QTC metrics: how to measure quote-to-cash performance
Reviewed by:
Ashley Kemper
SVP of Marketing
QTC metrics: how to measure quote-to-cash performance
Quote-to-cash (QTC) metrics measure performance from initial customer quote through final payment. This article covers five core metrics: QTC cycle time, quote turnaround time, quote approval time, quote conversion rate, and QTC efficiency.
By tracking them, revenue teams can see exactly where their deals slow down between quote and payment.
QTC metrics at a glance
Metric | What it measures | Formula | Unit | Benchmark availability |
QTC cycle time | Quote creation to payment | Payment date − quote date | Days | No standard benchmark — set internal baseline |
Quote turnaround time | Request to quote sent | Sent − requested | Hours or days | No standard benchmark — set internal baseline |
Quote approval time | Submission to approval | Approved − submitted | Hours | No standard benchmark — set internal baseline |
Quote conversion rate | Sent quotes that close | Closed-won ÷ sent × 100 | Percent | No quote-specific benchmark; see below |
QTC efficiency | Revenue per quoting effort | Revenue ÷ quotes, or ÷ cycle hours | Dollars | No standard benchmark — set internal baseline |
What is quote-to-cash (QTC)?
Quote-to-cash, or QTC, is the revenue process from when a quote is generated through when the agreement is signed and payment is collected. The key stages include configure and quote, propose, negotiate, approve, sign, invoice, and collect.
You measure performance at each stage to reveal revenue leakage, slow deal velocity, and gaps in forecasting.
Learn more about quote-to-cash vs. CPQ and how to increase deal velocity with CPQ.
5 core QTC metrics (and how to calculate them)
Below, we cover the five core QTC metrics. For each, you’ll learn its definition, formula, a worked example, why it matters, and what affects it.
QTC cycle time
Definition: QTC cycle time is the total elapsed time from quote creation to payment received and recorded. It’s the single broadest measure of QTC performance, so if you track only one metric, choose this.
Formula:
QTC cycle time = date payment received − date quote created (in days)
Use the median across your deals rather than the mean. This is because a single outlier deal can distort the mean significantly and give you a misleading picture of typical performance.
Example: A sales rep creates a quote on day one. The deal closes, and the agreement is signed on day 14. The payment is received on day 21.
QTC cycle time = 21 − 0 = 21 days.
Why it matters: Shorter QTC cycle times mean faster revenue recognition, better cash flow predictability, and less deal-decay risk. A long cycle time is a compound signal: it can show you problems at the quoting stage, the approval stage, or the payment collection stage. Having a sub-metric breakdown is necessary to see which stage is creating the bottleneck.
What affects it: The number of approval tiers needed, quote revision cycles, e-signature adoption vs. wet signature, payment terms (net-30 vs. net-60, for example), and whether you use manual vs. automated invoicing after the signature all affect QTC cycle time.
Benchmark: No widely accepted industry benchmark exists for QTC cycle time. Instead, you should establish a 90-day internal baseline as your primary reference point.
Quote turnaround time
Definition: Quote turnaround time is the elapsed time from when a quote is requested (or a qualified opportunity is opened) to when the quote is sent to the prospect.
Formula:
Quote turnaround time = timestamp quote sent − timestamp quote requested
Use hours for high-velocity sales motions and days for complex or enterprise deals. You should always state which unit you’re using when reporting this metric.
Example: A prospect requests a custom quote at 9 a.m. on Monday. The sales rep builds and sends the quote at 2 p.m. on Tuesday. A total of 29 hours elapsed from when the quote was requested on Monday morning to when the quote was sent Tuesday afternoon, which means:
Quote turnaround time = 29 hours
For more complex sales, it might take longer, in which case you’d use days as the unit instead.
Why it matters: Response speed is one of the strongest predictors of conversion in B2B sales. So when you have a slow turnaround, competitors can respond first. Plus, it can signal to the buyer that your process is manual and/or disorganized.
