Nick showed me a great video about how you can generate a fictional but realistic detailed transcript of a first sales call

https://www.youtube.com/watch?v=B3zz8-DORvI

In this video, Jordan demonstrates obtaining:

• A fictional, in-depth sales call transcript (8:28) between a company and a case study company, complete with specific details about the prospect's situation.
• A detailed analysis identifying public data signals (9:57) that could have indicated the company's need for the product. This included suggestions for niche data sources, combining different data types, and specific examples like LinkedIn posts, public court filings, and tech stack breadcrumbs (14:09).
• Evidence of AI's ability to help investigate documentation history (14:43) and potentially identify churn signals.
• The framework for generating a highly specific Go-To-Market (GTM) engineer job description (17:16) that outlines the entire research process, data sources, and playbook for operationalizing GTM plays using tools like Clay.com.

Essentially, the AI helped him simulate the research process for understanding customer buying conditions and then outline how to operationalize that understanding into a scalable GTM system.

Jordan used next prompts:

• Initial Setup and Case Study Identification (6:43): "Can you pick a random B2B vertical SAS company with a lot of case studies? Just like go find one on the web."
• Deepest Case Study Selection (7:27): "Pick one of these companies that has the most case studies and then go find all of their case studies and go give me the... the case study that has the most indepth detail."
• Fictional Sales Call Transcript Generation (8:19): "Generate a fictional, amazingly in-depth transcript as if this was a sales call, a first sales call between this company and the… the case study company and Cleo. And just, you can make up a bunch of details, but make sure they’re very specific details that they could happen, that the prospect is sharing the situation that they are in that led them to seek Cleo. And make sure the rep is super well-versed and great qualification. And so create that transcript for me, this fictional transcript, with as much detail."
• Identifying Public Buying Signals (9:50): "Given all of this kind of information in the transcript and the case study, what I want you to do is I want you to go identify what are what's what are public ways that I might have been able to determine that this company was in the situation where they needed Cleo... spend an ungodly amount of time researching different data... look in niche data sources. Think about how you might combine data... Don't be generic. Don't look just at like job postings or company descriptions... imagine you are the world's most qualified sales development rep that has a lust for OSINT techniques... find with sorts sites that have timestamps on them where you think the most compelling evidence or the most compelling multiple types of evidence exist with links and sources so that I can review this. This single document should have everything I need to be able to evaluate the different possible buying data buying signals."
• GTM Engineer Job Description Creation (17:03): "Now, what I want you to do is think like a GTM engineer... go look at clay.com and nadn and I want you to... and remember that clay.com has an agent tool that you can use. But what I want you to do is create a GTM engineer job description that is going to identify this whole research process. Assume you got everything perfectly right. identify which data sources we should use for which pieces of the information, how we should run this specifically, how all the pieces should play together and then how I should launch these sort of go to market plays. This GTM engineering job description should be ridiculously specific and it should have the exact playbook that someone will need to use clay.com to be able to turn this into a humming system that is so specific that no stone no question will left be left unanswered."

Nick and I have a subscription to Cannobal Substack. If you want any articles, email [email protected] and I'll send them to you.