It’s the wrong shape for this business, and it trains reps to do the opposite of what you want.

It’s built for a sales motion that isn’t T&L reality

The declining commission comes from the hand-off model. A hunter closes the deal, then passes the account to an account manager or a customer success team that owns it from there. The commission tapers because the rep genuinely leaves. They are not servicing the account in year three, so they are not paid as if they are. Software runs this way constantly (the AE sells, the CSM keeps).

Transportation and logistics mostly does not. The rep who sold the account is still responsible for it in year three, and year five. In truckload sales, the account may be serviced by operations, but when there is a problem, the sales rep is the one who owns the customer and the issue. In LTL sales, there is always more freight to get and the sales rep owns the territory and all customers it contains. In brokerage this isn’t even a discussion as I’ve rarely seen a declining commission used there - the customer is almost never truly handed off. Freight forwarders sometimes use this mechanic, but it usually works against them for the reasons noted. The only two places in the T&L space I can think of where it makes sense are Managed Transportation (where there is nothing left to sell) and maybe some warehousing or 4PL operations where there is very little need for an ongoing sales rep relationship.

If the role is pure lead gen, where someone sets the appointment or gets the first load and hands it off, then it would be more appropriate to talk about a goal for number of appointments and a closing bounty.

When the rep never walks away, a commission built around walking away stops making sense.

The psychology runs backwards

A declining commission sends one message to a rep: this account matters less to you every year you keep it.

That is the wrong message in a relationship business. Your oldest accounts are usually your biggest and stickiest, with the most room left to grow. You want the rep to care more as the account matures, not less. The declining plan pays them to mentally write off the book they should be defending, and to chase only the next new logo where the 10% lives.

So you get reps who neglect good, mature accounts (small current commission, steady work) and over-rotate to new-logo hunting. You lose share of wallet on customers you already won, and you won’t find out until the next bid season.

A flat rate forever is not the fix either

The obvious overcorrection is to pay one flat commission on the book for as long as the rep holds it. That solves the “care less” problem and creates a new one: it pays reps to sit. A flat annuity rewards holding the book, not growing it, and it dilutes the push to bring in new customers. You have traded an over-aggressive hunter for a rep who spends most of their time golfing and looking forward to a “working” retirement.

One rate cannot do both jobs, declining or flat. The plan needs two elements, each paying for a different behavior.

More reason to kill the cliff: it’s an admin mess

The declining schedule is a tracking headache (which account is in which year, at which rate, prorated from which start date), and every approaching cliff turns into a fight. When a rep’s rate is about to drop from 10% to 5%, they will find a reason that account is special and the drop should not apply. The reps spend time arguing about exceptions instead of selling and you spend time managing their complaints instead of more important things.

The fix: a two-element plan

Split the job in two and pay each part for what it actually is.

Element 1: new-customer commission. A straight-line rate (one number, no taper) on new accounts, for a fixed window of one to two years. It pays for the hunt. Because the rate is flat and the window ends on a known date, there is no cliff to argue about. When the window closes, the account simply rolls into the book.

Element 2: a growth element on the total book. A goal-based incentive tied to growth across the whole rep’s account base (every account, all time), with real leverage on overachievement. This is where caring about mature accounts gets paid. The rep carries a growth goal for all assigned customers based on their sales history and any house accounts which may have been assigned, and beating it pays disproportionately.

Together, the rep is paid to keep hunting (Element 1) and to grow everything they have ever sold (Element 2). The reason to care now rises with the book instead of decaying with it, and the new-logo push stays intact.

Note the difference between Element 2 and a flat annuity. An annuity pays a percentage of the book whether it grows or not. Element 2 pays for growth against a goal, so a rep cannot earn it by sitting on mature accounts. They have to keep making them bigger.

What Element 2 looks like

The growth element uses standard linear leverage. At goal, the rep earns the target incentive. Above goal, the payout accelerates. A common shape pays double the target for beating the goal by 25%.

At 100% of the growth goal, the rep earns 100% of the target growth incentive. At 125%, they earn 200%. Below a threshold (here 75% of goal), the growth element does not pay. The threshold and the cap are yours to set, but the principle holds: overachievement is worth more than proportional, so the rep is pulled to grow the book hard rather than to protect a number.

