Flooring Data Collection
Budget: $10 – $30 CAD
Project: Laminate & Engineered Hardwood Flooring Data Entry
Core Objective
Collect laminate and engineered hardwood product data with photos from provided websites at the lowest possible price.
Task Summary
Manually or automatically collect flooring product information. You can use any approach (manual entry, basic scraping, automation tools) - the price must be the same (lowest possible rate). Focus on accuracy and completeness.
Two Product Categories to Collect
1. LAMINATE FLOORING - Collect These Fields:
Brand
Product Name / Style
Collection / Series
Price (and Price per Sq Ft)
Color
Color Family / Tone
Plank Width
Plank Length
Thickness (mm)
AC Rating (AC1-AC6)
Water Resistance (with hours if available)
Wear Layer Thickness
Bevel Type
Surface Texture
Gloss Level
Installation System
Attached Underlayment
Warranty Length
Radiant Heat Compatible
Product Page URL
Photo Filename
2. ENGINEERED HARDWOOD - Collect These Fields:
Brand (Company)
Product Name / Style
Collection / Series
Price per Sq Ft
Color / Finish
Species
Plank Width
Plank Length
Thickness (mm)
Wear Layer / Veneer Thickness
Surface Texture
Grading
Board Variation
Country of Origin
Installation Methods
Core Type
Top Layer Finish
Warranty
Moisture Resistance
Product Page URL
Photo Filename
Photo Requirements for BOTH:
Download main product photo for each product/style/color
Rename photos using format: [Brand]_[Collection]_[ProductName]_[Color].jpg
Example: Pergo_PremiumCollection_Oak_Honey.jpg
Save all photos in organized folders (one for laminate, one for engineered)
Key Points:
You choose the method (manual or automated)
Same price either way (lowest possible rate)
I provide the website URLs
Deliver clean CSV/Excel + organized photos
Payment upon complete delivery
Deliverables:
Two spreadsheets (laminate.csv, engineered.csv)
Two photo folders with properly named images
Verification that all products were captured
Note: If you can scrape it quickly with simple tools, do that. If manual entry is cheaper for you, do that. I pay the same low price regardless of your method.
Core Objective
Collect laminate and engineered hardwood product data with photos from provided websites at the lowest possible price.
Task Summary
Manually or automatically collect flooring product information. You can use any approach (manual entry, basic scraping, automation tools) - the price must be the same (lowest possible rate). Focus on accuracy and completeness.
Two Product Categories to Collect
1. LAMINATE FLOORING - Collect These Fields:
Brand
Product Name / Style
Collection / Series
Price (and Price per Sq Ft)
Color
Color Family / Tone
Plank Width
Plank Length
Thickness (mm)
AC Rating (AC1-AC6)
Water Resistance (with hours if available)
Wear Layer Thickness
Bevel Type
Surface Texture
Gloss Level
Installation System
Attached Underlayment
Warranty Length
Radiant Heat Compatible
Product Page URL
Photo Filename
2. ENGINEERED HARDWOOD - Collect These Fields:
Brand (Company)
Product Name / Style
Collection / Series
Price per Sq Ft
Color / Finish
Species
Plank Width
Plank Length
Thickness (mm)
Wear Layer / Veneer Thickness
Surface Texture
Grading
Board Variation
Country of Origin
Installation Methods
Core Type
Top Layer Finish
Warranty
Moisture Resistance
Product Page URL
Photo Filename
Photo Requirements for BOTH:
Download main product photo for each product/style/color
Rename photos using format: [Brand]_[Collection]_[ProductName]_[Color].jpg
Example: Pergo_PremiumCollection_Oak_Honey.jpg
Save all photos in organized folders (one for laminate, one for engineered)
Key Points:
You choose the method (manual or automated)
Same price either way (lowest possible rate)
I provide the website URLs
Deliver clean CSV/Excel + organized photos
Payment upon complete delivery
Deliverables:
Two spreadsheets (laminate.csv, engineered.csv)
Two photo folders with properly named images
Verification that all products were captured
Note: If you can scrape it quickly with simple tools, do that. If manual entry is cheaper for you, do that. I pay the same low price regardless of your method.
Related categories:
Data Processing
Data Entry
Excel
Web Scraping
Data Mining
Data Analysis
Data Collection
Data Management