The Scenario
Every Friday afternoon, a CSV lands in your inbox from the time-tracking tool your agency uses. It has 80 to 100 rows — one per invoice — with external IDs, customer IDs, amounts, and due dates. Your billing ops specialist's job is to get all of them into Chaser before the weekend so the chasing sequence can start on Monday.
For the past three months, that job has meant opening the CSV in Excel, running a Power Query transform to fix the date format, importing the result into Chaser's bulk upload interface — which only accepts a specific column order and throws a generic error when a row fails validation.
The bad version:
- Paste the CSV into Excel, open Power Query, transform dates from MM/DD/YYYY to YYYY-MM-DD because Chaser's importer expects ISO, reorder columns to match the upload template.
- Upload into Chaser's import interface, get told "3 rows failed" with no indication of which rows or why — then cross-reference by hand until you find the ones with trailing spaces in the external ID field.
- Discover at row 82 that two invoices have the same external ID because the time-tracking tool generated a duplicate, and Chaser silently updated the wrong one.
By the time this is done it's close to 6 PM on a Friday. The billing ops specialist has spent two hours on a data movement task that should take five minutes.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the billing export in your worksheet, connects to Chaser through its built-in integration, and executes the bulk upsert — creating new invoices and updating existing ones — in one operation. Status comes back inline, per row.
With the weekly billing export pasted into your workbook, send this prompt:
Batch-upsert all invoice rows in this workbook to Chaser in one operation — use the external_id in column A to match, customer ID from column B, total amount from column C, and due date from column D. Write 'Created' or 'Updated' in column E for each row based on whether the invoice was new, and write any error message into column F.
What You Get
- Column E: "Created" or "Updated" for every row successfully processed
- Column F: The specific Chaser error message for any row that failed validation — malformed date, missing customer ID, duplicate external ID — so you know exactly which rows need attention and why
- The bulk upsert runs as a single API call to Chaser, not 80 sequential requests, so the rate limit is not a concern
- Any row where column F has an error can be fixed and re-run without touching the rows that already succeeded
What If the Data Is Not Quite Ready
The due dates are in MM/DD/YYYY format and Chaser needs ISO
Convert all values in column D from MM/DD/YYYY to YYYY-MM-DD format, then batch-upsert all rows to Chaser using external_id from column A, customer ID from column B, amount from column C, and the converted due date from column D — write 'Created' or 'Updated' into column E and any errors into column F.
Some external IDs have trailing spaces that cause Chaser to treat them as new invoices
Trim all values in column A before the upsert, then batch-upsert to Chaser using the trimmed external_id, customer ID from column B, amount from column C, and due date from column D — write the result status into column E and any errors into column F.
Skip any rows that have already been marked 'Created' or 'Updated' in column E from a previous run
Batch-upsert all rows in this workbook where column E is empty — using external_id from column A, customer ID from column B, amount from column C, and due date from column D. Write 'Created' or 'Updated' into column E and errors into column F, leaving already-processed rows untouched.
Trim IDs, convert dates, deduplicate by external_id, upsert, and write back status — all at once
Trim all values in column A, convert column D dates from MM/DD/YYYY to YYYY-MM-DD, deduplicate rows by keeping the last occurrence of each external_id value, then batch-upsert the cleaned rows to Chaser using column A for external_id, column B for customer ID, column C for amount, column D for due date — write 'Created' or 'Updated' into column E and any error messages into column F.
The pattern: all the preprocessing — trimming, date conversion, deduplication — goes into the same prompt as the upsert. You get one clean operation instead of a sequence of manual steps.
Try It
Get the 7-day free trial of SheetXAI and open next Friday's billing export in Excel, then ask it to batch-upsert the full run into Chaser in one shot. For related reading, see how to bulk create customers and opening invoices or pull overdue invoices ranked by exposure using SheetXAI with Chaser.