Kevin Green

Methodology for Analyzing Gong Call Briefs in Clay

hey folks! Does anyone have a good methodology for aggregating call briefs/ analysis from Gong in clay to create actionable insights on calls?

3Comments

Commented on Will the Enterprise GTM webinar be recorded? Peter...·Posted in01 Community General

Kevin Green

chiming in here because I got pulled into an internal and am super bummed I have to miss this 😿 excited to watch the recording!

Commented on Seeking Feedback on AI Prompting for LinkedIn Cate...·Posted in03 Tutorials & Inspiration

Kevin Green

Tanvi (Clay) this is great—thank you for your help!

Commented on Seeking Feedback on AI Prompting for LinkedIn Cate...·Posted in03 Tutorials & Inspiration

Kevin Green

Your mission is to determine whether the following people fall into one of the following six categories 1. sales and business development. 2. engineering managers 3. marketing 4. customer success. 5. product management 6. data analytics. To do this you will go the person's linkedin profile in column linkedin you will look at their most recent job history and make a determination if they fall into one of those categories. You can use additional information to support your hypothesis. It is very important that these are accurate, so if you are not at least 90% sure, you should feel comfortable returning "None of The Above." If you truly feel a person fits into more than one of these categories, you can return more than one answer.

Posted in 03 Tutorials & Inspiration·

Kevin Green

Seeking Feedback on AI Prompting for LinkedIn Categorization Project

Any AI prompting/ claygent wizards in here? I'm working on a project to go to a person's linkedin page, and group them into one of six** categories based on their current employment

1.
sales / business dev
2.
marketing
3.
engineering managers
4.
product management
5.
customer success
6.
data analysis

**The propmpt should feel comfortable selecting N/A if there are no matches, and returning multiple if it feels it could fit in >1 bucket. I took a stab at it with a subset of my table but wasn't happy with the number of false positives. My prompt in 🧵 would love any feedback 🙂 thx!

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Commented on Optimizing Prospect Table Analysis with LinkedIn C...·Posted in03 Tutorials & Inspiration

Kevin Green

I appreciate the context—good food for thought. Thank you!!

Posted in 03 Tutorials & Inspiration·

Kevin Green

Optimizing Prospect Table Analysis with LinkedIn Connections

Trying to think through a credit efficient way to go through a prospect table, look at linkedin profiles, and confirm if they are linkedin connections of folks at our company—specifically Dir+ Thinking this could be done w a claygent, but wondering if anyone here has done something similar

3Comments

Posted in 01 Community General·

Kevin Green

Understanding Agency MRR vs. Clay Accounts MRR in the Expert Program

Hey all, quick question about the clay experts program, could someone help me understand the difference between Agency MRR and Clay Accounts MRR? ty!

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