The thing that ends a small brokerage isn't usually a thin margin — it's concentration. One customer that walks, one carrier whose capacity disappears, or one lane that dries up can take a disproportionate share of the business with it. When the top account is 30%+ of revenue, the brokerage isn't really independent of that account. This report makes concentration visible on both sides — customers, carriers, and lanes — so the risk is a number you watch, not a surprise you absorb.
What this report answers
How much of our revenue rides on our single biggest customer, and on our top three? How dependent are we on one carrier for capacity? And how concentrated is our volume in a handful of lanes? The Customer Concentration page draws a Pareto curve of revenue by customer with a cumulative line and shows the segment mix; the Carrier & Lane Concentration page Paretos carrier cost, ranks loads by lane, and treemaps revenue by lane to expose lane dependence at a glance.
The metrics that matter
Top Customer Revenue Share and Top 3 Customer Share are SUM/SUM ratios — the cleanest read on how exposed you are if a key account leaves. Top Carrier Cost Share is the supply-side mirror: a brokerage leaning on one carrier for a large slice of capacity is one lost contract away from a service problem. The Pareto curves are the visual that matters — they show how few accounts or carriers carry how much of the book, which a flat ranking hides.
Why the data is trapped
The TMS — McLeod, Tai, AscendTMS, Aljex, Turvo — has every load tagged by customer, carrier, and lane, so the raw data exists. But concentration is a computed view: top-N shares, cumulative Pareto percentages, distinct carrier counts. None of those are native TMS reports, so owners usually carry a rough sense of "our big customer is a lot of us" without the actual share — until a renewal or a loss makes it concrete. This template computes the shares and Pareto curves off your export.
How to read it
Start with Top 3 Customer Share — if a few accounts carry most of the revenue, that's your single biggest durability risk, and the Pareto curve shows just how steep it is. Mirror it on the carrier side: heavy dependence on one carrier is a capacity risk worth diversifying. The lane treemap rounds it out — concentration in one or two lanes means a market shift in those lanes hits you hardest. The sample on this page uses entirely synthetic data — generic labels and made-up dollar figures, no real loads, carriers, or customers.
Metrics it tracks
| Metric | What it means |
|---|---|
| Total Loads | Count of delivered loads in the period. |
| Total Revenue | Customer revenue across all loads. |
| Top Customer Revenue Share | Largest customer's revenue ÷ total revenue (SUM/SUM) — concentration in the single biggest account. |
| Top 3 Customer Share | Top three customers' revenue ÷ total revenue (SUM/SUM) — concentration in the largest three accounts. |
| Active Carriers | Distinct count of carriers used in the period. |
| Top Carrier Cost Share | Largest carrier's cost ÷ total carrier cost (SUM/SUM) — dependence on one carrier for capacity. |
Used by: Brokerage owners and principals
Frequently asked questions
What is customer concentration risk for a freight brokerage?
It's the exposure created when a large share of revenue depends on a single customer or a small handful. If a top account that's 30%+ of revenue leaves or cuts volume, the impact is outsized. Tracking top-customer and top-3 share — as SUM/SUM ratios — is how an owner sees and manages that risk before a renewal forces the issue.
Why track carrier concentration too?
Concentration cuts both ways. Leaning on one carrier for a large share of your capacity means a lost carrier contract or a service failure can disrupt a big slice of your loads. Watching top-carrier cost share alongside customer share gives a full picture of business durability, supply side and demand side.
Can I build this on my own load data?
Yes. Export your delivered loads tagged by customer, carrier, and lane with revenue and carrier cost from your TMS and use this as a template — we model it into a Power BI report with Pareto curves and top-N shares. The sample uses synthetic data, so there are no real accounts in what you see here.
Build this report on your own data
Clone this Freight brokerages template — describe it and we’ll generate sample data so you can try it free, or upload your own export. You get a fully modeled, branded Power BI project that opens in Power BI Desktop.
Use this as a template →