Win-loss analysis for a manufacturer’s quotes: the win rate, a quote log template and why quotes are lost
Win-loss analysis shows why you win some quotes and lose others, starting with your quote win rate.
What win-loss analysis means for a manufacturer
Most of what you find under win-loss analysis comes from software vendors that sell to B2B sales teams. Avoma defines it as examining why specific deals were won or lost. Klue builds its programs on buyer interviews, tagged and then analyzed across deals for patterns.
A plant that quotes configured or engineered products has a different unit of work. It sends many quotes a year, many of them small and some revised several times. Interviewing every lost buyer is out of reach at that volume. The quote log, and the orders that did or did not follow, are the raw material.
Machine shops track the same measure as a quote-to-book ratio. Modern Machine Shop points out that a ratio of 100 percent would mean winning every job bid. It adds that the ratio says little on its own: a shop that wins everything at a poor margin may be quoting too low. Read the win rate beside the margin.
How to calculate your quote win rate
Win rate = quotes won ÷ (quotes won + quotes lost)
Win rate by value = value of quotes won ÷ value of quotes won and lost
No-decision rate = quotes with no decision ÷ quotes closed
Open quotes stay out of all three until they are won, lost or expired
The formula is simple. The rules around it decide whether two people get the same number.
- Count each request once. A quote revised three times is one decision, counted at its last revision. Dynamics 365 Sales, for example, has you close a quote that does not become an order as revised, canceled or lost.
- Report no decision on its own line. When the customer buys from nobody, no competitor won. Counting those quotes as losses lowers the rate and hides a different problem.
- Fix the rule for open quotes. Close a quote at its validity date, or at a fixed age such as 90 days, and keep the rule the same every month.
- Keep budgetary quotes apart. A budgetary quote prices a project that may never go ahead, so mixing it with firm quotes drags the rate down.
- Count by value as well as by number. Winning many small quotes and losing the large ones looks fine on a count and poor in dollars.
Quote speed is worth a cut of its own. In Modern Machine Shop’s 2026 Top Shops benchmarking, shops that turn quotes around within a day report a 51% win rate on new business. Shops that take longer report 41%.
A worked example: win rate by product, customer, size and lead time
A maker of industrial doors sends 520 quotes in twelve months. The numbers are made up and generated by a script to show the method. Forty-four quotes are still open and 40 ended with no decision, which leaves 436 decided: 174 won and 262 lost.
The win rate is 174 ÷ 436, or 39.9%. Counting the 40 no-decision quotes as losses would show 36.6%. By value, the plant won $3.31 million of the $12.16 million decided, or 27.2%, because it wins small quotes more often than large ones.
| Segment | Quotes decided | Won | Win rate | 95% range |
|---|---|---|---|---|
| By product family | ||||
| Sectional doors | 223 | 92 | 41.3% | 35% to 48% |
| Rolling steel doors | 167 | 67 | 40.1% | 33% to 48% |
| High-speed doors | 46 | 15 | 32.6% | 21% to 47% |
| By customer type | ||||
| Plant end users | 136 | 62 | 45.6% | 37% to 54% |
| Distributors | 146 | 61 | 41.8% | 34% to 50% |
| General contractors | 154 | 51 | 33.1% | 26% to 41% |
| By quote size | ||||
| Under $10,000 | 212 | 101 | 47.6% | 41% to 54% |
| $10,000 to $50,000 | 176 | 64 | 36.4% | 30% to 44% |
| Over $50,000 | 48 | 9 | 18.8% | 10% to 32% |
| By quoted lead time | ||||
| 4 weeks or less | 168 | 82 | 48.8% | 41% to 56% |
| 5 to 8 weeks | 196 | 79 | 40.3% | 34% to 47% |
| Over 8 weeks | 72 | 13 | 18.1% | 11% to 28% |
Lead time is the sharpest cut. Quotes promising 4 weeks or less win 48.8%, and quotes over 8 weeks win 18.1%. The pattern holds inside each customer type, so customer mix does not explain it. Distributors win 56% at 4 weeks or less and 12% over 8 weeks. A lead time quoted from available to promise instead of a fixed number is the place to start.
Large quotes lose most often, at 18.8% over $50,000, which is why the rate by value sits below the rate by count. High-speed doors look weakest at 32.6%. On 46 decided quotes, though, the range runs from 21% to 47% and overlaps the other two families.
The range column is a 95% confidence interval by the Wilson method, which NIST’s e-Handbook of Statistical Methods gives for a proportion. It shows how much a rate can move on chance alone. Five wins in 10 quotes is consistent with anything from 24% to 76%, so wait for more quotes before acting on a small cut.
See where your quotes are won and lost
Tell Derik where your quotes are logged and which ERP holds the orders that followed. He will tell you what a four-week reporting sprint would cover for your win rate.
