Company parsing
Gather contact details of local (non-network) companies that deal with:
- ski rentals, mountain equipment (hiking, climbing), bicycles, watercraft (kayak, SUP, rafting in general, etc.), go-karting, ATVs. - 50%
- insurance brokers - 20%
- notary offices - 20%
- lawyers (not large companies) - 10%
Format for collecting contacts: company name, email, phone number, address, website, and Instagram (if available on the company's website).
- Switzerland search for companies on the site local.ch 1000 pcs - German language
- Austria on the site herold.at 1000 pcs - German language
- USA on the site yelp.com 2000 pcs - English language
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1 day22 USD
1 day22 USD
Hello, I can parse, feel free to contact me.
My stack: JS, TS, ReactJS, NextJS, SCSS...
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5 days112 USD
3840 78 0 5 days112 USD
Good day!
I have extensive experience in parsing. I can complete your project.
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1 day67 USD
2830 19 0 1 day67 USD
Hello. I am ready to perform contact parsing from the specified websites taking into account all the listed points. I suggest discussing the details in private, and I will guide you on the terms.
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2 days56 USD
484 0 1 2 days56 USD
Hello, Yaroslav! I am an experienced Fullstack developer, ready to ensure quality and fast execution of the project "Company Parsing". I will solve the problem of collecting contact information using effective parsing algorithms for the websites local.ch, herold.at, and yelp.com. By obtaining company names, emails, phone numbers, and other data, I guarantee accuracy and adherence to deadlines. Let's create a successful project together!
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3 days90 USD
2213 49 2 1 3 days90 USD
Hello!
I am ready to complete your project.
I have experience in collecting contacts, specifically phone numbers and emails of companies and individuals.
The cost of one contact is 1 UAH.
Examples of my work are in the portfolio:
Freelancehunt
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4 days45 USD
3219 84 0 4 days45 USD
Ready to take it on.
But we need to clarify the order details, write!
I will implement it with a Python script.
Price - the terms are approximate for one site. But we need to consider the complexity of the sites.
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Odessa