Because the goal is built on the entire book, an account the rep sold four years ago counts exactly as much as one signed last month. The fifteen-year customer is no longer worth almost nothing to the rep. It is part of the base they are paid to grow. There is one more subtle benefit here you may have caught: accounts the rep did not sell can be included in Element 2. If the rep is responsible for the the growth of the account, that is where it belongs. Now you don’t have to worry about “discounted rates” on accounts the rep did not sell, but is now responsible for.

Pay for what you want

You want two things from a transportation sales rep: keep bringing in new customers, and keep making the whole book bigger every year. A declining commission pays for the first and quietly discourages the second. A flat annuity does the reverse. A two-element plan, one piece for the hunt and one for book growth, pays for both, and it stops teaching your best reps to lose interest in their best accounts.

Two reps can each turn in $50k in GM$ for the month and be running completely different businesses. One might have thin margins and a ton of loads. The other might have fat margins (high profit per load (PPL)) and a fraction of the volume. Same surface impact on the P&L, but the books are very different in terms of cost to produce, and very different in terms of value to the company.

That gap is the whole argument for building incentive plans around three levers instead of one.

The cost-to-serve problem

First some basic math - backwards and forwards.

GM$ divided by Revenue = GM%; therefore GM$ divided by GM% = Revenue.

If GM$ is $50k and you change the margin:

• At 12% margin, you move about $416k in freight to make that $50k (~278 loads at $1500 each)

• At 6% margin, you move about $833k in freight to make the same $50k (~556 loads at $1500 each)

Same gross margin, double the freight handled.

Every load is more work: a carrier to source and vet, a truck to book, tracking and check calls, paperwork, a billing cycle, and the claim, falloff or fraud risk. That work scales with load count, not with margin dollars. So the 6% month costs roughly twice as much to produce as the 12% month as there are more employees and more exposure for the exact same gross margin. And because low-rate markets compress revenue per load too, the real load-count gap is usually worse than 2×.

This is why, in the low-rate market we’ve been living in, GM% stops being a vanity stat and becomes the thing that decides whether volume is worth chasing at all. Move $50k at 6% and you can actually be losing money once you load in the cost to serve. Move it at 12% and you don’t.

The high-rate market flips the priority

Run the same math when rates are high and the picture inverts. Margins are wide, so GM$ comes easy. A rep can hit the same number with far fewer loads and that’s exactly where the trouble starts, and anyone who remembers 2021/2022 knows exactly what I’m talking about.

When you make the same money on fewer loads, the rational move for a rep paid on GM$ is to work less. Fewer customers, fewer lanes, less coverage. They make the same (or more) on less work, so why grind?

The problem is load count buys you customer “stickiness”. Load count is how you stay in a customer’s routing guide, how you hold lane density, how you become the call they make first. Drop your volume in a fat market and you’ve quietly handed that ground to a competitor who is willing to take a little less of a markup. When the market turns (as it always does) you’re left with margin you can no longer get and no volume to fall back on.

So load count matters in a high market for a reason GM$ will never show you: it’s the asset that protects next year’s revenue.

Three levers, and the ability to toggle with the market

Put those together and the pattern is clear. GM$ is the size of the result. GM% is what it costs to get there. Load count is what it’s doing to the customer relationship. You need all three, and which one you lean on depends on the market:

• Low-rate market: protect GM% so volume doesn’t bury you in cost to serve.

• High-rate market: protect load count so coasting doesn’t cost you the relationship.

A plan built on GM$ alone can’t make that distinction. A plan hard-wired to GM% will move away from strategically useful volume the moment the market loosens. Any fixed plan works in one market but not in the other.

The matrix

This is where a matrix earns its keep. The structure I keep coming back to for a carrier sales rep is simple to state:

Pay commission on GM$ with the commission rate determined by GM% and load count.

