You can use tools from Python: or web scraping or whatever:

For the companies listed below:

Samsung, Hungary $($manufacturer of electronic devices$)$

P&G$,$ Turkey $($Ariel brand$)$

Nestl$,$ Slovenia $($NESCAF$$ brand$)$

eKupi, Croatia $($online store$)$

Please collect the following information from the above companies:

each company's website

postal address of each company $($administrative buildings $-$ places where the company's management sits$)$

names and surnames of persons in the board of directors$/$chief directors of the company

names and surnames of the marketing director, communications director, brand manager, marketing manager $-$ for P&G and Nestl$$ companies, focus on the department responsible for the brand listed in parentheses

e$-$mail addresses of persons from the points $3$ and $4$ above

telephone numbers of persons from points $3$ and $4$

Display the collected data in an Excel table as you think is best $-$ in such a way that the collected data is as transparent as possible.

The above information can be found on company websites, LinkedIn profiles of wanted persons, commercial court databases of the countries where these companies are located, etc.

In order to find e$-$mail addresses and phone numbers, you can also use IT tools for searching for data.

Try to find as much information as possible for each company listed. The more data $($e$.$g$.$ the more e$-$mail addresses and people within the company$)-$ the better.

If you cannot find any information for a company, or you are not sure that this information is correct, then leave that field in the Excel table empty.