Sales quote reporting: close rate, revenue won and rep performance

What quote reporting covers

Because quotes, signatures and deals all live in one app, the numbers come from what happened to each quote. Nobody has to fill in a field for the report to be right.

The report answers five questions:

• How many quotes went out? The count of quotes sent in the window.
• How many were opened? The count viewed.
• How many closed? The count signed.
• What is the close rate? Signed divided by sent for the window.
• What did we win? Revenue won from signed quotes.

Managers and admins also see a per-rep table with the same measures side by side.

How the numbers get there from a live call

Every figure is a by-product of normal selling. When a rep saves a quote in live presentation mode and sends it, the quote is counted as sent. When the buyer opens the share link, it becomes viewed. When the last signer completes the e-signature, it becomes signed.

The other tracked statuses, declined, expired and voided, are recorded the same way. Repeat views from the same browser within 30 minutes are deduplicated, so a buyer refreshing the page does not inflate view counts.

Since the definitions are fixed and the events are system-recorded, two managers looking at the same window see the same close rate.

Filters, date ranges and CSV export

• Date presets and custom ranges. Pick a preset or set your own start and end dates.
• Filter by rep. Look at one person's quotes alone.
• Filter by form. Compare how different quote forms perform, for example a new pricing layout against the old one.
• CSV export. Export quotes and deals to CSV for finance, for a board deck or for your own analysis.

The filters work together. You can look at one rep, on one form, for one quarter, and the counts, close rate and revenue won all recalculate for that slice.

Access follows role. Reps see only their own data. Managers and admins see the whole organization and the per-rep table. The same rule applies across the app: reps see their own quotes, contacts and deals, and managers and admins see everything.

Sample walkthrough: a monthly pipeline review

This is an illustrative example with a made-up company and made-up numbers, shown only to explain how the figures relate. Juniper Row Software (fictional) has a sales manager reviewing last month.

1. She selects last month as the date range. The report shows 40 quotes sent, 31 viewed and 10 signed.
2. The close rate reads 25 percent, which is 10 signed divided by 40 sent.
3. Nine quotes were never opened. She filters by rep and finds most of them belong to one person, which points to a follow-up habit and not a pricing problem.
4. She filters by form. The new packaged form and the older custom form show different close rates for the same period, so she has a concrete question to bring to the team.
5. She exports quotes and deals to CSV and sends the file to finance.

Each rep can open the same report and see their own numbers for the same window.

The point of the example is the order of the questions: start with the window, read the three counts, then use the rep and form filters to find out where the gap between sent and signed comes from.

What it replaces and what it pairs with

This replaces the weekly spreadsheet where reps self-report what they sent and what closed. It also replaces the guesswork about whether a quote was ever opened.

The home dashboard complements the report with a quote status breakdown, a quote activity trend and a pipeline funnel from the built-in CRM, where each deal's value is weighted by its stage probability. A top reps leaderboard is visible to managers and admins.

If you need the data somewhere else, CSV export is the standard route. Teams on the Enterprise plan can also use the REST API and outbound webhooks to send quote events to their own systems.