90-day benchmark
6,810 sales enquiries
Average volume was about 76 sales-enquiry tickets per day, with one peak week reaching around 158 per day.
Live motion layer · Lead intake
Sales and Quote Capture Triage
Enquiries become quote context, clean tickets and human handoff
Use case · Real build pattern, generalised
Sales and quote capture triage
Capture enquiry context, quote intent, job details and escalation reasons before leads become messy tickets or missed callbacks.
Based on an anonymised 90-day sales-enquiry and quote-intake audit. These figures are planning inputs for workflow design, not universal guarantees or a named-client claim.
6,810 sales-enquiry tickets over 90 days3,531 quote-tagged tickets99.5% voice/API sales intake
Problem pattern
Sales queues are rarely just sales
High-volume enquiry queues mix quote requests, new orders, delivery issues, refunds, collections, equipment problems and people who just need a human quickly.
The first useful system should not chase every caller through a generic script. It should capture job type, dates, location, urgency and quote context, then route mixed support or problem cases differently.
Measured sales/quote data
Lead capture works best when it also filters non-sales pressure
The anonymised audit showed a large sales-intake queue, but also a strong mix of operational and problem tags. That makes clean triage more valuable than simply creating more tickets.
Quote workload
3,531 quote-tagged tickets
Quote requests were a major operational stream. In a 1,000-ticket sample, 57.3% carried a quote reason.
Intake shape
99.5% voice/API sales intake
Sales-enquiry tickets were overwhelmingly created through a voice/API route, making structured capture and handoff quality critical.
Triage risk
39.5% mixed with problem tags
Many “sales” enquiries also contained delivery, transport, collection, refund or equipment-problem signals, so they need routing, not blind lead treatment.
The useful automation goal is not “AI sells for you”. It is: capture the quote facts, detect when the enquiry is actually an operations issue, create a clean record, and give staff the shortest possible path to a proper answer.
Map quote facts
Define the minimum useful fields: job type, dates, location, urgency, item/service needed and customer contact route.
Separate intent
Classify quote, order, delivery, transport, collection, refund and equipment-problem signals before routing.
Create clean handoff
Write the ticket or CRM record with a short summary, missing fields and next action for the right human queue.
Measure lead quality
Track quote completion, callback speed, misroutes, repeat callers and handoff quality before expanding automation.
Next step
Want cleaner sales and quote handoffs?
Send one enquiry route, quote form or call pattern. We will map the first useful version and the human review boundary.