Finder.fi Business Directory Scraper: 3 Practical Use Cases

Q: What do the currency fields represent?

All monetary variables, such as turnoverKEur, are stated in thousands of euros. A value of 500 represents €500,000.

Q: How does the search logic function?

The scraper combines the category or customQuery with the selected city to mimic a standard browser search query.

Direct answer

The Finder.fi Business Directory Scraper targets Finder.fi (Fonecta), Finland's primary business registry. By query or direct URL lookup, it extracts comprehensive contact details, categories, active registry codes, and multi-year financials. To derive real value, identify a concrete business decision before running the scraper, and then configure a focused run to deliver an actionable artifact.

Practical use cases

These use cases come from Finder.fi Business Directory Scraper's published documentation. Each is expanded into an operating pattern so the Finder.fi Business Directory Scraper output has a purpose beyond collection.

Use case 1: Sales & lead generation

Outcome: build prospect lists by category and municipality, complete with phone/email and revenue band.

Question to answer: Which candidates satisfy the qualification rule, and what evidence makes each one worth a closer look?

Configure: Start with category (A common Finnish business category. Combined with city (if set) and customQuery to build the Finder.fi search. Leave as-is or clear it and use customQuery for anything not in this list.), customQuery (Free-text search term (Finnish). Overrides/extends category - e.g. "kampaamo", "IT-konsultointi", or a full company name. Combined with city if set.), city (Restrict results to a Finnish municipality. Leave empty to search all of Finland.). Use the narrowest Finder.fi Business Directory Scraper values that represent the real task, keep the first result set small, and record why each selected input matters to the Finder.fi Business Directory Scraper outcome.

Working method: Fix the disqualifying criteria first so obvious mismatches are removed cheaply, then apply the positive criteria only to what remains, recording the evidence field behind every qualified decision.

Deliverable: Create a shortlist split by qualification status, each entry citing the exact field and value that earned its placement. Include the Finder.fi Business Directory Scraper source identifier and the collected fields behind every Finder.fi Business Directory Scraper decision.

Stop condition: Pause when the qualification bar is being applied inconsistently between batches, or key identifying fields are missing more often than not. Fix the Finder.fi Business Directory Scraper question, comparison rule, or configuration before expanding the Finder.fi Business Directory Scraper run.

Use case 2: Market research

Outcome: pull turnover and employee-count trends for a whole industry segment in a city.

Question to answer: What changed since the previous collection, and which changes deserve action now?

Working method: Store every run under its collection date, key records by a durable identifier rather than position or display text, and only escalate a difference once it has been confirmed against two consecutive runs.

Deliverable: Create a monitoring log that pairs every flagged change with the two runs it was confirmed across. Include the Finder.fi Business Directory Scraper source identifier and the collected fields behind every Finder.fi Business Directory Scraper decision.

Stop condition: Pause when a change is flagged from a single run with no second confirmation, or the matching key itself proves unstable. Fix the Finder.fi Business Directory Scraper question, comparison rule, or configuration before expanding the Finder.fi Business Directory Scraper run.

Use case 3: Credit / risk screening

Outcome: pull multi-year financials (turnover, operating margin, solvency) before onboarding a Finnish supplier.

Question to answer: Which returned records satisfy the stated decision rule, and what should happen to each accepted record?

Working method: Write the acceptance rule down before the first record is reviewed, apply it consistently across the batch, and change only one rule or input between batches so any shift in the result has a clear cause.

Deliverable: Create a review-ready queue split by status, with the deciding field cited next to every record. Include the Finder.fi Business Directory Scraper source identifier and the collected fields behind every Finder.fi Business Directory Scraper decision.

Stop condition: Pause when the acceptance rule had to be reinterpreted mid-batch, or reviewers disagree on how to apply it to the same record. Fix the Finder.fi Business Directory Scraper question, comparison rule, or configuration before expanding the Finder.fi Business Directory Scraper run.

Turn documented output into a deliverable

The scraper extracts critical operational data points, including official Finnish Patent and Registration Office (PRH) and Statistics Finland details:

Contact and Identity: name, companyOfficialName, businessId (Finnish Y-tunnus), phone, email, and website.
Industry Standard Classifications: Official Finnish TOL (Toimialaluokitus) codes mapped via industryCode and industryName.
Official Registry Dates: Detailed onboarding markers including tradeRegisterDate, vatRegisterDate, and employerRegisterDate.
Multi-Year Financial History: Extensive historical metrics under financials[] (all currency values reported in thousands of euros), detailing turnoverKEur, operatingMarginPercent, solvencyPercent, and numberOfEmployees.

Build one useful workflow end to end

Define the criteria: Document your required parameters, identifying acceptable municipalities, target TOL industry codes, and essential financial thresholds.
Run a test configuration: Execute a small test run on the Apify platform using a low maxItems value to check the output structure.
Isolate and clean the dataset: Standardize currency conversions by multiplying the default values by 1,000 to convert thousands of euros into raw euros, and drop records missing critical contact fields.

Design around documented limitations

Financial reporting limits: Sole traders (Toiminimi) and small voluntary associations are not legally mandated to publish comprehensive balance sheets. Keep your expectations aligned with local corporate disclosure laws.
Registry details: The ownerName attribute is populated primarily for sole proprietorships; registered corporations rely on a board of directors, which is excluded from these directory files.
Anti-bot measures: The source directory employs AWS WAF Bot Control. The actor routes traffic via headless browser requests with polite spacing delays, which caps execution speeds compared to raw HTTP requests.

Frequently asked questions

What do the currency fields represent?

All monetary variables, such as turnoverKEur, are stated in thousands of euros. A value of 500 represents €500,000.

Why are some financial arrays missing?

This occurs because sole traders and minor associations are not required to publish comprehensive accounts in the public registry.

What is the purpose of the industryCode field?

It houses the official Finnish TOL classification code, allowing you to match companies against government economic databases.

How does the search logic function?

The scraper combines the category or customQuery with the selected city to mimic a standard browser search query.

Can I bypass WAF restrictions?

The tool manages anti-bot challenges natively using headless browsers and polite timing intervals to ensure successful scraping.

Resources

Finder.fi Business Directory Scraper on Apify