Win/loss analysis is the structured practice of reviewing why a seller wins or loses the quotes and bids it submits. Sellers examine both outcomes, comparing won quotes against lost ones across factors such as price, lead time, customer type, and product line. The goal is to find repeatable patterns behind wins and losses so the sales and quoting process can be improved with evidence rather than guesswork.
Why This Matters
Most suppliers track revenue closely but rarely study the quotes they submit as a data set. That gap is expensive. According to HubSpot, the average B2B sales win rate is around 21%, meaning roughly four out of five quotes go nowhere. Understanding the difference between the winning fifth and the rest is where win/loss analysis earns its value.
The discipline also corrects a common bias. Sales teams tend to blame lost deals on price, but that explanation is often wrong. Research from Satrix Solutions finds that pricing is rarely the only reason a deal is lost. Response speed, quote completeness, relationship strength, and simple timing all play a role. Win/loss analysis surfaces these hidden causes and prevents a team from cutting margins to fix a problem that price never caused.
How It Works
Win/loss analysis starts by defining what counts as a win and a loss. A win is a quote or bid that converts into a purchase order. A loss is a quote the buyer declines in favor of a competitor. A third outcome, the no-decision, occurs when the buyer neither buys from you nor a rival, they simply do nothing. Clozd reports that no-decision losses often exceed losses to any single competitor by two to three times, so many programs track them separately.
Once outcomes are defined, sellers segment the results. Common dimensions include:
- Price — Was the quote above, at, or below the winning price?
- Lead time — Did a shorter or longer delivery window decide the outcome?
- Customer — Do certain industries, sizes, or regions convert better?
- Product — Which lines or SKUs win consistently, and which lag?
- Response time — How quickly did the quote reach the buyer?
The final step is gathering the reason for each outcome, ideally from the buyer directly through a short follow-up rather than an internal guess. Patterns then emerge: perhaps quotes sent within a day win far more often, or a particular product loses on lead time. Those patterns become the input for improvement. Suppliers building this habit often pair it with a broader review of supplier win/loss analysis across their quoting pipeline.
How Buyer24 Helps
Buyer24 focuses on the buyer side of quoting, but its structured quote data gives both parties a cleaner record of what was submitted, when, and against which requirements. An emerging win/loss portal is on the roadmap to help suppliers see how their quotes compared on price and lead time, so the reasons behind an outcome are visible rather than assumed. See a demo →
FAQ
Is win/loss analysis only for sales teams?
No. While sales teams run it most often, procurement, product, and pricing teams all use win/loss findings. The data reveals which products win, which customers are a good fit, and where pricing or lead times need adjustment.
How many quotes do you need to start?
Even a few dozen quotes reveal early patterns. Larger data sets give more reliable segmentation, but there is no strict minimum. The key is reviewing outcomes consistently rather than only after a major loss.
What is the difference between a loss and a no-decision?
A loss means the buyer chose a competitor. A no-decision means the buyer bought nothing at all. They have different causes, so tracking them separately helps sellers respond to each correctly.
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