Documentation

Analytics should clarify collections behavior, not bury it.

The analytics layer is there to help owners understand what is being recovered, what is lagging, and which accounts create repeated drag on cash flow.

Steps

How to handle analytics in ChaseNow

Use the date filter to focus on the week, month, quarter, or full period that matters.

Review expected collections against what actually landed.

Check average invoice value and overdue patterns to spot cash flow drag.

Use client behavior sections to identify accounts that repeatedly pay late.

Analytics view

Recovery metrics tied to real invoice states

Expected versus collected
Average invoice value
Accounts to watch by payment behavior
Good analytics here are practical: what is open, what is slowing, and which clients deserve tighter handling next time.

Notes

Operational notes

Analytics are only as accurate as the invoice statuses feeding them.

The goal is operational clarity, not vanity reporting.

Client behavior patterns are especially useful when you need to tighten terms on repeat slow payers.

FAQ

Are these analytics about collections or accounting?

Collections. They focus on invoice state, recovery pace, and payment behavior rather than full financial reporting.

Why does expected differ from collected?

Expected reflects what should land in the selected period, while collected reflects what owners have actually confirmed as paid.

Related pages

Next step

Use the docs, then put the workflow to work.

The goal of the documentation is not to describe software in the abstract. It is to help you get an invoice into ChaseNow and keep the follow-up moving.