CAP beneficiaries 2025

Click a criterion button (Name, Town, postcode…) to add as many filters as you like. Filters of different types combine with AND; several entries of the same type combine with OR. Total amount and subsidy type can only be added once (their button is then greyed out). Tick “Invert” on an entry to exclude it ('everything except'). The × cross removes a filter.

Name

What you type is searched anywhere in the name, case-insensitively: michel also finds GAEC MICHELET. The * wildcard stands for anything: mi*el finds EARL MICHEL. For the exact name, wrap it in straight double quotes: "EARL MICHEL", the wildcard still works there, but on the whole name ("mi*el" does not find EARL MICHEL).

Town

Full name. Punctuation does not matter: dashes, spaces and apostrophes are ignored, so saint-malo and SAINT MALO return the same thing; which helps, as the official data mixes both spellings for a single town. As with the name, the search matches anywhere and the * wildcard works: SAINT finds every town containing SAINT, saint*mer finds SAINT MALO SUR MER. Straight double quotes force the exact town: "RENNES".

Postcode

Add one entry per code: a postal region (35), a full code (35000), a range (35-44) or the * wildcard anywhere in the code (35* = starts with 35, *3010 = ends with 3010, 4*130 = starts with 4 and ends with 130).

Total amount

Enter a minimum, a maximum, or both: only farms whose total subsidies for the year falls within the range are kept.

Subsidy type

Tick one or more subsidy types in the dropdown menu. The amount shown is then what was received under the chosen types.

• Export: the “Export data” button downloads a CSV file (Excel/LibreOffice). A big result set means a big file.
• Farm details: click a farm's name or its amount to open its detail page (subsidies year by year, by type). The postcode and town links instead start a new search on that value.

Be careful when interpreting the data: this tool is designed to make a very large public database easier to browse, not to correct it. Given the level of detail imported, some information may have been poorly transcribed at the source: a single farm listed in multiple ways, a town merged with or assigned to the wrong postcode, an ambiguous subsidy label covering different programs. Before drawing any conclusions, be sure to verify the type of the payments and cross-check them with official data.