Note: all rates are illustrative and not recommendations for any role

GM$ is what is used as the calculation base (what the commission rate is applied to), because that’s what the rep actually produced. But the rate they earn on it moves depending on how they produced it. Same $50k in GM$ pays one way if it came from thin margins and high volume, and another way if it came from high margins and lower volume. The rep works toward the cells you’ve made worth the most, while providing push back against one of two common problems in other plan designs:

1. Cherry picking freight (we know the stories of reps coming into the office at 4 am to get all the “good freight”) OR

2. Taking the first carrier that comes along without bothering to negotiate.

Both grids above pay on GM$. They differ in one thing: where the high rates sit. The volume-driven plan pays more in the upper left, where load count is high. The GM%-driven plan pays more in the bottom right, where margin is high. The spine that runs diagonally bottom left to upper right, and the target cell in the middle, holds in both.

Note that it is common for carrier sales roles to use a similar matrix, but pay a $ per load value on the cells inside rather than a commission on GM$. This can work in certain environments (especially in an organization with heavy contracts that mean loads may need to be moved at a loss), but keep in mind you have now doubled down on the LOAD lever in the plan and completely removed GM$ from the equation.

Re-tune without rebuilding

The reason the matrix beats a formula is that you can re-tune it as the market moves without touching the structure.

In a high-rate market, weight the opposite diagonal rate toward load count so you reward the volume that defends your customer base while margins are easy. In a low-rate market, weight them toward GM% to reward the discipline that keeps high volume from eating you alive.

It’s the same plan with the same axes. You move the emphasis. Reps don’t need to relearn how they’re paid; they just feel the emphasis shift toward what the business needs this quarter.

Where reps sit, and what it pays to move them

Reps will tend to live where the market points them. In a high-rate market they drift down and to the right, to low load count and high margin. In a low-rate market they anchor in the top-left because they need load count to survive. Neither corner is where you want them to stay for long. So you point the plan at the move you need.

High-rate market — push load count up. Take a rep sitting at low load count and 18% margin, moving freight at about $2,000 a load. Move him up to target load count at the same margin and his commission goes from about $1,890 to $5,670 a month (a 200% jump) while the company picks up roughly $54k more in GM a month ($50k after the extra commission expense). The extra loads cost more to serve, but in a high rate market the freight carries the margin to pay for it.

Low-rate market — push margin right. Take a rep moving high volume at 10% margin, maybe at about 140 of PPL. If she can hold the load count but lift profit per load to about $216, through firmer sell-side pricing and tighter buy-side cost, margin now reaches 15%. Her commission goes from about $2,205 to $5,103 a month (up 131%) while the company picks up about $34,200 more in GM ($31k after the extra commission expense). In this case there are no extra loads behind it, zero added cost to serve, all of it margin.

That contrast is the point. The high-market move adds GM$ with cost to serve attached, so be careful about reducing GM% too much to get more loads - that move can backfire quickly. The low-market move adds GM$ with no new loads behind it, but of course, this is easier said than done and requires intense customer and carrier rate negotiations. It’s the same basic compensation plan, just tuned to drive the behavior you need for the current market.

The part that makes it work

One design note worth stating, because it’s easy to miss. At a fixed GM$, GM% and load count pull against each other. The only way to push a lot of loads through a given GM$ is to accept lower margins on them; the only way to lift margin on a given GM$ is to be choosier and move fewer. The matrix won’t let a rep max both. It forces them to pick the blend, and you decide which blend pays best.

That tension is deliberate. Don’t engineer it out. The matrix is the way you control the tension: you set the push through emphasis on the opposite diagonals, the reps find the highest reachable cell, and the business economics move in the direction you need.

GM$ will always be the most important number. It just shouldn’t be the only one in the pay plan. Build the plan to see, and control, all three levers, and build it so you can move them when the market shifts.

Two common questions are “where should we be” and “what do we do if our data is ‘off’ of what the survey shows it should be?”

Where Should We Be?

This is a heavily philosophical question with deeply practical implications.

First, a brief hierarchy of importance when looking at Total Compensation stats vs Salary Stats. Always start with Total Comp. Freight brokers are an incentive heavy lot, but not everyone uses incentives the same way. There are many companies in our set that pay Carrier Sales, Hybrid 1, and Hybrid 6 using ZERO salary. They may get a draw, or they may not once they are “on commission.” This is why you may see salary numbers DECREASE for higher experience levels, because a number of incumbents are reported at zero.

There are also companies who pay very little in incentive compensation to these same roles and skew more salary heavy.

