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How to Scrape Das Telefonbuch Leads to CSV

Scrape Das Telefonbuch leads to CSV. Extract company names, addresses, phones, websites, industries and hours with UScraper's local desktop app. No code.

UScraper
June 22, 2026
8 min read
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How to Scrape Das Telefonbuch Leads to CSV

This tutorial shows how to scrape Das Telefonbuch leads into CSV with the Das Telefonbuch Lead Scraper template for UScraper. You will prepare URLs, import the workflow, validate rows, and fix common export issues.

Before you start

Prerequisites, scope, and policy checks

You need UScraper installed as a local desktop app, the Das Telefonbuch lead scraper template, and reviewed detail URLs your team is allowed to process. Start with five to ten records; the first run should prove the CSV shape.

Use the official site manually first. Das Telefonbuch has general directory search, phone directory search, and company search. This template is narrower: it works from known detail pages, so every row has a traceable source URL.

Review the live page, current robots.txt, and privacy policy before automation. Directory listings can include personal data, protected database content, and contact details.

If your objective is sales outreach, document the source URL, purpose, lawful basis, suppression rules, opt-out handling, and retention period before importing rows into a CRM.


Input prep

Build a clean Das Telefonbuch URL list

The workflow expects detail URLs, not search keywords. Run your search in a browser, open matching records, and copy only the pages you plan to review. A clean input list has one region, one category, and a clear owner.

Avoid mixing unrelated searches in the first batch. Combining company detail pages, city searches, and reverse phone lookup pages makes validation harder because each page type can expose different fields.


Workflow anatomy

What the Das Telefonbuch scraper does

The JSON export is the authoritative workflow definition. In plain English, the template does this:

Navigate -> Wait for Page Load -> Inject JavaScript -> Sleep
-> Wait for Element -> Structured Export -> Loop Continue

Navigate contains the URL list. Wait blocks let the page render. JavaScript tries to dismiss consent prompts and reveal phone numbers. Structured Export writes one row, and Loop Continue advances to the next URL.

The workflow is URL-controlled. It does not crawl every result page or bypass account walls, which keeps the run easier to audit.

{
  "project": {
    "name": "Das Telefonbuch Lead Scraper",
    "description": "Scrapes lead data from Das Telefonbuch detail URLs under adresse.dastelefonbuch.de."
  },
  "blocks": [
    {"title": "Navigate", "config": {"urls": ["https://adresse.dastelefonbuch.de/Berlin/example-detail.html"]}},
    {
      "title": "Structured Export",
      "config": {
        "fileName": "das-telefonbuch-lead-scraper.csv",
        "fileMode": "append",
        "columns": ["firma_oder_person", "ort", "unternehmen_url", "...", "oeffnungszeit"]
      }
    }
  ]
}

Output map

CSV fields for Das Telefonbuch lead data

No CSV sample was bundled, so validate against the JSON definition and your first live export. Treat blank cells as review signals, not automatic failures.

CSV columnWhat it capturesValidation check
firma_oder_personCategory inferred from URL path or visible textConfirm it matches the listing type.
ortCity from address fields or URL pathCompare against the page address.
unternehmen_urlSource detail URLUse it as the audit trail for every row.
name_des_unternehmensCompany or person nameMatch the visible heading.
adresseStreet, postal code, and cityCheck formatting before CRM import.
telefonnummerPhone number when visible or revealedExpect blanks when no number is exposed.
offizielle_websiteExternal website link when presentExclude directory-owned links.
brancheIndustry or category textDeduplicate categories before analysis.
oeffnungszeitOpening-hour or status textTreat as volatile, because hours can change.

Runbook

How to scrape Das Telefonbuch leads to CSV

1

Import the template

Open Das Telefonbuch Lead Scraper, download the JSON, and import it into UScraper.

2

Replace the sample URLs

In Navigate, replace the Berlin examples with approved adresse.dastelefonbuch.de detail URLs.

3

Confirm interaction blocks

Keep the consent and phone-reveal JavaScript step for the first run.

4

Set the export folder

Confirm das-telefonbuch-lead-scraper.csv, headers, append mode, and a project folder.

5

Run one URL first

Export one record, compare the CSV to the browser, then widen the URL list.


Validation

Validate the export before outreach

Open the CSV beside the source page and inspect rows from the beginning, middle, and end. Dedupe by source URL, phone number, and official website. Tag rows that need manual review.

SymptomLikely causeFix
Empty company nameExpected heading did not renderRerun one URL and increase waits.
Blank phone numberNo phone is exposed or reveal changedCheck the browser and update the interaction step.
Wrong website linkRedirect or internal links appeared firstExclude directory-owned URLs.
Missing industryCategory markup moved or the URL pattern changedUpdate the JavaScript column against the live detail page.
Duplicate rowsAppend mode kept tests or duplicate URLsClear the CSV and dedupe inputs.

Alternatives

UScraper vs Python, Octoparse, Apify, and hosted tools

If you are comparing Das Telefonbuch scraper options, decide where the browser runs and who maintains the workflow.

OptionGood fitTrade-off
UScraper templateAnalysts who want local CSV outputYou still validate selectors and policy fit.
Octoparse templateHosted no-code scraping teamsCloud execution and plan limits may matter.
Apify actor or Python APIAPI-driven hosted runsBilling, maintenance, and data custody shift to the platform.
Python or Selenium scriptEngineers who need complete controlYou maintain browsers, waits, selectors, retries, and packaging.

For adjacent German directory workflows, browse the UScraper template library or the UScraper blog.


Frequently asked questions

Public pages can still be restricted by site rules, robots directives, database rights, privacy law, direct marketing rules, and reuse context. Review the source, keep runs modest, and get legal review before outreach.

FAQ

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