Converting LinkedIn Locations to Metro Areas for Event Invitations | Clay

Converting LinkedIn Locations to Metro Areas for Event Invitations

I am successfully finding LinkedIn profiles and extracting the contact's location, but I would like to convert the location into a "metro area" (for example) normalizing Brooklyn and Manhattan to "NYC Metro" and Dallas, Irving and Frisco to "Dallas Metro". i tried Normalize Location, but it seems to just clean up place names and does not help me invite people to local events.

6 comments

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To convert extracted locations into metro areas, you can use our "Normalize Location with Mapbox" action. This integration leverages Mapbox's Geocoding API to standardize location data. Here's how you can approach this: 1. Use the "Normalize Location with Mapbox" action in your workflow. 2. Input the extracted location into the "Location" field. 3. The action will return various standardized geographical information, including "Place Name" and "Region". You can then use these standardized outputs to create your metro area classifications. For example, you could map "Brooklyn" or "Manhattan" to "NYC Metro", and "Dallas", "Irving", or "Frisco" to "Dallas Metro". Keep in mind that you may need to create your own logic to group specific cities or regions into your desired metro areas, as the Mapbox integration doesn't directly provide "metro area" classifications.
Sources: Normalize Location with Mapbox | Clay.com Normalize Location with Mapbox
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Tom P.
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That is not accomplishing my goal. For example, Irving is just normalized to Irving, Tx
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Owen C.
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Hey there, thanks for reaching out. This will likely require some sort of AI column that will take the location and broaden it into a metro area. Are you handing locations all around the world are just in the U.S? To get a quick headstart, try typing in something like: "take this location (insert location column using "/") and generalize it to a larger metro area that's relevant to the location" Into an AI column, then press "Help Me" which is a meta prompter and will optimize this prompt into somethign more effective. Then try saving and running on 10 rows to see what results are generated. Let me know how this goes, this will need some refinement but is a good starting place. :)
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Tom P.
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I’ve run out of credits. I am going to need to do this manually