I’ve worked with a lot of industries and never seen one with such disparate approaches to pay for the same roles - both in amount and in how the pay is delivered.

Therefore, the safest stat to begin with is Total Comp as it will capture the full pay, regardless of how it is delivered. Think of the base salary as the minimum required, and the total comp as the point of differentiation. A perfectly valid compensation philosophy positioning statement would be:

We match salary to the market 50th percentile, and total compensation to the market 75th.

This would mean your median performer would be exceeding the market median in total comp, and your high-end performers would be above that. Keep in mind that your data is a range, just like the market, and you can be “at market” with a variety of different pay levels, as follows:

For the salary view, you’ve set your salary mid-point at the market, but the 20% range around the mid-point means pay as low as $42,400 and as high as $63,600 is safely within your salary band. The market data lets you know that $42,400 may be too little to attract and retain talent, so from a practical standpoint you may not want to bring in anyone with a salary less than $47,500 even though your band allows it.

For the total comp view, you have earners below the 75th percentile market target you selected, and you have earners above (some well above), but your internal median is landing very close to the market 75th. Good job! This is what it means to be benchmarking to the market. It does NOT mean everyone in this role makes exactly $91,567. What is more important is: are the high earners creating more profit for the company than the lower earners? Not in raw dollars (I would hope so) but in percent. A well designed incentive plan (or in truth, any plan that uses a salary) has a declining cost of compensation at higher production levels because the salary does not (and should not) be proportionally linked to production. There are also ways to design the commission plans so you enhance the effect - pay more for high performance, but as a % of production - pay a reducing percentage at target performance. We will get into more of these details in our upcoming webinar series: www.prosperiogroup.com/connect.

What do we do if our data is “off”?

This is a more complex question and one that should be addressed carefully. First, define “off” in the context of the preceding section. A few people are “off” or everyone is “off”? Where does your median land relative to the market?

Remember to always start with Total Compensation (not salaries). If you are aligned with the market for Total Compensation, you may be ok if your salaries are a tad below market. You also have to consider the impact of benefits - if you pay a higher percentage of employee healthcare, that is a true offset to lower salaries. Conversely, if you pay nothing toward healthcare, then your salaries may look higher than the market but they must be to provide a competitive total rewards package.

Increasing salaries (or commission rates) is the easy psychological change - rarely do employees complain when these changes happen. The converse is much more difficult and, frankly, not recommended unless there are extreme circumstances. Reducing salaries NEVER ends well and should only be done as a last resort, and usually with a reduction in hours rather than simply saying we are planning to pay you less for the same amount of work. Employers may want to increase motivation by reducing salary and putting the dollars toward incentive compensation, but this inevitably backfires (I’ve seen this firsthand). What you get is a demoralized and distrustful workforce, not a motivated one.

Kink the Curve Instead

In fact, the better motivational incentive design moves the OPPOSITE direction. Raise salaries. Remove any portion of the incentive that functions as “phantom base salary” and make the leverage or upside in the plan even more meaningful so the dispersion in pay between your 90th percentile earner and your 50th percentile earner INCREASES.

I know it’s counterintuitive, but raising base salaries can actually help you unlock more motivation from your incentive plan. One of the primary challenges with commission-only (or draw) models is they have no or limited ability to increase leverage as the plan is too leveraged from the start. A draw model requires a higher commission rate, that then cannot be meaningfully increased at higher performance levels without damaging company economics. Raising the salary and reducing the starting rate allows you to increase the rate paid for higher production, which creates more motivational reward for getting to the higher production (for everyone).

It’s an understandable question. Many people have never taken a stats class, or if they did, it was a long time ago. So here’s the whole thing in a few minutes, using real numbers from the 2025 survey.

A percentile tells you where a number sits in a line-up.

Take one role. Line up every person in it from lowest paid to highest paid, left to right. The 50th percentile is the person standing in the exact middle. Half the people earn less, half earn more. That middle number is the median, and it’s the number you should anchor to.

So what are the 25th and 75th?

Same line-up. Same 100 people.

• 25th percentile — a quarter of the way in from the bottom. 25 people earn less, 75 earn more. This is roughly where a newer or lower-paid person in the role lands.

• 75th percentile — three quarters of the way up. 75 people earn less, 25 earn more. This is the high end of normal, before you get into the true outliers.

