them as a connected system, read them in gross-profit terms, weight them by account size, pair the lagging ones with leading indicators, and never let a wall of green numbers substitute for walking the routes and talking to operators.

A practical rule for resolving the counter-case in day-to-day management: when two KPIs conflict, default to the one denominated in gross-profit dollars and the one that is a leading indicator. If revenue is up but gross profit per stop is flat, believe the gross profit. If logo retention is fine but order frequency is sliding, believe the order frequency.

If penetration looks high but the account's own volume is shrinking, believe the volume trend. The nine KPIs almost never all disagree at once — but when two of them do, the dollar-based, leading-indicator metric is the one telling the truth, and the other is the one being gamed, lagging, or measured against a stale baseline.

Frequently Asked Questions

Which KPI should a broadline foodservice distribution team prioritize first? Start with Case-Fill Rate and Account Retention Rate. They tell you whether the recurring base — the foundation of the entire business — is healthy and defended. A distributor with a leaking base cannot grow no matter how good its new-account engine is.

Once service and retention are stable, shift focus to Account Penetration and Lines per Stop, the primary growth levers.

How often should these KPIs be reviewed? Service and drop metrics (Case-Fill Rate, Lines per Stop) belong in the *weekly* sales meeting because they move fast and signal operational problems early. Margin mix and penetration are *monthly* — they move slowly and weekly noise drowns the signal.

Retention and DSR productivity are *quarterly*. Commodity-protein margin should be watched more frequently than monthly during volatile markets.

Are these benchmark targets realistic for a smaller regional distributor? Yes — the ranges are achievable for well-run regional and independent distributors, not just Sysco, US Foods, and PFG. Smaller distributors often *beat* the national players on Case-Fill Rate and street-account penetration because they are closer to their operators.

Treat the benchmarks as direction and trend targets; steady quarter-over-quarter improvement toward the range matters more than hitting an absolute number immediately.

How do these KPIs connect to revenue forecasting? They form a forecasting chain. Retention and penetration trends predict how much of the existing book carries forward and grows; New Account Activation predicts how much signed new business becomes real volume; Case-Fill Rate and order-frequency trends flag accounts likely to churn before they do.

Together they make a broadline revenue forecast far more reliable than projecting from bookings or last year's number alone.

How do we compete on these KPIs against Sysco, US Foods, and PFG? Not on price on commodity center-of-plate — that is the national broadliners' scale advantage. Compete on Case-Fill Rate (service reliability), on penetration (being the operator's genuine partner across categories), on DSR relationships (the local rep who knows the operator's menu), and on private label that the operator values.

The KPI set is built to direct a regional distributor's effort exactly where scale does *not* decide the outcome.

Should new-account count be a KPI at all? New-account count alone is misleading — it rewards signing tiny, unprofitable accounts. Use New Account Activation Rate instead, which only counts accounts that reach real steady-state volume, and always read it next to Lines per Stop so the team is not rewarded for adding sub-economic drops.

Related Pulse Library Entries

For sales leaders building out a broadline foodservice distribution KPI program, these related Pulse entries go deeper on adjacent topics:

• (ik0040) — sales KPIs for the broader Wholesale Distribution industry, useful for benchmarking drop-size and penetration logic across distribution models.
• (ik0029) — sales KPIs for the Restaurant / Food Service industry, the operator-side view of the same value chain a broadline distributor serves.
• (ik0018) — sales KPIs for the Logistics / Freight industry, relevant to the route-density and cost-to-serve mechanics behind drop economics.
• (ik0079) — sales KPIs for Cold Storage & Refrigerated Warehousing, the temperature-controlled supply chain that feeds broadline center-of-plate and frozen.
• (ik0056) — sales KPIs for Wine & Spirits Distribution, a parallel route-based distribution model with comparable penetration and drop-size dynamics.
• (st0052) — a 60-minute team working session on the cross-sell conversation, directly applicable to lifting Account Penetration and Lines per Stop.
• (st0042) — the Renewal Risk Forecast monthly account-health review that operationalizes the Account Retention KPI and catches churn 90 days early.
• (st0048) — the Territory Plan Build working session, the practical tool behind improving DSR Productivity through route density.
• (q104) — what an acceptable churn/retention rate looks like across business models, context for the Account Retention benchmark.
• (q108) — when to move from CRM reports to a dedicated forecasting tool, relevant to the CRM-tracking section above.
• (q15) — how to comp a sales rep who carries or inherits an existing book, the comp-design counterpart to the DSR Productivity KPI.
• (st0031) — the Expansion QBR working session, a structured way to turn an account review into a penetration-and-margin growth conversation rather than a status update.
• (ik0061) — sales KPIs for Commercial Janitorial Supply Distribution, a useful comparison for the disposables/chemical category mechanics inside a broadline catalog.

