Hi Umashankar, thanks for reaching out. Could you share some context on the datapoints you're using to write your personalized messages? Did you already enrich your leads with those datapoints or are you retrieving them using Claygent?
There are two main approaches to draft personalized messages:
1. Using GPT to reason on existing datapoints in your table: With this approach, you'll input datapoints which you have already retrieved from your leads into a GPT prompt and fine-tune that prompt to output a consistent personalized message across your leads.
2. Using formulas to set up message templates which you can fill in with dynamic variables: The second options, which prevents you from going through the iterative prompt-tuning part of your workflow, is to use out AI formulas feature to write a template of the message for your leads, where you can input the dynamic variables retrieved in your enrichment process. https://www.loom.com/share/feb23b5e57b34e17ae54742e838598b9?sid=62f50120-fb2d-4a2a-8701-d1b9ad0eb31b
I hope this was helpful. If there's anything else I can assist you with, please let me know!
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