For Carrier Sales (Cover Freight) in 2025, base salary ran $47,500 at the 25th, $53,000 at the median, and $61,795 at the 75th. If you’re paying a carrier sales rep a $48K base, you’re at the low end of the market. If you’re at $62K, you’re near the top of it.

Why we do not report averages

An average adds everyone’s pay up and divides by the total number of people. The problem is that pay isn’t spread evenly — a small number of top earners make multiples of everyone else, sometimes 10x or 20x the typical person. Those few big numbers yank the average up, away from what most people actually make, and in small populations this distortion can be profound!

The median doesn’t care about that. If the top person in the line up makes $10 billion dollars, the person standing in the middle doesn’t move. That’s why every detailed Measure Up statistic is a median or a percentile, not an average.

Here’s easy math so you can see yourself. Three numbers:

$10

$100

$1,000

The average is $1,110 / 3 or $370. The median is $100.

If the top number becomes $100,000, the average is now $33,370 but the median remains $100.

“The market rate” is a range, not one number

Frankly, this one sets my teeth on edge and is the biggest “tell” that someone doesn’t understand market surveys. There is no single market rate for a role. There is no amount of emphasis that is TOO MUCH for that sentence. There is NO SINGLE MARKET RATE FOR A ROLE. There’s a range, and the percentiles are how you see it.

Look at the same Carrier Sales role two ways — base salary, then total cash (salary plus incentive):

Two things to notice. Total cash sits higher than base, because incentive is real money on top of salary. And the gap between the middle and the top gets wider once incentive is in the picture — the 75th on total cash is $91,567, farther above the $67,983 median than the 75th is above the 50th in base salary. That spread is the story. It’s what separates an average performer from a strong one, and it’s the lever you actually control when you design a plan, and the one that will increase plan motivation (we have a webinar coming up on this very topic, which you can register for here: www.prosperiogroup.com/connect)

There are two additional statics worth noting:

IQ Ratio (Interquartile Ratio) or P75/P25 is the 75th percentile over the 25th percentile. Using the numbers above the IQ Ratio for salary is 1.3 ($61,795 / $47,00) but the IQ Ratio for total comp is 1.6 ($91,567 / $57,136). The 75th percentile earner makes 60% more than the 25th percentile earner.

Interquartile simply means the MIDDLE of the quartiles, where 50% of the participants live.

The other stat is the incentive DISPERSION ratio and you need your whole data set to figure this one, but it’s the 90th percentile earner in incentive comp divided by the 50th percentile earner. This tells you how much upside or leverage your plan has and how motivational it is likely to be to the participants. This is exactly the topic we will get into in the first 2 webinars, so be sure to sign up.

The guardrails

A couple of rules sit behind every number, both to keep the data meaningful and to keep the survey on the right side of antitrust law:

• Five-company minimum. If fewer than five companies reported data for a role, we don’t publish a statistic for it. Too few sources and the number stops meaning anything.

• The 25% rule. No single company can make up more than a quarter of any statistic. If one big brokerage would dominate a number, the data gets trimmed back until that’s no longer true. We have a complex process that does this while still preserving every company’s median contribution; simply put we trim equally from the top and the bottom of the company’s list of employees so the remaining employees still provide the same median that the larger set provided.

So when you see a figure in the report, it’s drawn from a real spread of companies, not one outlier with a massive amount of employees (and we have a couple of very big companies in this year’s set!).

How to use the report

Pick your role. Read the median first (50th percentile)— that’s your anchor. Then look at the 25th and 75th to see how much room there is on either side. If your people sit below the 25th, you have a retention problem waiting to happen. If they’re above the 75th, you’d better be getting top-quartile results for it.

The full 2025 results are also in the online tool, where you can filter by region and look back at history to 2019. If you participated this year, you have free access through September 30. Email katie.burkholder@prosperiogroup.com if you want a walkthrough of the on-line tool.

Pay went up. Median total compensation rose 11%, from about $71,100 to $78,700 (this is a simple median of ALL 16,458 employees’ total compensation in the data set).

