Copy-paste formulas for product categorization
Paste a formula into row 2, test it on a few rows, then drag down to run the workflow across your spreadsheet.
Assign a category
A: product title · B: description · C: allowed taxonomy
=GPT("Assign this product to exactly one category from this allowed list: " & C2 & ". Product: " & A2 & ". Description: " & B2 & ". Return only the category name. If none fit, return Uncategorized [review].")
Extract attributes
A: title · B: description · C: attributes to extract
=GPT("Extract these attributes as a compact key:value list from the product: " & A2 & ". Description: " & B2 & ". Attributes: " & C2 & ". If an attribute is not stated, mark it unknown. Do not invent values.")
SEO title + description
A: product · B: key attributes · C: brand voice
=GPT("Write an SEO product title (<=60 chars) and meta description (<=155 chars) for: " & A2 & ". Key attributes: " & B2 & ". Brand voice: " & C2 & ". Factual, no unverifiable claims. Return title | description.")
QA / consistency flag
A: row output · B: allowed taxonomy
=GPT("QA this product row: " & A2 & ". Allowed taxonomy: " & B2 & ". Flag off-taxonomy categories, invented attributes, and claims not supported by the description, then return pass/review/fail.")
Short answer
AI product categorization in Google Sheets is a workflow for ecommerce and catalog teams who need to classify, tag, and enrich a large product list without doing it SKU by SKU. GPT for Sheets runs AI formulas across a table of product title, description, and your taxonomy, producing category assignments, extracted attributes, and SEO copy in adjacent columns — constrained to your allowed values.
Fastest path: Install GPT for Sheets → add product and taxonomy columns → paste a formula from the formula section → review 10 rows → fill down. For plans, see GPT for Sheets pricing.
This page is for purchase-intent catalog and merchandising teams that already work in spreadsheets.
Workflow
A practical sheet for this workflow usually has these columns:
| Column | What to put there | Why it matters |
|---|---|---|
| A | Product title | Stable row anchor |
| B | Raw description / specs | Evidence the model classifies from |
| C | Allowed taxonomy / attribute list | Constrains output to valid values |
| D | Assigned category | The catalog field you need |
| E | Extracted attributes | Powers filters and facets |
| F | SEO title + description | Improves product page discoverability |
| G | QA / consistency flag | Stops off-taxonomy and invented values |
Step-by-step setup
- Start with 10 representative products before filling down.
- Keep raw fields unchanged; write outputs to new columns.
- Constrain category output to your allowed taxonomy.
- Add rules: never invent attributes, mark unknown when not stated.
- Add a QA formula that flags off-taxonomy or unsupported output.
- Fill down, then review flagged rows before publishing.
Why categorize in a spreadsheet
Catalog data usually starts or lands in a spreadsheet anyway. Categorizing there — with the product, the assigned category, and a QA flag side by side — lets you constrain output to your real taxonomy, test on 10 SKUs, and export clean data to your store, instead of fixing categories one product at a time in the storefront admin.
Copyable formula notes
Paste the cards into row 2 and drag down. Always pass your allowed taxonomy so categories stay valid, and keep the “do not invent attributes” rule so specs stay trustworthy.
Use cases
- Assign each SKU to exactly one valid category.
- Extract structured attributes for filters and facets.
- Draft SEO titles and descriptions at catalog scale.
- Flag off-taxonomy categories and unsupported claims.
Best for / not best for
Best for: ecommerce and catalog teams that manage product data in Sheets and want consistent, constrained categorization and enrichment.
Not best for: publishing AI attributes or claims without review, or categorizing against a taxonomy you have not supplied.
Use GPT for Sheets as the classification, enrichment, and QA layer on top of your catalog export.
Internal links and next workflows
- GPT for Sheets
- GPT for Sheets pricing
- Data cleaning for CRM imports
- Sentiment tagging for reviews
- ABM target account list building
Safety, compliance, and data quality
Constrain categories to your real taxonomy, never let the model invent attributes, and keep claims supported by the product description. Treat AI output as a draft, keep raw columns intact, review flagged rows, and publish only what passes. A pass / review / fail QA column protects catalog quality.
Frequently Asked Questions
What is the fastest way to categorize products in Google Sheets?
Install GPT for Sheets, add product and taxonomy columns, paste one category formula into row 2, review a sample, then fill down across the catalog.
Will it stick to my category list?
Yes, when you pass your allowed taxonomy in the formula and instruct it to return Uncategorized [review] when nothing fits. Review flagged rows before publishing.
Can it write product SEO copy too?
Yes. It can draft constrained SEO titles and meta descriptions from the attributes you provide. Keep claims factual and review before publishing.
Do I need to copy and paste between ChatGPT and Sheets?
No. GPT for Sheets runs AI formulas directly in spreadsheet cells, which is better for repeatable bulk categorization and QA review.
Start this workflow in Google Sheets
If your catalog already lives in spreadsheets, install GPT for Sheets and categorize and enrich it where your rows already live.
Install GPT for Sheets or compare plans to turn a raw catalog into categorized, enriched, SEO-ready product data.