The Problem With Getting Workbook Data In and Out of Chaser
You have an Excel workbook full of data — overdue invoice lists, client IDs, payment amounts, aging calculations. You need it pushed into Chaser, or pulled back out, without rebuilding the same export-clean-sort routine every time your AR team needs a current view.
Chaser is good at automating the chase — sending reminders, tracking communication history, escalating at-risk accounts. But the moment you want to analyze its data inside Excel, or load an invoice batch from an external system, the gap between the two tools is on you to bridge. Most AR teams default to a CSV export from Chaser, a Power Query clean-up step to fix the date formatting, a manual sort, and then start over next week.
Below are the four common ways teams handle this. Only the last one scales.
Method 1: Manual CSV Export and Import
The default for Excel users. You pull a CSV from Chaser's export interface, open it in Excel, run a quick Power Query transform to reformat dates and strip phantom columns, sort by overdue amount, and share the file.
That routine might feel manageable the first few times. By week six, when the export drops decimal precision on large amounts and the sort has been silently wrong because someone formatted the date column as text, the routine becomes a problem. AR teams running this cycle tend to end up with a SharePoint folder full of slightly-wrong snapshots that different people are working from without realizing it.
Method 2: Power Automate
Power Automate has Chaser connector support. You can trigger a flow when an invoice status changes in Chaser and write a row into an Excel table, or trigger on a new Excel row to push invoice records into Chaser.
Honest question before you invest time here — do you know what a connector action is? Have you configured trigger conditions in a cloud flow? Can you debug a 400 response from the Chaser API by reading the error body? If those feel like the wrong questions, skip to Method 3 or 4.
Still here? The flow itself is achievable. A status-change trigger keeps the Excel table current without manual exports, and a new-row trigger pushes batches into Chaser without UI clicks. Getting there means selecting the right trigger event, mapping every Chaser field to its Excel column, handling the date format mismatch between Chaser's ISO timestamps and Excel's serial number format, and landing on the right Power Automate plan.
But a row-level flow is not a bulk operation.
Running 80 overdue invoices through a Power Automate flow means 80 separate HTTP actions — 80 separate chances to hit a rate limit, 80 rows in your run history, and no reliable way to detect which ones quietly failed when Chaser rejects a malformed field.
You probably just need a sorted list of high-exposure accounts to drive your collection calls. You probably have no idea how to write the expression that maps Chaser's date fields to Excel's format, and honestly you shouldn't need to. So this goes to whoever on your team builds automations — and now you're waiting for a Slack reply while the week's call block sits idle.
Once you need aging buckets, cross-tab lookups, or conditional flags written back inline, you've outrun what a row-level flow handles natively.
Method 3: The Previous Generation — Connector Add-Ons
Until recently, the best repeatable option for Excel-to-Chaser data movement was a category of add-ons that let you configure column mappings, save a template, and run it against Chaser's API on a schedule. You specified the object type, you tagged your fields, you saved the config.
That was a meaningful step up. Consistent output run to run, reusable configs, no manual export reformatting every Monday.
But the field mapping was yours to maintain. The filter logic was yours. The aging calculation was yours. The add-on moved the data through. The thinking stayed entirely with you. And when Chaser's response schema changed — which it does — your saved config would silently return empty columns until someone traced the breakage back to a renamed field.
This is the previous generation. It worked, but it asked a lot of the person maintaining it.
The Easy Way: Using SheetXAI in Excel
There is a different way entirely. SheetXAI is an AI agent that lives inside your Excel workbook. It reads the workbook, understands what you are looking at, and through its built-in Chaser integration it can push to or pull from Chaser for you — no template to configure, no flow to build, no manual reformatting. You just ask.
Example 1: Pull all overdue invoices, ranked by exposure
Fetch all invoices from Chaser with an AUTHORISED status and a due date before today, calculate days overdue, and write invoice number, customer name, amount, due date, and days overdue into columns A through E sorted by amount descending.
SheetXAI calls Chaser, runs the aging calculation, sorts the results, and writes everything into the workbook. Your AR team opens the file and starts calling.
Example 2: Bulk-create customers and opening invoices from a new client list
For each row in this workbook, bulk-upsert the customers into Chaser using company name in column A, email in column B, and external ID in column C — write the returned Chaser customer ID into column D. Then for each ID in column D, create an invoice in Chaser with the amount in column E, due date in column F, and description in column G — write the resulting invoice ID into column H.
The pattern: instead of logging into Chaser to create each client record manually, you send the whole batch in one prompt. SheetXAI handles the two-step sequence — customers first, then invoices against the returned IDs — and writes both confirmations back into the workbook inline.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with invoice data or a list of clients you need in Chaser, then ask it to do one of the tasks above. The Chaser integration is included in every SheetXAI plan.
More Chaser + Excel guides
Pull Overdue Invoices From Chaser Into a Google Sheet, Ranked by Amount
Fetch every invoice past due from Chaser, calculate days overdue, and sort them into a prioritized Google Sheet so you can start with the highest-value calls first.
Bulk Create Customers and Opening Invoices in Chaser From a Google Sheet
Onboard a batch of new clients into Chaser — customers and their first invoices — directly from a Google Sheet, without touching the UI one row at a time.
Batch Upsert a Weekly Invoice Export Into Chaser From a Google Sheet
Push an entire week's billing export into Chaser in one operation, creating new invoices and updating existing ones, with status written back to the sheet.
Export Credit Notes and Overpayments From Chaser Into a Google Sheet for Matching
Pull all unallocated credits and overpayments out of Chaser and match them against open invoice balances directly inside your Google Sheet.
Audit All Chaser Customer Contacts Into a Google Sheet
Export every Chaser customer and their contact persons into a Google Sheet and flag any account with a missing or invalid primary email before you enable automated chasing.
Bulk Attach Invoice PDFs to Chaser Records From a Google Sheet
Upload a folder of signed invoice PDFs to their matching Chaser invoice records using a Google Sheet as the mapping file — no manual attachment clicking required.