A suggested reading order for a sales leader new to a broadline KPI program: start with (ik0040) and (ik0029) for the wider distribution-and-operator context, then use (st0052) and (st0048) to operationalize the penetration and territory levers, then (st0042) and (st0031) to build the retention and expansion review cadence, and finally (q15), (q104), and (q108) for the comp and tooling decisions that make the dashboard stick.

Tracking these nine KPIs — Case-Fill Rate, Lines per Stop, Gross Margin per Case, Account Penetration Rate, Account Retention Rate, DSR Productivity, Private-Label Penetration, Street vs. Contract Mix, and New Account Activation Rate — gives a broadline foodservice distribution sales team an honest, early-warning view of its own performance and a clear, benchmarked target for every DSR to coach toward in 2027.

*Sources and references: (1) Sysco Corporation FY2024–FY2026 annual reports and investor presentations, broadline segment disclosures; (2) US Foods Holding Corp. annual reports and investor materials, including Exclusive Brands and street/national account commentary; (3) Performance Food Group Company (PFG) annual reports and Foodservice segment disclosures; (4) International Foodservice Distributors Association (IFDA) industry data and distribution-operations benchmarks; (5) IFDA Distribution Center Benchmarking & Best Practices reports; (6) National Restaurant Association annual State of the Restaurant Industry reports, operator-purchasing data; (7) Technomic foodservice distribution market analyses; (8) Datassential operator-segment and menu-penetration research; (9) U.S.

Bureau of Labor Statistics food-away-from-home and producer price index (food) series; (10) U.S. Department of Agriculture Economic Research Service food-expenditure series; (11) USDA Agricultural Marketing Service wholesale commodity price reports (beef, poultry, pork); (12) UniPro Foodservice distributor-network materials on independent-distributor competitive positioning; (13) IRI / Circana foodservice channel data; (14) Sysco "share of stomach" and account-penetration framing from investor-day presentations; (15) US Foods cost-to-serve and route-economics commentary from earnings calls; (16) PFG independent-account growth strategy disclosures; (17) IFDA productivity and labor benchmarking for selectors and drivers; (18) industry-standard perfect-order and case-fill rate definitions from the Council of Supply Chain Management Professionals (CSCMP); (19) APICS / ASCM supply-chain metric definitions for fill rate and order accuracy; (20) National Restaurant Association data on independent-restaurant openings and closures; (21) Technomic distributor private-label penetration studies; (22) foodservice trade press coverage (Winsight / Restaurant Business, ID Access) of broadline competitive dynamics; (23) Sysco and US Foods 10-K risk-factor disclosures on customer concentration and contract rebids; (24) IFDA member surveys on DSR span-of-control and book size; (25) commodity-market reporting from the USDA Livestock, Poultry & Grain Market News; (26) restaurant-operator purchasing-behavior research from Datassential and Technomic on primary vs. secondary distributor splits; (27) supply-chain cost-to-serve methodology references; (28) foodservice GPO and contract-purchasing structure documentation; (29) industry analyst coverage of broadline distribution margin structure; (30) Pulse RevOps internal benchmark library cross-references (entries ik0040, ik0029, ik0018, ik0079, ik0056, st0052, st0042, st0048, q104, q108, q15); (31) National Restaurant Association food-cost-inflation operator-impact reports; (32) IFDA Foodservice Distribution sales-organization structure guidance.*