What affects it: The availability of pre-built templates, a product catalog, pre-send approvals, pricing data access for reps, and whether you use manual vs. CPQ-assisted quoting can affect this metric.
Benchmark: No widely accepted industry benchmark exists for quote turnaround time. Track internal median turnaround and compare it quarter over quarter.
Quote approval time
Definition: Quote approval time is the elapsed time from when a quote is submitted for internal approval to when it is approved and released for sending. This differs from quote turnaround time because it measures only the time to get through the internal approval stage, not the entire creation-to-send window.
Formula:
Quote approval time = timestamp approval granted − timestamp submitted (in hours)
Use the median across all your submitted quotes in the measurement period.
Example: A rep submits a discounted quote for manager approval at 3 pm Friday. The manager approves the quote at 10 am Monday. From when the quote is submitted to when it's approved, a total of 67 hours elapsed. This means that:
Quote approval time = 67 hours.
Why it matters: Internal approval delays are one of the most common causes of QTC cycle time inflation, yet it’s also one of the most correctable. Even if a deal closes quickly from a sales conversation, you can still end up with a long QTC cycle time if you have to wait days for a discount approval.
What affects it: The number of approval tiers, discount thresholds that trigger escalation, approver availability, whether you use manual (like email/Slack) vs. automated approval workflows, weekend stalls, and undefined approval SLAs all impact this metric. Fortunately, a document approval workflow can help.
Benchmark: No widely accepted industry benchmark exists for quote approval time. Your team should track internal median approval time and set explicit SLAs as your primary reference point.
Quote conversion rate
Definition: Quote conversion rate is the percentage of sent quotes that result in a signed agreement or a closed-won deal within a defined measurement window.
Formula:
Quote conversion rate = (closed-won quotes ÷ quotes sent) × 100
Always specify the measurement window for this metric. A 30-day window will give you a different rate than a 90-day window for the same pipeline.
Example: A team sends 80 quotes in Q3. By the end of Q4 (the agreed measurement window), 24 of those quotes led to closed-won deals.
Quote conversion rate = (24 ÷ 80) × 100 = 30%.
Why it matters: A low conversion rate is a compound signal that can indicate pricing problems, quote quality issues, poor timing, or a mismatch between the qualified opportunity and actual buying readiness. You can’t improve this metric without first figuring out which stage is causing the loss.
What affects it: Quote personalization and quality, pricing competitiveness, follow-up speed and cadence, whether the document is a static PDF or an interactive document with embedded signature capability, and when you send the quote can all affect your quote conversion rate.
Benchmark: No single benchmark exists specifically for quote-to-closed-won conversion. The figure depends on how "quote sent" is defined relative to your pipeline stages. The closest credible figure is a 19% average opportunity-to-close rate, from the Ebsta x Pavilion 2025 GTM Benchmarks (655,000 opportunities, $48 billion of pipeline analyzed). Teams that measure from the proposal stage specifically report higher rates. RAIN Group's research puts the average proposal-stage win rate at 47%. Neither figure maps directly to a quote conversion rate without knowing how your pipeline stages are defined.
QTC efficiency ratio
Definition: The QTC efficiency ratio expresses how much revenue a team generates relative to the time or resources invested in the QTC process. This metric doesn’t have a single standard formula. This is because teams operationalize efficiency differently depending on what inputs they can actually measure.
Formula: Here are two variants:
(1) Quote yield = total revenue from closed deals ÷ total number of quotes sent in the same period
This formula expresses the average revenue per quote sent, regardless of conversion rate.
(2) Revenue per cycle hour = total QTC revenue ÷ total QTC cycle time (in hours) across all closed deals in the period
This formula expresses the revenue generated per unit of process time invested.
