
Most freight brokers we talk to have a blind spot when it comes to their sales data.
Picture this: It's Friday afternoon. Your team sent out 120 quotes this week. You booked 14 loads.
Is that a good week?
If you ask your reps, they’ll say the market is soft or capacity is tight. But without hard data, you're just guessing. You don't know if you're losing on price, losing on speed, or quoting lanes you have no business running.
The hidden labor cost of manually quoting and tracking loads that you ultimately lose is staggering. If a rep spends 15 minutes calculating a rate, building a quote, and sending an email for a load they never win, that’s time they aren't spending covering actual freight.
At FasterQuotes, we've seen brokerages transform their profitability just by turning the lights on. Once you know exactly what you're winning and losing, you can stop wasting time on dead-end quotes and focus on the freight that actually pays.
Here is the step-by-step guide on how to track freight quote win rates in a small brokerage, establish your baseline, and start winning more freight.
A freight quote win rate (often called a quote-to-order ratio) is the percentage of freight quotes you submit that successfully convert into booked loads.
If you send 100 quotes and win 12 of them, your win rate is 12%.
For small brokerages, tracking this metric is non-negotiable in 2026. The spread between carrier costs and shipper rates is tighter than ever. If you don't track your win rates, you risk falling into two dangerous traps:
Before you start tracking, you need to separate your data into two distinct buckets: spot market quotes and contract RFP bids.
Spot Market Quotes are transactional. A shipper needs a truck today or tomorrow. Speed is the primary factor here. If you don't respond within 10 minutes, you usually lose, regardless of your price.
Contract RFP Win Rates are strategic. A shipper is asking for annual pricing on 50 lanes. You have days or weeks to respond. You must understand the exact difference between a freight RFQ vs tender to track these accurately, as the strategy for winning annual freight is entirely different from winning daily spot loads.

To calculate your freight quote win rate, divide your total booked loads by your total submitted quotes, then multiply by 100.
The Formula:
(Booked Loads ÷ Total Submitted Quotes) × 100 = Win Rate %
If you quoted 450 loads last month and won 52:
(52 ÷ 450) = 0.115
0.115 × 100 = 11.5% Win Rate

Many small brokerages panic when they realize they are losing 85% of the loads they quote. But in logistics, a high win rate isn't always a good thing.
According to historical data from FreightWaves, spot market dynamics dictate that if your win rate is too high, your rates are too low.
Here are the industry benchmarks for 2026:
To get actionable data, you must track your win rates by specific variables. An overall win rate of 12% tells you very little. But knowing you win 25% of your flatbed loads out of Texas, and only 2% of your reefer loads out of California, tells you exactly where to focus your sales efforts.
You can track freight quotes using an Excel spreadsheet, a dedicated CRM/TMS, or an AI-powered RFQ automation platform. The right choice depends on your volume and team size.

If you are a startup brokerage doing less than 20 quotes a day, Excel or Google Sheets is fine.
To set this up, create a sheet with the following columns:
The Problem with Excel: It relies entirely on manual data entry. Reps get busy, they forget to log the quotes they lost, and your data becomes skewed. You end up with a 100% win rate on paper because reps only log the loads they actually book.
Most modern Transportation Management Systems (TMS) have quoting modules built-in. When a rep builds a quote in the system, it automatically logs it. If it doesn't convert to a load within 48 hours, the system marks it as lost.
This eliminates the data entry problem, but it still requires the rep to manually build the quote in the system before emailing the shipper.
The most sophisticated small brokerages don't log quotes manually at all. They use AI to read incoming quote requests from emails, instantly calculate the rate, and log the data automatically.
By utilizing AI-powered logistics quoting, the system tracks exactly how many requests came in, what was quoted, and what was won—without a human ever touching a spreadsheet.
| Feature | Excel Spreadsheet | TMS / CRM | AI Automation (FasterQuotes) |
|---|---|---|---|
| Setup Cost | Free | Medium to High | Low to Medium |
| Data Accuracy | Low (Human Error) | Medium (Requires manual input) | High (Automated capture) |
| Speed to Quote | 15+ minutes | 10-15 minutes | Under 1 minute |
| Win/Loss Analytics | Manual Pivot Tables | Built-in Dashboards | Real-time automated insights |
Win rate alone doesn't pay the bills. You can have a 20% win rate and still go bankrupt if you aren't tracking the complementary metrics that dictate profitability.
Alongside your quote-to-order ratio, you must track:

