How to scrape franchise and business opportunities data from the Primary Authority register
- Minexa.ai
- 6 days ago
- 2 min read
The UK government's Primary Authority register at primary-authority.beis.gov.uk/par holds a publicly accessible directory of franchise and business opportunity partnerships. Getting that data into a spreadsheet without copying row by row is exactly what this guide covers.
Install the Minexa.ai Chrome extension and follow the steps below to turn the register into a clean, structured dataset in a few minutes.
What data is on the page
The Primary Authority register lists partnerships between businesses and local regulators. Each entry on the listing page includes the business name, the primary authority responsible, the sector or industry, and a link to the full partnership detail page. These fields are consistently structured across all entries, which makes the page well suited for automated extraction.
Before Minexa: what manual collection looks like
Without a tool, collecting this data means opening each entry, copying fields one at a time, and pasting into a spreadsheet. For a register with hundreds of entries across multiple pages, that process takes hours and introduces transcription errors. Minexa replaces that entirely: one training session on the page structure, and all entries are extracted automatically across every page.
Step-by-step: extracting the data
Step 1: Open the register page Navigate to primary-authority.beis.gov.uk/par in Chrome.
Step 2: Open the Minexa extension and confirm the page Click the Minexa.ai icon in your Chrome toolbar. The extension opens and shows an 'I'm on the right page' button. Click it to confirm you are on the correct starting URL.
Step 3: Review pagination detection Minexa scans the page and identifies the pagination controls automatically. You can see which navigation element was detected and confirm whether pagination is needed before continuing.
Step 4: Choose list only or list with detail pages You can scrape the listing entries alone, or follow each link to extract the full detail page for every partnership. For most use cases, the list data is sufficient.
Step 5: Select the data container Minexa highlights the full HTML block containing all the listing entries. Confirm the selection and click 'Create Scraper'. All data columns are identified automatically within seconds.
Step 6: Review extracted columns Once the scraper is created, all detected data points are listed. Use the next and previous navigation to browse every field that was found.
Step 7: Configure the job and run Set up Google Sheets integration or a schedule if you want recurring exports, then click Run. Results appear in a table as pages are processed.
Video walkthrough
Sample extracted data
Below is an example of the structured output returned after a completed run:
[
{
"business_name": "Subway",
"primary_authority": "Westminster City Council",
"sector": "Food and catering",
"partnership_link": "https://primary-authority.beis.gov.uk/par/partnership/123"
},
{
"business_name": "Domino's Pizza",
"primary_authority": "Milton Keynes Council",
"sector": "Food and catering",
"partnership_link": "https://primary-authority.beis.gov.uk/par/partnership/456"
}
]Reusing the scraper
The scraper trained on this page works across all structurally similar pages of the Primary Authority register. You do not need to retrain it for each run. If you want to pull data programmatically at scale, click 'API Request' inside the extension to get a ready-to-run Python snippet with your scraper ID already included.
Export options after each run include Excel, JSON, and direct push to Google Sheets. The Minexa.ai extension handles the full extraction from a single training session, with no selectors or code required.
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