Do LinkedIn URLs Normalize Person's Names Automatically?

Miguel M. · 2025-08-06 15:57:38.463112+00

does the "enrich person" from linkedin URL already normalize the persons name now? OR do i need still run an additional name normalization column?

Do LinkedIn URLs Normalize Person's Names Automatically? | Clay

9 comments

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Clay
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The "Enrich Person" actions from LinkedIn URL return "Contact - Full Name" as one of their data outputs. However, the sources don't specify whether this full name output is already normalized or in what format it's provided. You'll likely still need a separate name normalization column to ensure consistent formatting for your specific use case.
Sources: Enrich Person with "Companies, People, and Jobs" | Clay.com Enrich Person from LinkedIn URL with Snov.io | Clay.com Enrich Person with Datagma | Clay.com Enrich Person with LeadIQ | Clay.com
Luca P.
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Miguel - Do you mind sending the link (url) to the table so we can take a look?
(52 kB)
Miguel M.
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https://app.clay.com/workspaces/217721/workbooks/wb_0t07p79SWVkDi56f4uz/tables/t_0t07pifJC7MSaFP4fE3/views/gv_0t07pifDx55jwXzZtJH
Miguel M.
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i just wnat to know if the "enrich person" column already normalizes the person's name from their linkedin profile or if I need to run an additional enrichment for that?
Luca P.
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Hey Miguel! Great question! 😊 Yes, the "Enrich Person" action from LinkedIn URLs already includes automatic name normalization! You don't need to run an additional name normalization column. When you use the Enrich Person feature with a LinkedIn URL, it automatically outputs several normalized name fields: ** normalized_first_name: First name only, cleaned up ** normalized_last_name: Last name only, cleaned up ** normalized_name: Full name in "First Last" format The normalization process automatically handles a bunch of things for you: ** Removes titles and suffixes (Dr., Prof., PhD, MBA, etc.) ** Removes honorifics (Mr., Ms., Mrs., etc.) ** Translates non-English names to English phonetic equivalents ** Applies proper capitalization ** Handles special cases like hyphenated names So you can skip the extra normalization step and just use the normalized name fields that come directly from the LinkedIn enrichment! This saves you both time and credits. Hope that helps streamline your workflow! Let me know if you have any other questions about the enrichment features.
Miguel M.
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can you help me understand why each entry is being duplicated on this table/
Luca P.
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Hi Miguel, I just took a look at your table, everything looks pretty good. What exactly do you mean by duplicated?
Miguel M.
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Sorry wrong thread
Luca P.
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No worries, how can I help then?

Loading comments

Clay
APP
·
·
The "Enrich Person" actions from LinkedIn URL return "Contact - Full Name" as one of their data outputs. However, the sources don't specify whether this full name output is already normalized or in what format it's provided. You'll likely still need a separate name normalization column to ensure consistent formatting for your specific use case.
Sources: Enrich Person with "Companies, People, and Jobs" | Clay.com Enrich Person from LinkedIn URL with Snov.io | Clay.com Enrich Person with Datagma | Clay.com Enrich Person with LeadIQ | Clay.com
Luca P.
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Miguel - Do you mind sending the link (url) to the table so we can take a look?
(52 kB)
Miguel M.
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·
https://app.clay.com/workspaces/217721/workbooks/wb_0t07p79SWVkDi56f4uz/tables/t_0t07pifJC7MSaFP4fE3/views/gv_0t07pifDx55jwXzZtJH
Miguel M.
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i just wnat to know if the "enrich person" column already normalizes the person's name from their linkedin profile or if I need to run an additional enrichment for that?
Luca P.
·
·
Hey Miguel! Great question! 😊 Yes, the "Enrich Person" action from LinkedIn URLs already includes automatic name normalization! You don't need to run an additional name normalization column. When you use the Enrich Person feature with a LinkedIn URL, it automatically outputs several normalized name fields: ** normalized_first_name: First name only, cleaned up ** normalized_last_name: Last name only, cleaned up ** normalized_name: Full name in "First Last" format The normalization process automatically handles a bunch of things for you: ** Removes titles and suffixes (Dr., Prof., PhD, MBA, etc.) ** Removes honorifics (Mr., Ms., Mrs., etc.) ** Translates non-English names to English phonetic equivalents ** Applies proper capitalization ** Handles special cases like hyphenated names So you can skip the extra normalization step and just use the normalized name fields that come directly from the LinkedIn enrichment! This saves you both time and credits. Hope that helps streamline your workflow! Let me know if you have any other questions about the enrichment features.
Miguel M.
·
·
can you help me understand why each entry is being duplicated on this table/
Luca P.
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Hi Miguel, I just took a look at your table, everything looks pretty good. What exactly do you mean by duplicated?
Miguel M.
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Sorry wrong thread
Luca P.
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No worries, how can I help then?