The Scenario
You manage the product catalog for an e-commerce brand that sells on three channels. Your master product sheet has 200 rows — one per SKU — and columns for name, price, and category. BoxHero stores a bunch of additional product detail that your sheet doesn't have: weight, color, material, vendor code, and a handful of custom attributes that the logistics team added over the past year.
Your merchandising lead just asked for a complete product data export — "everything we know about each product" — to send to a new 3PL partner. The 3PL wants it in a single spreadsheet. You have half of it in Google Sheets and the other half scattered across BoxHero product records.
The bad version:
- Open BoxHero, search for SKU 1, open the item record, read off the custom attributes, switch to your sheet, find the matching row, type in each field.
- Repeat 199 more times.
- Discover around row 40 that some custom attributes are named differently in BoxHero than what your sheet expects ("item_weight_kg" vs. "Weight (kg)") and you've been pasting into the wrong column since row 12.
Your merchandising lead needs the sheet by end of week for a handoff call. Entering 200 product records by hand isn't the job — but here you are.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that runs inside your Google Sheet. It reads your existing product data, connects to BoxHero through its built-in integration, and fetches custom attribute values for each SKU — writing them into new columns without touching your existing data.
For each item ID in column A of my Google Sheet, look up its BoxHero custom attributes and write each attribute as a new column
What You Get
- New columns appended to the right of your existing data, one per BoxHero custom attribute.
- Attribute names as column headers in row 1.
- Attribute values written into the matching row for each SKU.
- SKUs not found in BoxHero get a note in a flag column rather than silently writing blanks across all attribute columns.
What If the Data Is Not Quite Ready
BoxHero attribute names don't match the column headers your 3PL expects
For each item ID in column A, fetch BoxHero custom attributes. Rename "item_weight_kg" to "Weight (kg)", "color_code" to "Color", and "material_type" to "Material" as you write the headers. Leave other attribute names as BoxHero stores them.
You only need a specific subset of attributes, not all of them
For each item ID in column A, fetch the BoxHero custom attributes named "weight", "color", and "vendor_code" only. Write each as a new column. Skip all other attributes.
Some rows have SKUs that are formatted differently from BoxHero item IDs
For each value in column A, treat it as a BoxHero item barcode rather than item ID. Look up the matching item record and write its custom attributes as new columns. Flag any barcodes with no BoxHero match in column Z.
Full kill chain — normalize, enrich, flag gaps, validate against 3PL required fields
For each item ID in column A, fetch all BoxHero custom attributes. Rename attributes to match the 3PL field names in this mapping: weight_kg → Weight, color → Color, material → Material, vendor_code → Vendor Code. Flag any row missing "Weight" or "Vendor Code" with "Missing required field" in column M — those are the two the 3PL has marked mandatory. Items not found in BoxHero should be flagged in column N.
One prompt does the enrichment, the renaming, and the validation in one pass.
Try It
Open your product master sheet and get the 7-day free trial of SheetXAI — then ask it to pull BoxHero custom attributes for every SKU in column A. You can also see how SheetXAI handles stock level queries or browse the full BoxHero integration overview.