Locate Item Name, Price, and Condition from Subito & Wallapop Screenshots
Manually scrolling through Subito or Wallapop listings and typing each one into a spreadsheet takes about 3 minutes per ad — this locates Item Name, Price, and Condition from any screenshot in under 10 seconds.
5-10s per screenshot · Up to 99% accuracy on printed text
Three Fields You Can Locate from Any Subito or Wallapop Screenshot
Subito and Wallapop listing screenshots mix card data with platform UI — navigation bars, sponsored placements, and category badges all produce visible text. With Custom Column Extraction, the AI identifies each field by its role in the listing card, not its screen position.
The listing title in Italian or Spanish — typically the boldest text in the card.
The asking amount in Euros — Subito uses comma decimals (€ 65,00), Wallapop often uses integers or period decimals (€89).
Status labels — "Nuovo", "Come nuovo", "Usato" in Italian for Subito; "Nuevo", "Como nuevo", "Usado" in Spanish for Wallapop.
Type these as column names. The AI reads each field by card structure across both platforms and both languages.
Same EUR Currency, but the Condition Label Changes Language and the Card Layout Differs
A Subito screenshot from Milan shows "Usato — € 65,00" where a Wallapop screenshot from Madrid shows "Como nuevo — €89" — and the card layouts themselves differ: Subito uses a compact list-style card while Wallapop uses a larger photo-dominant card. The same condition concept needs to be read across Italian and Spanish labels, with different price formatting and card UI. Here is why that breaks traditional approaches and how semantic reading solves it.
Why Subito & Wallapop Screenshots Break Traditional OCR
Condition labels are bilingual and appear near the price in different positions. Subito shows "Come nuovo" as a compact tag next to the price; Wallapop places "Como nuevo" below the item name with a coloured badge. Traditional OCR reads all text in the card region and cannot distinguish the condition label from the item name or other metadata.
Card UI structure differs significantly between Subito and Wallapop. Subito uses a dense list-style card with the price on the right and condition as a small badge. Wallapop uses a larger card with a prominent photo, the title below it, and the condition shown as a coloured label. Template-based extraction tuned for one layout fails on the other.
EUR price formatting varies by platform locale. Subito shows "€ 65,00" with a comma as the decimal separator (Italian locale). Wallapop shows "€89" without decimals or "€89.00" with a period. Rule-based scrapers expecting one format misread the other, especially when the comma is confused with a thousands separator.
How Semantic Extraction Reads Conditions Across Languages and Layouts
Name the fields — the AI finds conditions by semantic context, not dictionary lookup. Type Item Name, Price, Condition. The visual model identifies the bold card title as the Item Name, reads the numeric value near the € symbol as the Price, and captures the status label near the price — whether it reads "Usato", "Usado", "Come nuovo", or "Como nuevo" — as the Condition, preserving the original language.
One column definition works across Subito list cards and Wallapop photo cards. Upload a mix of Subito Italy and Wallapop Spain screenshots into the same batch. The AI reads each layout independently — recognising the condition badge position in Subito's compact card from the coloured label zone in Wallapop's image-dominant card — and outputs clean language-preserved values in the Condition column.
Process gallery screenshots alongside fresh captures. A screenshot from last week's Subito search still works even if the listing URL is dead. Mix mobile cards, desktop search results, and detail pages from both platforms in one batch — the AI adapts to each layout independently.
From a Gallery of Southern European Marketplace Screenshots to One Consolidated Spreadsheet
Whether you are comparing prices across Italy and Spain, tracking your own listings on Subito and Wallapop, or archiving completed transactions, here is how the extraction workflow turns your screenshot collection into a structured record.
Upload Your Mixed Subito and Wallapop Screenshots
Drop in the captures from your gallery — Subito list-style cards from the Italian app, Wallapop photo-dominant cards from the Spanish app, or detail pages with full descriptions from either platform. PNG, JPG, or WebP from any device. Mix screenshots from both platforms in the same batch — no sorting by marketplace needed beforehand.
