Hey folks! I’m struggling with a Zapier webhook setup. I’m getting data from a vendor, but it’s coming in as a weird array-like format. I need to break it down to use in my CRM.
Here’s what I’m dealing with:
active: True id: 138371 memo: AcmeCo modifiedOn: 2017-03-17T19:01:30.0774473 type: Email value: [email protected] active: True id: 138370 memo: None modifiedOn 2017-03-17T19:01:30.0764491 type: MobilePhone value: 5551234567
I want to grab the email, memo, and phone number. Any ideas on how to split this up? I’m pretty new to Zapier, so I’m not sure where to start. Thanks for any help!
hey benmoore, ive seen this before. zapier can be tricky with weird data like that. have you tried using the ‘formatter’ step? it’s pretty good for breaking down text. you could use it to split on ‘active:’ first, then grab the bits you need with regex. something like value:\s*(\S+@\S+) for email might work. just play around with it and youll figure it out!
Having worked with Zapier’s webhook responses before, I can suggest a different approach that might simplify things. Instead of relying solely on Zapier’s built-in tools, consider using a Code step with Python. This gives you more flexibility in parsing complex data structures.
In the Code step, you could split the string on ‘active: True’ to separate each entry, then use regular expressions to extract the needed information. Something like:
import re
entries = input_data.split('active: True')
for entry in entries:
email = re.search(r'type: Email value: (\S+)', entry)
phone = re.search(r'type: MobilePhone value: (\d+)', entry)
memo = re.search(r'memo: (\S+)', entry)
if email and phone and memo:
# Do something with the extracted data
This approach allows for more precise control over the parsing process and can handle variations in the data structure more robustly. It might take a bit more setup initially, but it’s often worth it for complex data extraction tasks.
I’ve dealt with similar challenges in Zapier, and I can share a strategy that worked for me. The key is to use Zapier’s ‘Formatter’ utility, which is incredibly powerful for parsing complex data.
First, use the ‘Text’ option in Formatter to split your input on the ‘active:’ keyword. This will separate each entry. Then, use another Formatter step to split each entry on the line breaks.
From there, you can use Zapier’s ‘Extract Pattern’ feature to pull out the specific data you need. For email, use a regex like value:\s*(\S+@\S+). For phone, try value:\s*(\d+). The memo might be trickier, but memo:\s*(.+?)\s could work.
It takes some trial and error, but once you get it set up, it’s pretty robust. Don’t hesitate to use multiple Formatter steps to clean and shape your data. Good luck with your setup!