Problem Statement

1. Contact Data Scraping

Scrape publicly available company data from their websites — focus only on what’s reliably accessible.

Field	Status	Notes
Website URL	Required	Use Google Search fallback if not provided
General Contact Email	Required	Usually in “Contact Us” or page footer
Phone Number	Required	Found in footer or contact page
Location / Address	Required	Available on contact or “About” page
Leadership Names	Optional	Only if listed under “Team” or “Leadership”

Output Required:

Company	Website	Email	Phone	Location	Found Leadership Name(s)

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2. Technology Detection via Python

For each company (list given), write a Python script to identify whether the website mentions:

Cloud Technologies (e.g., AWS, Azure, GCP) MES Technologies (e.g., Siemens Opcenter, Rockwell FactoryTalk) PLM Technologies (e.g., Teamcenter, Windchill, ENOVIA)

Output Required:

Company	Website	Cloud Tool Mentioned	Source URL	MES Tool Mentioned	Source URL	PLM Tool Mentioned	Source URL
Company A	https://www.companya.com	AWS	www.companya.com/tech	Siemens Opcenter	www.companya.com/tech	-	www.companya.com/tech
Company B	https://www.companyb.com	GCP	www.companyb.com/products	-	www.companyb.com/products	Teamcenter	www.companyb.com/products

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To use the Data Scraping Script for extracting details

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Either use Function7 or Function9

error_correction. Might not work well as some problems are occurring after navigate_to_contact_page() - function

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Test on an unknown website, other than the 10 provided.

Script successfully fetched information from ifm's website, Including Contact number and Email Address, but got stuck collecting address details. Result

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Run below mentioned scripts for better results.

    function7.py

    function9.py

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To convert an Excel file to .csv, use this

    convert.py

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