Product · analytics
Quoting instantly means finally having the data
When quoting happens by e-mail, the enquiries that never became orders leave no trace. When it happens in a widget, every one of them is a measurement: what was asked for, what it was priced at, and where the buyer stopped.
Where quoting stops being quoting
Parts analysed, prices shown, quote requests, quotes saved, manual quote requests and orders placed - as counts. A big drop between “price shown” and “quote saved” is a pricing conversation. A pile of failed analyses, under operations, is a file-format conversation. They need different fixes and the numbers tell you which one you have.
What your market actually wants
Materials and options
Which materials, colours and finishes buyers choose, and how often.
Oversize attempts
How many parts arrived too big for any machine you have - useful when you are deciding which machine to buy next.
DFM findings
Manufacturability findings by code, and the reasons lines went to review or were blocked. The parts that keep failing are a pattern, not bad luck.
Revenue
Quoted against ordered value by day, with the average order and the conversion, counted from the quotes and orders themselves.
Operations
Analyses done and failed, the review queue, and how many webhook deliveries arrived.
Usage
Quote requests against your quota, per configuration, per day, with a CSV when you want to do your own arithmetic.
No vanity metrics
Counts are of things that happened, not of things that might have. A re-price when a buyer changes quantity is not a new quote request and is not counted as one, on your bill or in your funnel. Everything is a UTC calendar day, inclusive, so two reports of the same week agree.
And you can take it away: usage exports as CSV, and the export is the data rather than a picture of it.
Find out what you have been missing
Most shops are surprised by at least one thing in the first month.