Start a conversationThe quote log: a win-loss analysis template
A win rate is only as good as the log behind it. These are the fields the example needed, with an entry a door maker might make. Copy the columns into the sheet or system your team quotes from.
| Field | Example entry | Why it matters |
|---|---|---|
| Quote number and revision | Q-24117, revision 2 | Counts each request once, at its last revision |
| Date requested and date sent | March 3 and March 5 | Measures turnaround, which moves the win rate |
| Customer and customer type | A general contractor | Cuts the rate by customer type |
| Product family and size | Sectional door, 16 by 14 feet | Cuts the rate by product |
| Quantity and quoted price | 4 doors, $38,400 | Gives the rate by value |
| Cost and margin | $27,900 cost, 27.3% margin | Shows whether wins come from thin prices |
| Quoted lead time | 7 weeks after drawing approval | Cuts the rate by lead time |
| Valid until | April 4 | Closes an open quote on a fixed date |
| Status and decision date | Lost, April 11 | Separates won, lost, no decision and open |
| Order number | SO-31502, when won | Links the quote to the order that followed |
| Lost reason code | Lead time | Counts losses by reason |
| Lost reason in the buyer’s words | “Another supplier offered 4 weeks” | Keeps the evidence behind the code |
| Competitor and winning price, if known | The competitor’s name and price | Shows who wins, and at what price |
| Quoted by | The estimator’s name | Shows rates by estimator |
Your systems may hold some of these already. Dynamics 365 Sales lets you record the competitor, close date and a description when you close an opportunity as lost. Business Central requires a close opportunity code and a closing date. SAP lets you enter a reason for rejection on each quotation item, such as too expensive or delivery date too late.
If quotes come out of an Excel builder, the Excel builder map lists the workbook’s inputs and outputs. Those show which fields a log could capture.
Why lost quotes go unexplained
A win records itself, because it becomes an order. A loss leaves nothing behind unless someone closes the quote.
- A lost quote stays open. SAP’s training notes that when a customer buys elsewhere, no sales order references the quotation. It stays open until someone closes it, often with a reason for rejection.
- The won quote turns into a number on the order. In Microsoft’s Dynamics NAV 2018 documentation, making an order from a quote removes the quote. The order keeps the quote’s number in a Quote No. field. Nothing in that flow records a loss.
- The buyer does not reply. A quote that expires without an answer carries no reason at all.
- The reason is the seller’s. A reason picked from a list by the person who lost the quote is that person’s view of it.
Buyers often see it differently. A study in Industrial Marketing Management interviewed 35 buying decision makers after they turned down a key account proposal. It found three drivers: a proposal not adapted to the buyer, weak relationship potential and cost. The authors chose buyers as the source because data from salespeople and sales managers can carry attribution bias.
Lost reasons to record, and questions to ask the buyer
Keep the list of reason codes short so people use it, and keep a separate field for the buyer’s words.
- Price. A competitor was cheaper, or the budget was lower than the quote.
- Lead time. The date did not meet the buyer’s schedule.
- Specification or fit. The product did not match the requirement as well as another offer.
- Incumbent. The buyer stayed with a current supplier.
- Slow response. The quote arrived after the buyer had decided.
- No decision. The project was cancelled or postponed.
- No reason given. The buyer did not say, which keeps silence visible in the counts.
For the larger losses, a short call or email from someone other than the estimator gets the buyer’s view. These questions cover the codes above:
- Which supplier did you choose, and how far apart were the prices?
- What decided it: price, lead time, the specification or something else?
- Did the lead time on the quote work for your schedule?
- Was anything in the quote unclear or missing?
- What would have changed your decision?
Where AI does the work
AI reads the records a person would otherwise read one at a time, each month. A named person checks each result before it goes into the report.
Each number in the report comes with the query and the quotes behind it, so a figure that looks wrong can be checked. AI reporting covers how that works on ERP data, and human in the loop covers the review step.
The coded reasons then feed pricing. Price optimization uses won and lost quotes to estimate the chance of winning at each price for a kind of customer and order.
How ThriveAI builds your win rate report
ThriveAI’s AI reporting sprint builds the report from the records you already keep. Derik connects read-only to your ERP and accounting system and copies the records into one reporting database. The spreadsheet your team logs quotes in is added as a source. With your controller, he writes down what counts as won, lost and no decision. A win rate report by product, customer, size and lead time can be one of the reports rebuilt in the first stage. Each total is tied to a figure your controller trusts. You then ask for last quarter’s win rate on large door quotes, in plain words, and get the table with the query and rows. The first stage takes four weeks, and the CRM can be added as a source after it. The AI reporting sprint offer describes the four weeks.