How to Use the PROPER Function in Excel

The PROPER Function

1. Start with a messy text field

• Use a dataset that contains inconsistent name formatting
• In the video, the examples include customer names, technician names, city names, and email addresses
• This is common when data comes from CRM systems, dispatch tools, or exported reports

2. Insert a new helper column next to the field you want to clean

• Add a new column beside the original text field
• This keeps the raw data intact while you standardize the formatting in a new column
• In the video, this was done first for customer names

3. Use the PROPER function to standardize name formatting

• Apply PROPER to the selected name field
• This changes the text so the first letter of each word is capitalized and the remaining letters are lowercase
• In the video, this corrected inconsistent customer name formatting such as mixed uppercase and lowercase entries

4. Fill the function down through the rest of the column

• Once the first cell is correct, copy the function down the full list
• This applies the same text cleanup logic to every row in the dataset
• The result is a consistent naming format across the entire field

5. Paste the cleaned results back as values

• Copy the corrected output column
• Paste it back as values using Ctrl + Shift + V
• This removes the formulas and leaves you with clean, static text

6. Use the same process on technician names

• Insert another helper column for the technician field
• Apply PROPER again
• This formats first names and last names consistently, making technician names easier to read and report on

7. Compare PROPER with UPPER for fields that need all caps

• In the video, a city field was reformatted using UPPER
• This is useful when you want every character capitalized, such as city names or codes
• It shows that PROPER is best for names, while other text fields may need a different formatting function

8. Compare PROPER with LOWER for fields that should be lowercase

• In the video, email addresses were cleaned using LOWER
• This is useful because email addresses are typically best stored in lowercase for consistency
• It also helps reduce issues when matching or comparing text fields

9. Label the cleaned columns clearly

• Rename the helper columns based on the cleaned output
• In the video, examples included columns for city, technician name, and email
• Clear labels make the cleaned dataset easier to understand and use later

10. Watch for exceptions where PROPER does not work perfectly

• PROPER only capitalizes the first letter of each word
• In the video, a name like “McCormick” was used as the example
• PROPER would not preserve the internal capital letter correctly
• These special cases may require manual correction after applying the function

11. Use the cleaned data in your final worksheet

• After applying PROPER and related text functions, keep only the cleaned columns you want
• Delete extra helper columns if they are no longer needed
• This leaves you with a more standardized and analysis-ready dataset