Pre-import data preparation for Shopify catalogs

Supplier CSVs arrive inconsistent and incomplete. CatalogLoom helps you evaluate whether your data can be prepared with far less manual work.

No Shopify access•No auto-imports•No credit card

Run Readiness Check

Supplier CSV (raw)

Capacity	Dimensions	Variant	Title
2L / 2000 ml	35×40×45 cm	S / Small / 42	Espresso machine pro 2l
350 ml	8 × 8 × 20 inches	L / Large / 46	Milk Frother deluxe
1.5 liters	diameter 12cm height 28cm	XL / X-Large	Cold Brew Maker large

After CatalogLoom (prepared)

Capacity(ml)	Dimensions(JSON)	Variant	Title	QA
2000	{"w":35,"h":40,"d":45}	Small	Professional Espresso Machine – 2L	0.92
350	{"w":20,"h":20,"d":51}	Large	Automatic Milk Frother – 350ml	0.63
1500	{"w":12,"h":28,"d":12}	X-Large	Cold Brew Maker – 1.5L Glass	0.91

Supplier CSV→CatalogLoom→Matrixify / Shopify

Start Your Readiness Check

Upload your supplier CSV or Excel file and see your data transformed. No signup required.

Upload Your Supplier File

Drop your CSV or Excel file here. Maximum 50 rows, 15MB file size.

Drag and drop your file here

or click to browse

Supports CSV and Excel files (.csv, .xlsx)

Supported file types:

CSV, XLSX, XLS (up to 50 rows, 15MB max)

Questions? Contact hendrik@catalogloom.com

Known data issues

Pattern	Issue
2L / 2000 ml / 2 liters	Mixed units
35×40×45 cm	Free-text dimensions
S / Small / 42	Variant ambiguity
—	Missing attributes

Reported: 15–20 hrs/week manual cleanup|Pre-import preparation — not Shopify

Import tools vs. preparation tools

Where current tools work

Matrixify, spreadsheets, scripts

✓Data already structured
✓Consistent units across rows
✓Predictable column formats
✓Complete fields, no inference needed

Where they break

Pre-import data preparation

✗Mixed unit formats (ml, L, oz)
✗Free-text dimensions
✗Missing or ambiguous values
✗Variant values needing inference

CatalogLoom handles the preparation step — before your import tool takes over.

System layer

InputSupplier CSV

→

↓

CatalogLoom

normalize•infer•flag

→

↓

OutputShopify CSV

→

↓

ImportMatrixify / Native

Not a Shopify app|Not an import tool|Pre-import preparation layer

System capabilities

Normalize

Unit conversion (ml, L, g, kg, oz, lb)
Decimal format standardization
Dimensions to structured JSON
Mixed supplier format handling

Infer

Option values from pick lists
SEO-friendly product titles
Product descriptions from source data
Shopify metafields (text, number, JSON)

Flag

Confidence score per inferred field
Review-required markers
Ambiguous value detection

Output: Shopify-compatible CSV|No Shopify access required|Nothing auto-imported

Human review stays in control

→Review only flagged rows

→Override any inferred value

→Nothing imports automatically

Readiness check

Is this supplier data a good fit for automated preparation?

1.Upload sample (up to 50 rows)

2.Configure column mappings

3.See transformed preview

No signup required. No data stored beyond session.

Output preview

Title	Capacity (ml)	Dimensions	QA
Professional Espresso Machine – 2Linferred	2000	{"w":35,"h":40,"d":45}	0.92ok

Immediate: Live preview of 3 transformed rows

By email: Readiness summary with fit assessment

Data handling

✓AWS us-east-1 processing

✓Auto-delete within 7 days

✓Manual delete available

✓No human access without invitation

✓Not used for training

Fit assessment

Good fit

✓Shopify agencies
✓Large, inconsistent supplier catalogs
✓Data preparation is the bottleneck
✓Existing Matrixify / import workflow

Not a fit

✗Small merchants, simple catalogs
✗Non-Shopify platforms
✗Expecting zero review
✗Already clean, structured data

If preparation isn't painful, this won't add value.