The Problem
Email addresses contain useful information, but it is buried inside one long text string. If you want to group contacts by company, school, agency, or mail provider, the part you really need is the domain after the @ sign.
Reading those domains by eye works on a tiny list, but it gets clumsy fast. Different usernames have different lengths, so the formula cannot just cut from a fixed position. It needs to find the separator first, then pull the useful part after it.
The flow below shows the cleanup path. A full email becomes much more useful when the domain is isolated into its own column and can be counted or filtered on its own.
The Problem: Domains Are Hidden Inside Email Text Finding the @ sign gives the formula a reliable split point.
In this workbook, the subscriber emails are in one column and the domain output belongs beside each row. After the domains are extracted, the summary should show the total email count and how many unique domains appear in the list.
full email -> find @ -> domain text -> unique-domain summary
That keeps the cleanup useful beyond display. Once the domain is separated, the list can support reporting questions like which companies appear, which providers dominate, or whether the list has too many one-off domains.
How We Solve It
The key step is finding the @ sign. Once we know its position, we can return everything to the right of it or remove everything before it. Both approaches work, and the challenge accepts formulas built around that logic.
Method 1: MID with FIND
Method 1: Start after the @ sign and return the remaining text.
This is the formula used in the solution. FIND locates the @, then MID starts one character later and returns the rest of the email. It is dependable because the username can be any length and the formula still finds the right starting point.
This solves the challenge directly because the worksheet needs everything after the @ sign in its own column. Once the starting position is known, MID can pull the domain cleanly no matter how long the username is.
=MID(A2,FIND("@",A2)+1,LEN(A2))
Method 2: RIGHT with a length calculation
Method 2: Use RIGHT after calculating how many characters come after the @ sign.
This version works from the other side. First it calculates how many characters are to the right of the @, then RIGHT returns exactly that many. It is a nice option when you like formulas that describe the domain as the ending segment of the text.
This solves the same problem with a different angle. Instead of choosing where to begin, it measures how much text belongs to the domain and then returns that ending piece from the right side of the email.
=RIGHT(A2, LEN(A2) - FIND("@", A2))
Method 3: Delete the front part with REPLACE
Method 3: Remove everything up to and including the @ sign.
Another way to think about the task is not to extract the domain but to delete the username. REPLACE can do that by replacing everything from the first character through the @ with an empty string.
This solves the challenge by removing the part we do not want instead of building the part we do. That can feel more natural when the username is just noise and the real goal is to leave only the domain behind.
=REPLACE(A2, 1, FIND("@", A2), "")
Function Explanation
1. FIND
FIND returns the position of a character or text fragment inside another string. Here it tells the rest of the formula where the domain begins.
That matters because usernames can be short, long, or include dots. The @ sign is the stable marker that lets every row use the same logic.
Learn more this functionFIND
2. MID
MID returns text starting from a position you choose. Combined with FIND, it becomes a flexible way to isolate the domain from each email.
In the workbook, it starts one character after the @ sign so the output keeps only the provider or company part.
Learn more this functionMID
3. REPLACE
REPLACE swaps part of a string based on position. In this case it removes the part we do not need, leaving the domain behind.
It is useful because some text cleanup problems are easier to think about as deleting noise rather than extracting the desired piece.
After extraction, the next useful step is usually a summary such as a unique count or a grouped report by domain. That is why this challenge ends with a unique-domain total, using the cleaned domain column rather than the original email text.
Extract the domain from each email in column A, then finish the summary so the sheet shows the total number of emails and how many unique domains appear in the list.