Are you winning freight by sacrificing your spread? Track your margin percentage alongside your win rate. If your win rate goes up but your average margin drops from 15% to 8%, your pricing strategy is broken.
This is the single most important metric for pure brokerages operating in the spot market. First response wins the load.
According to data from DAT Freight & Analytics, brokers who respond to spot quote requests within 5 minutes win up to 60% more freight than those who take 15 minutes. We see this constantly. When we build real-time quoting systems with 50-80ms latency, our clients watch their win rates double simply because they beat the competition to the inbox.
How often do you follow up on a quote you sent yesterday? Most reps send the rate and wait. Tracking how many touchpoints it takes to win a load helps you build a standardized sales process.
Once you have the data, you have to use it. Tracking for the sake of tracking is a waste of time. Here is how you analyze the data to improve your spot quote management in a volatile market.
Identify Profitability Trends: Filter your tracking system by equipment type. You might find that you win 18% of your dry van quotes but only 3% of your flatbed quotes. This means your team either lacks flatbed carrier capacity (so your costs are too high) or doesn't understand flatbed accessorials.
Categorize Your Losses: Force your reps to categorize why a load was lost.
Refine Your Calculation: If you are consistently losing on price in a specific lane, check your rating tools. Are you relying on outdated historical averages instead of real-time market data?

If there is one takeaway from this guide, it's this: Speed is the ultimate conversion lever.
You can have the most accurate pricing model in the world, but if it takes your team 20 minutes to calculate the rate and reply to the shipper, the load is already gone.
Small brokerages often feel they can't compete with mega-brokers who have entire departments dedicated to pricing. But technology has leveled the playing field. By implementing AI for small trucking companies and brokerages, you can automate the entire quoting workflow.
When an email comes in from a shipper asking for a rate from Chicago to Dallas, automation tools can read the email, check your historical carrier costs, add your desired margin, and draft the reply—in seconds.
We've helped brokerages reduce their quoting processes by 87.5%, taking tasks that used to take months of labor down to just weeks. When you remove the manual data entry, your reps can focus on building relationships and covering freight, rather than acting as human calculators.

Tracking your freight quote win rate is the first step toward running a profitable brokerage. But if your reps are spending two hours a day logging quotes into a spreadsheet, you are losing money on administrative overhead.
At FasterQuotes, we build RFQ automation for freight brokers who want to scale without adding headcount. We've helped clients eliminate 99% of their admin work by automating the exact processes that slow them down.
Our systems don't just calculate rates instantly; they automatically track every quote requested, sent, won, and lost. You get a real-time dashboard of your win rates by lane, shipper, and equipment type, without ever opening Excel.
Stop guessing where your margins are leaking. Start tracking your data automatically and win the freight you actually want.

A healthy win rate for a freight broker in the spot market is typically between 10% and 15%. For contract freight or annual RFPs, a good win rate is higher, usually ranging from 15% to 30%, because these involve established shipper relationships and predictable volumes.
To calculate your freight quote win rate, divide the total number of loads you successfully booked by the total number of quotes you submitted, then multiply that number by 100. For example, winning 15 loads out of 100 submitted quotes equals a 15% win rate.
Alongside your quote win rate, a small freight brokerage should track average margin per load, quote turnaround time (speed-to-lead), and load fall-off rate. Tracking these complementary metrics ensures you are winning profitable freight, not just cheap freight.
To track freight quotes in Excel, create a spreadsheet with columns for Date, Shipper Name, Origin, Destination, Equipment Type, Quoted Rate, Status (Won/Lost), and Loss Reason. While this works for low volumes, it requires strict manual data entry from your sales reps to remain accurate.
The average closing rate for daily transactional freight sales hovers around 10% to 12% across the industry. Brokers who leverage automation to respond to quote requests in under 5 minutes often see their closing rates jump to 20% or higher due to the speed-to-lead advantage.

Siddharth Rodrigues
Founder and CTO
Siddharth Rodrigues is an AI automation engineer who builds systems that save companies 20+ hours per week per employee. With $191K+ in documented client savings across 18 projects, he specializes in turning manual, repetitive processes into intelligent automation. Currently building FasterQuotes.io to help logistics companies process RFQs faster.