Label spreadsheet rows
Category, missing info and a review flag for every product in the catalog.
Try it on this example
Product name: Women's Trail Runner GTX
Other columns, each as column: value: sku: FW-TR-2291 | size: 39 | colour: Slate/Coral | upper material: (empty) | weight: 290 g | image: (empty) | gender: (empty)
Product description
- Which catalog category does this product belong to?Shoes100%
- Who is this product made for, by fit or by how it is sold?Women100%
- Does the product row leave out a detail the catalog requires for its category?Yes98%
- Do the product name, description and columns contradict each other about the product?Yes93%
- Does the product row contain placeholder text or internal notes that must not go live?No78%
- Is there enough in the product row to tell what the product is?Yes97%
These are real answers stored from one run on this example.
The prism behind it
Label spreadsheet rows
Fields
- Product name
- Product description
- Other columns, each as column: value
Context
The rows come from the product catalog of Fellway Outdoor, an online outdoor clothing and footwear shop. Each row is one product: its name, its description, and the other catalog columns written as "column: value", where "(empty)" means the cell is blank. The answers fill the category and gender columns and flag rows for the catalog team to fix before the product goes live. A person fixes the row; nothing is published or removed on these answers. What every product row must give before it goes live: - Shoes: size, colour, upper material and an image link. - Clothing: size, colour, fabric and an image link. - Gear: colour or finish, weight, material and an image link. Size where the product comes in sizes, such as a backpack or a sleeping bag. - Accessories: colour, material and an image link. Size where the product comes in sizes, such as gloves or hats. A detail counts when it appears in the name, the description or its column.
Questions
Which catalog category does this product belong to? Choice
Go by what the product is, from the name and description, not by the column values alone. Pick one option.
Who is this product made for, by fit or by how it is sold? Choice
Go by what the row says, such as "women's" or "men's fit" in the name or description, or a gender column. When a shoe, garment or accessory made to fit a body does not say who it is cut for, choose the insufficient information option rather than guessing.
Does the product row leave out a detail the catalog requires for its category? Yes / No
Use the list for the product's category in the context. A column marked "(empty)" does not count as given unless the detail appears in the name or description. Yes: At least one required detail is missing from the row. No: Every detail the category requires is given somewhere in the row.
Do the product name, description and columns contradict each other about the product? Yes / No
Count a clash about what the product is or does, such as a name that says waterproof or GTX and a description that says not waterproof, a colour in the name that differs from the colour column, or a name for a jacket and a description of trousers. A description that only adds detail the name leaves out is not a clash. Yes: Two parts of the row say different things about the product. No: The parts of the row agree, or only add to each other.
Does the product row contain placeholder text or internal notes that must not go live? Yes / No
Count text meant for staff or not yet written: "TBC", "TODO", "lorem ipsum", "copy from supplier sheet", "check with buyer", supplier codes in the description, or notes about margin or stock. Yes: The row contains text of this kind in the name, the description or a column shown to shoppers. No: The row contains no text of this kind.
Is there enough in the product row to tell what the product is? Yes / No
Answer No when the name and description are blank, only a supplier code, or too vague to tell what is being sold, such as "Item 2" or "New style". Yes: A careful reader could tell what the product is. No: The row does not say what the product is.
Lens columns
category, category_probability, gender, gender_probability, missing_required_info, missing_required_info_probability, name_description_conflict, name_description_conflict_probability, unpublishable_text, unpublishable_text_probability, enough_information, enough_information_probability
Run it on your own text
Add this prism in the app, change any question, and test it on a file of your own.