Base pay beat the market - but incentive beat it more. Base rose about 5%. Total comp rose 11%. The difference is incentive. Variable pay went from roughly 6% of total comp to roughly 12% in a single year — close to double. This is interesting because 2025 was not a particularly GOOD year for Freight Rates, so it’s worth pondering what caused the increase. Without any particular stats to back it up (the submitting companies change a bit year to year), Prosperio’s HR Best Practices Group (larger brokers) showed that turnover was a bit higher in 2025. This may mean that the freight that was left could be distributed amongst fewer employers, creating higher payouts for those that remained.

For context, national pay rose about 3.5–4% over the same period — that’s from the Employment Cost Index and the Atlanta Fed’s wage tracker. Brokerage comp in this survey ran well ahead of that. I’d go easy on the exact multiple, though. The national gauges hold the job mix steady; our survey doesn’t, since the companies and roles in it shifted somewhat from 2024 to 2025. It’s not a complete shift though - we retained about 75% of the same jobs from year to year and 60% of the companies are in both the 2024 and the 2025 survey.

National pay figures:
U.S. Bureau of Labor Statistics, Employment Cost Index (12 months ending December 2025)
Federal Reserve Bank of Atlanta, Wage Growth Tracker (September 2025).

The role-level picture is uneven. One hybrid “cradle-to-grave” role — the person who finds, manages, and covers their own freight — posted the largest jump, with median total comp up 73% year over year. While intriguing, this is most likely because we added a big cradle-to-grave player into the survey this year and historically our data in for this role has always been a little lean. At the other end, pay didn’t rise for everyone: one C-suite role’s median fell about 20%. Both of those sit in the full report, with the dollar figures and the company counts behind them.

A structural note: we added 8 roles this year and removed 7 that didn’t have enough participating companies to report within DOJ rules which mandate 5 companies for any disseminated statistic.

What’s in the full report

The 2025 report covers all 60 roles — base, incentive, and total compensation, reported by percentile, with year-over-year movement and the number of companies behind each figure. It’s the level of detail you’d need to set or defend a pay range.

To buy the report or join Measure Up, email Katie Burkholder at katie.burkholder@prosperiogroup.com.

Read more

Financial Improvement

• Improved economics (pay aligned better with performance) –pay as % of GP$ should decrease over time and for very high producers (they should still make a lot, but as a % of GP$ it should be less)

• Business results – if you drive a particular thing in the plan (e.g., load count, GP%) have you seen an improvement in that thing?

Human Resources Outcomes

• Reduced turnover? (HR can help you track this)

• Better attraction of top talent? (again, look to HR and your hiring manager to see if the plan is helping)

• Improved understanding (poll your employees after the plan has been in place for a year)

• Improved career development? You will see this if people stay and progress through levels in the plan (if it has them - which it should)

Administrative Improvements

• Simplification of plan (ask the people who calculate it if it’s easier to process with less errors)

• Less plan volatility – do you feel you have more control over the plan and don’t need to change it as often (or, if you do, the changes are minor tweaks that are easily absorbed by the team w/o angst)

How do we connect incentive compensation to business priorities?

The answer touches nearly every part of a business:

• Top line revenue growth

• Bottom line profitability

• Employee and customer retention

• Employee recruiting

• New customer acquisition

• Performance accountability

• Culture

Yet most incentive plans are borrowed from what a leader did at a different company.

And once they’re in place, they either never change or they get changed every six months.

We often hear that the plans aren’t driving a “sense of urgency” among employees, and that leaders disagree on how to fix it.

Beth Carroll and her team at Prosperio Group have spent almost three decades designing, building, and operating incentive compensation programs across all industries, with a particular focus on transportation, logistics, and supply chain.

This is where we’ll share what we’re seeing and teach you what we know.

You can expect articles and tools on:

• Incentive plan design — both motivational theory and practical reality

• Compensation governance and philosophy

• Transportation industry trends in compensation

• Leadership, accountability, and how leaders can get out of their own way and let a plan work

• Lessons learned from real-world implementations

Some posts will be practical, others analytical.

Some will challenge conventional wisdom, and some will make your head hurt (that’s on purpose — if you aren’t thinking, you aren’t learning).

We’re not here to hand out generic HR advice. We’re here to help leaders make better decisions about performance, incentives, and growth.

Welcome aboard.

— The Prosperio Team