How to Connect Retailed to Excel (4 Methods Compared)

The Problem With Getting Workbook Data In and Out of Retailed

You have an Excel workbook full of SKUs, product references, and inventory counts. You need the current market pricing from StockX, GOAT, or one of the fifty-plus platforms Retailed covers — and you need it matched to every row, not just spot-checked for one or two items.

Retailed is good at providing real-time resale pricing across multiple marketplaces through a single unified API. But the path from your workbook to that data is longer than it looks. The usual flow is: export a CSV, write a script against the Retailed API, paste the results back in, and hope the column order held.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: CSV Export and Manual Merge

You export your SKU list as a CSV, run it through whatever script or tool you have access to, get results back in a second file, open both in Excel, and paste columns across while matching row order. If anything is out of order — a missing SKU, a case mismatch — the merge silently populates the wrong row.

Doing this once is fine. Doing it before every weekly buying call means the first thing you do each Monday is reconcile two CSV files instead of analyzing the data they contain.

Method 2: Power Automate

Power Automate has flow templates that can call external APIs and write results back to Excel. You can build a flow that reads each SKU from your workbook, hits the Retailed API, and writes the response fields back to corresponding columns.

Quick check before you continue: do you know how to configure an HTTP action in Power Automate? Parse JSON? Set up dynamic expressions for row indexing? If those don't ring a bell, you'll spend more time debugging the flow than you would just doing the lookup manually — head to Method 3 or 4.

If you've built flows before, the setup is workable. You authenticate to the Retailed API, configure the HTTP request with the SKU as a parameter, parse the JSON response, and use a condition to write fields back to the right row. It runs.

But the flow fires one row at a time.

Two hundred SKUs means two hundred HTTP calls, two hundred flow runs, and a run history that's painful to scan when row 87 returns a schema you didn't expect because the product had been delisted.

You probably just need a full market snapshot across your whole workbook, and you probably have no idea how to build a Power Automate flow with error branches for partial API responses. So you either figure it out yourself over two hours or you ask your IT contact and wait. Neither is a great use of your morning.

And the moment you want both GOAT and StockX data in the same row, you're chaining two separate HTTP calls per row, which doubles the run time and the failure surface.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for recurring workbook ↔ market data workflows was a category of add-ins that let you configure column mappings, save templates, and run them on demand. You mapped your SKU column, tagged the output fields, saved the config, and ran it.

That was a real step up from the CSV merge. Consistent output, reusable configs, no file juggling.

But you were still responsible for the field mapping, the query parameters, the handling of SKUs that returned no match, and the conditional logic around which rows to include. The tool got the data through, but the thinking was still yours. And when a worksheet was renamed or a column inserted before column A, the config broke silently until someone noticed the data was wrong.

This is the previous generation. It worked, but it asked a lot.

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're looking at, and through its built-in Retailed integration it can query StockX, GOAT, or any supported marketplace for you. No field mapping, no flow configuration, no file juggling. You just ask.

Example 1: Bulk price lookup for an inventory list

Read all SKUs in column A of my Excel StockList tab, query StockX via Retailed for each one, and paste the product name, colorway, and price range (low ask to high bid) into columns B, C, and D

Every row gets populated in one pass. Rows where the SKU returns no result get flagged, not silently skipped.

Example 2: Cross-platform comparison in one prompt

Read the Sneakers tab in Excel (column A = product ID), get GOAT prices and StockX prices for each item via Retailed, and write GOAT low ask in column B and StockX low ask in column C

The pattern: instead of building two separate flows and joining the output manually, you ask for both in one prompt. SheetXAI handles the cross-platform lookup inline.

Try It

Get the 7-day free trial of SheetXAI and open any Excel workbook with a column of sneaker SKUs or product references, then ask it to fetch the current StockX or GOAT pricing for every row. The Retailed integration is included in every SheetXAI plan.