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Measurement

Part of Measure proposal software by revenue or by reply, the choice that changes your numbers

How to build a proposal software benchmark

Build a proposal software benchmark from quote and proposal records, test external claims, define useful metrics and document a method your team can refresh.

Editorial Desk · · 6 min read

What to take away

  • Benchmark figures now sit on vendor pages that are edited without notice, so a number can change between your draft and publication.
  • A benchmark rebuilt from your own quoting and proposal records is defensible; an external study supplies context only.
  • Record the source page and the date you read it for every figure you publish.
  • Agree the method before collection starts, because procurement teams now ask how a comparison was produced.
  • Keep any published comparison reproducible for a reader with the same access to the records.

What counts as proposal software benchmark research?

Benchmark research is a measured comparison against a baseline you can name. A team that claims an average quote turnaround of, say, 3.2 working days must be able to state the sample, the period and its definition of turnaround.

That is not the same as market sizing, which estimates how many buyers exist, or vendor marketing, which describes a supplier's own customers. Both can inform your thinking without qualifying as a benchmark.

If your reporting definitions are still informal, fix them before you collect anything. The measurement and reporting guide explains which metrics survive a change of sales leadership.

How do you tell a usable external benchmark from a marketing claim?

Five checks for external benchmarks

  • Publisher states the sample
  • Collection window is given
  • Geography matches your market
  • Method is repeatable by another analyst
  • Underlying data available on request

Geography is where most teams slip. A figure covering the whole United Kingdom may not describe a sales team working only in England, and a global figure rarely does. Check the wording of any geographic claim before you reuse it.

Method matters more than sample size. A small, transparent panel beats a large, unexplained one, because you can at least test the small one against your own records.

A public vendor page is a source to inspect, not a benchmark in itself. Google's robots.txt specification concerns crawler access to web pages; it does not validate proposal performance or provide quote data. If you build a panel from public pages, record which pages were accessible and capture each source page and the date you checked it.

Keep continuity separate from proposal performance. BS EN ISO 22301 is a business continuity management standard; it may inform questions about continuity, but it does not measure quote turnaround, proposal acceptance or revision cycles. Do not use certification or alignment as evidence of sales-document performance.

Choose a consistent cohort and report the numerator, denominator and time period for each measure. These definitions make a proposal software benchmark reproducible:

  • Mean quote turnaround:total working time from quote creation to its first sent timestamp, divided by the eligible quotes first sent in the cohort. Use one agreed working-day calendar.
  • Proposal acceptance rate:proposals accepted by a defined cut-off, divided by proposals sent in the cohort. State how acceptance is recorded, such as a status change or completed e-signature.
  • Revision cycles per proposal:recorded post-send revision cycles, divided by proposals first sent in the cohort. Define what counts as a cycle and use version history or revision events where available.
  • Mean time to approval:total elapsed time from submission for approval to the approval timestamp, divided by proposals approved in the cohort. Keep internal approval distinct from client acceptance.

How do you build a benchmark your team will keep using?

Start with the question the benchmark must answer. A useful question is narrow, such as how long quotes above a stated value take to reach a decision. Broad questions produce averages nobody acts on.

Choose a comparable product panel

Examples to scope are Proposify, PandaDoc, Qwilr and Better Proposals. These are examples of proposal and quoting products, not a ranking or evidence that their workflows are identical. Record which products and workflows are in scope, and compare like with like.

For external context, Proposify's State of Proposals report is a named vendor-published source. Check its sample, period, metric definitions and publication date. Treat its figures as context, not as a like-for-like benchmark against your own records unless the cohort and measure match.

Get the data from source records

Use quote and proposal records from each system, rather than relying on marketing pages. Check for a record ID, creation and first-sent timestamps, status, version history or revision events, and acceptance or e-signature completion timestamp. Include an internal approval timestamp where that workflow applies, and keep it separate from client acceptance.

Where available, export records as CSV and calculate measures in Microsoft Excel or Google Sheets; Power BI can present a recurring dashboard. Confirm that each product actually provides the fields you need rather than assuming its records or exports match another system.

Benchmark rebuild: before and after

Before the rebuild

Baseline
Vendor deck figure
Sample
Unstated
Definitions
In someone's head
Source date
Missing
Review
Annual, if remembered

After the rebuild

Baseline
Own median
Sample
Written inclusion rules
Definitions
Written and versioned
Source date
Recorded per figure
Review
Quarterly, named owner

Before collecting data, work through the method in order:

  • Set the comparison question, eligible proposal or quote cohort, and collection period.
  • Record the baseline and the source of each data point, including the source page and date for any external figure.
  • Extract the required records and map each system's statuses and revision events to the definitions above.
  • Calculate the measures using the same start and end events, working-time rules and denominators across the cohort.
  • Check a sample of records against the source system, document exclusions and publish the definitions alongside the result.

Build a benchmark

Before the rebuild

Baseline
Figure quoted from a vendor deck
Sample
Unstated
Definitions
Held in someone's head
Source date
Missing
Review
Annual, if remembered

After the rebuild

Baseline
Your own median from system records
Sample
Quotes that meet written inclusion rules
Definitions
Written, dated and version controlled
Source date
Recorded beside every figure
Review
Quarterly, with a named owner

Once those definitions hold, a reporting dashboard makes the quarterly refresh a short job rather than a project, which is what keeps the benchmark alive past its first quarter.

Name an owner for the definitions as well as for the refresh. Publish the method alongside the result.

Readers who can see how a figure was produced will argue with the definition rather than the number, and that argument improves the next version.

Common questions

Where should the baseline sit?

Set it at the point your team already reports, even if that point is imperfect. A benchmark tied to existing reporting gets refreshed; one tied to a special exercise does not.

How often should a benchmark be refreshed?

Quarterly suits most sales teams, with an annual rebuild of definitions. Refresh sooner if pricing, product scope or the target segment changes.

Can we cite a vendor's published benchmark?

Yes, as context, provided you name the publisher, the date and the sample. Never present it as your own measurement.

What if a figure changes after publication?

Add a dated note rather than quietly editing the page. A visible correction is cheaper than a lost reader.

Filed underproposal softwarebenchmarkingsales metricsreportingB2B sales

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