Example (quote yield variant): A team closes $480,000 in revenue in Q3 from 80 quotes sent. Using the formula above, we can learn the average revenue of each quote:
Quote yield = $480,000 ÷ 80 = $6,000 per quote sent
Why it matters: This metric shows whether your team is generating more revenue from the same quoting effort over time. It helps indicate directional trends. For example, is yield per quote going up or down? This matters more than getting the standalone absolute number.
What affects it: Average deal size, conversion rate changes, time spent on non-converting quotes, and automation reducing manual quoting effort per quote sent can all affect this metric.
Benchmark: No widely accepted industry benchmark exists for QTC efficiency in any of its formulations. Track directional change against your own internal baseline rather than an industry number.
How to use QTC metrics to find where deals slow down
Start by measuring QTC cycle time to see whether a problem exists. If that time is rising, break it down.
Compare your quote turnaround time and approval time to see whether the slowdown is at creation, internal approval, or post-signature payment collection. PandaDoc’s approval workflows and e-signature connect to these stages, allowing you to increase deal velocity with CPQ and automate revenue recognition.
Then, you can use quote conversion rate to determine whether the problem is velocity or volume.
Setting benchmarks when no industry standard exists
Industry benchmarks for QTC metrics are scarce, inconsistently defined, and often sponsored by vendors with an interest in the outcome.
That’s why it’s best to establish an internal baseline first. Measure what you have now, before you introduce any tool or process change, and use that as your primary benchmark.
You can do this with a simple 90-day baselining approach: track all five metrics for a full quarter with no process changes. Then calculate medians and use them as the “before” state against which you measure any future changes.
Looking to close more deals? Check out our blog on sales enablement metrics to track, or check out our quoting software.
Speed up every stage of quote-to-cash
Once you know where your deals slow down, PandaDoc helps you fix it. Quote Builder and CPQ help your reps build accurate quotes faster. Conditional approvals send discounted quotes to the right approver as soon as a rep submits them, so no one has to chase a sign-off in Slack. E-signatures and PandaDoc Payments put the payment request in front of your customer the moment they sign.
PandaDoc CPQ runs natively inside HubSpot, Salesforce, and Pipedrive, so your reps stay in the CRM they already use. Document analytics show you when buyers open a quote and how long they spend on each page, so your team can follow up at the right moment.
Start your free PandaDoc trial and see how quoting works for your team.
Frequently asked questions
No single benchmark exists specifically for quote-to-closed-won conversion. The figure depends on how "quote sent" is defined relative to your pipeline stages. The closest credible figure is a 19% average opportunity-to-close rate, from the Ebsta x Pavilion 2025 GTM Benchmarks (655,000 opportunities, $48 billion of pipeline analyzed).
Teams that measure from the proposal stage specifically report higher rates. RAIN Group's research puts the average proposal-stage win rate at 47%. Neither figure maps directly to a quote conversion rate without knowing how you define your pipeline stages.
QTC cycle time is the end-to-end elapsed time from quote creation to payment received. It’s the most comprehensive single measure of quote-to-cash performance.
Quote turnaround time = timestamp of quote sent − timestamp of quote requested. Calculate in hours for high-velocity motions or in days for complex or enterprise-level deals.
Number of approval tiers
Quote revision cycles
E-signature adoption
Payment terms
Invoicing automation
CRM/CPQ integration quality
No single definition exists. You can use two formulas: one for quote yield and one for revenue per cycle hour.
Quote yield is the total revenue per quote sent in the same period.
Revenue per cycle hour is total QTC revenue divided by the total cycle time (in hours) across all closed deals in the period.
QTC metrics: how to measure quote-to-cash performance
Reviewed by
Ashley Kemper
SVP of Marketing
Ashley Kemper leads the global Marketing team at PandaDoc. She's built and scaled marketing programs from the ground up at Asana and launched new brands at Double and HyperComply. Before moving into marketing, she spent years as a digital media producer and graphic designer at National Geographic, Agence France-Presse, and Government Executive. Fun fact: Ashley has survived five cross-country moves with her wife, Malorie, and their French Bulldog, Frannie.
