BENCHMARKS
The numbers the hunt actually runs on.
Forwarder sales content is thick with statistics nobody can trace. This page holds the ones that survive checking — the win-rate curve, the follow-up scoreboard, the response-time evidence and the seller’s week — with the source named on every row, secondary figures flagged, and the famous fakes named and left out.
SOURCES: WEBCARGO/FREIGHTOS · FREIGHTOS MYSTERY SHOPPER · MIT/OLDROYD · HBR · SALESFORCE · UPDATED JULY 2026
The win-rate curve
The strongest dataset in forwarder sales is the WebCargo/Freightos analysis of 500,000 quotes (2025). It measures one thing from two angles: how much easier winning gets as a customer moves from stranger to regular. It is vendor-published — WebCargo is a Freightos company — but it is the only quote-level win-rate data of this size in the public domain, and we label it accordingly.
| Figure | What it measures | Source |
|---|---|---|
| 13.4% | win rate when quoting new customers | WebCargo/Freightos 500,000-quote analysis, 2025 (vendor analysis) |
| 22.7% | win rate when quoting existing customers — 1.7x the new-customer rate | WebCargo/Freightos 500,000-quote analysis, 2025 (vendor analysis) |
| 10.5% | win rate with customers who sent a single quote request | WebCargo/Freightos 500,000-quote analysis, 2025 (vendor analysis) |
| 20.6% | win rate with customers at 21–50 quotes — roughly double the one-quote rate | WebCargo/Freightos 500,000-quote analysis, 2025 (vendor analysis) |
SOURCE: WEBCARGO/FREIGHTOS 500,000-QUOTE ANALYSIS (2025) · VENDOR ANALYSIS, LABELLED AS SUCH
Read as a curve, not four numbers: the path from new to existing roughly doubles your win rate, and the doubling happens quote by quote. That is the entire argument for working wallet share as deliberately as new logos — the hunt gets you the first quote; the next twenty are where the odds move.
The follow-up scoreboard
Freightos ran a mystery-shopper exercise: pose as a shipper, request quotes, count what happens. The results are the most damning numbers in the industry — and the cheapest to beat, because the bar is set by forwarders who never call back.
| Figure | What it measures | Source |
|---|---|---|
| 60% | of quote requests were never quoted at all — the enquiry died in an inbox | Freightos mystery-shopper study (secondary, via Quotiss) |
| 8% | of forwarders who did quote ever followed up on that quote | Freightos mystery-shopper study (secondary, via Quotiss) |
SOURCE: FREIGHTOS MYSTERY-SHOPPER STUDY · CITED SECONDARY VIA QUOTISS — FLAGGED UNTIL THE ORIGINAL IS LOCATED
Multiply the two: of the requests that arrive, roughly 40% get a quote, and roughly 8% of those get a follow-up — about three follow-ups per hundred enquiries. A cadence policy that guarantees one follow-up per quote is not sophistication; it is showing up. The desk-side chase of individual quotes belongs to our sibling aiquotedesk.com — what belongs here is the sales motion that makes following up a rule instead of a mood.
The response-time evidence
The follow-up scoreboard says most forwarders never come back. The response-time literature says the ones who come back fast collect outsized odds. Neither study is freight-specific — both are B2B lead-response research — but the mechanism (a buyer actively shopping, attention decaying by the minute) describes an RFQ inbox exactly.
| Figure | What it measures | Source |
|---|---|---|
| 100x | contact odds calling a web lead within 5 minutes vs 30 minutes | MIT/Oldroyd Lead Response Management study |
| 21x | qualification odds at 5 minutes vs 30 minutes, same study | MIT/Oldroyd Lead Response Management study |
| 7x | qualification odds responding within 1 hour vs firms that waited longer | Harvard Business Review, 2011 (audit of 2,241 US firms) |
SOURCES: MIT/OLDROYD LEAD RESPONSE STUDY · HBR 2011 · B2B LEAD-RESPONSE RESEARCH, NOT FREIGHT-SPECIFIC
This is why a first-touch window is written into cadence policy rather than left to inbox archaeology: an RFQ email that becomes a pipeline card at 07:41 with a first-touch clock running is the entire response-time literature, operationalized.
The seller’s week
The last pair of numbers explains why good reps miss cadences anyway: selling is a minority share of a seller’s week, and the tool meant to fix that fails more often than it works when it is bought as a database instead of a discipline.
| Figure | What it measures | Source |
|---|---|---|
| 28% | of a sales rep's week spent actually selling — the rest is admin, data entry and internal work | Salesforce State of Sales |
| 50–63% | reported CRM implementation failure rates across studies | Multiple industry studies (secondary; ranges vary by definition of failure) |
SOURCES: SALESFORCE STATE OF SALES · CRM FAILURE FIGURES SECONDARY, FLAGGED
Across FIATA’s roughly 40,000 forwarding firms — in India, around 85% of them small operators — the selling minutes are the scarcest resource on the floor. A CRM that adds typing subtracts selling; that is the case for voice-logged activities and for a queue that ranks itself, and it is also the honest reading of the failure rates: CRMs fail when they demand admin and return reports.
The numbers you won’t find here
“80% of sales take five follow-ups” — the most-quoted statistic in sales content — is absent from this site by choice. Its usual attribution (a national sales association) has never been verified, and no primary source has ever surfaced. We checked; we don’t use it. Follow-up discipline needs no fake numbers when the real ones — an 8% follow-up rate — are this bad.
No public benchmark of forwarder outbound cadence exists — touches per won deal, first-touch-to-quote time, cadence-to-win curves. We searched; nobody has published it. The board intends to: as live desks accumulate history, we will publish anonymized cadence-to-win data — how many touches, at what spacing, precede a won forwarding deal. Until then, every number above carries its source, and the gaps stay labelled as gaps.
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