Define the Fields You Need
Type the columns for your tracking spreadsheet: Item Name, Price, Condition. The AI reads each screenshot independently — a Subito card yields "iPhone 13 — Usato — € 65,00"; a Wallapop card yields "Mesa de comedor — Como nuevo — €89". Fields that do not appear on a given screenshot remain blank.
Export a Consolidated Listing Spreadsheet
Processing takes 5-10 seconds per screenshot — about 18x faster than opening each image and typing the fields manually. The output is one XLSX or CSV file with the columns you defined. Filter by Platform to compare Subito Italian listings against Wallapop Spanish listings. Sort by Price to find the best deals across both countries. Export directly to Excel or push to Google Sheets via the add-on for ongoing tracking.
When Subito & Wallapop Screenshot Extraction Works Best — and When to Be Cautious
When It Works Best
Full-resolution native screenshots of listing cards or detail pages. Machine-rendered text from the Subito or Wallapop app reaches up to 99% accuracy for fields like Item Name and Price.
Mixed platforms and languages in one batch. Subito Italy and Wallapop Spain screenshots processed together — the AI adapts to each card layout and condition label language independently.
Gallery screenshots of listings no longer live on the site. Since the AI reads the visual output, a saved screenshot captures data even after the listing URL expires or the ad is removed.
When to Be Cautious
Screenshots forwarded through messaging apps. WhatsApp and Telegram compress images, reducing accuracy for smaller text like condition badges. Use native screenshots for best results.
Multiple listings in one screenshot. The AI reads the most visually prominent card. For clean per-item extraction, capture each listing individually.
Photos of a screen taken at an angle. Glare and distortion reduce accuracy. Capture native screenshots on your phone or computer for best results.
Frequently Asked Questions
Can I extract data from Subito Italy and Wallapop Spain screenshots in the same batch?
Yes. The AI processes each screenshot independently against your column definitions. A Subito listing showing "€ 65,00" with Italian condition labels and a Wallapop listing showing "€89" with Spanish condition labels are both read for the same fields — Item Name, Price, Condition — using the same semantic column names. Every screenshot becomes a row in the same spreadsheet, regardless of platform or language.
How does the tool handle Italian "Nuovo/Come nuovo/Usato" and Spanish "Nuevo/Como nuevo/Usado" condition labels?
The AI reads the condition label as it appears visually on the screenshot and preserves the exact text in the Condition column. No translation rules or lookup tables are needed — the semantic model identifies the label by its position and visual role in the card (near the price, styled as a status badge) and outputs the raw label text. A Subito screenshot returns "Usato" or "Come nuovo"; a Wallapop screenshot returns "Usado" or "Como nuevo". The column contains the original language, so you can filter or categorise by condition in your spreadsheet regardless of which platform produced it.
Both Subito and Wallapop use Euros — can the tool handle their different price formats?
Yes. Subito typically formats prices with the Italian locale — "€ 65,00" (comma as decimal separator, space before the symbol). Wallapop usually shows prices without decimals — "€89" — or with a period separator in some views. The AI reads the raw price text as displayed on the screenshot and returns it exactly as shown in the Price column. The column preserves the original formatting including the € symbol, so you can normalise or convert prices in your spreadsheet after export.
Can I extract fields from screenshots showing search results with multiple listings instead of a single detail page?
The AI identifies the most visually prominent listing card in the frame and reads your defined fields from that card. Search result views with multiple cards are parsed by detecting the primary card based on size and position. If the target listing is not the dominant visual element, accuracy may decrease. For clean per-item extraction, capture each listing card individually — a full-screen single listing capture yields the best results.
Will the Condition column be empty if the screenshot shows a listing without a condition badge?
Yes. Some Subito and Wallapop listings — particularly older posts or certain categories — may not display a condition label on the card. In those cases, the Condition column remains blank for that row. The AI only extracts a value when a condition label is visually present and identifiable. You can still extract Item Name and Price from the same screenshot without the condition field being populated.
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Deep dives: Batch processing marketplace screenshots into a single spreadsheet · General guide to extracting data from screenshots