Nick Saraev Daily Update Wednesday, July 9
Nick Saraev Daily Update - Money-Making AI Insights
Key Money-Making Insights
Working 3-4 hours per night is sufficient to build a profitable AI automation business if you focus ruthlessly on revenue-generating activities. Avoid premature automation of sales processes, as chatbots can cost you $12,500/month in lost sales while only saving $1,200/month in labor costs. Let customer demand drive your platform learning rather than investing time in tools before there's proven need.
Top Money-Making Q&As
Question 1
What advice would you give to someone who works full-time but wants to pursue this space? Is 3 to 4 hours a night enough to make a dent and eventually snowball into a profitable business? Also, being on Eastern time, is there any strategy in focusing on leads who are in an earlier time zone like Pacific Standard, considering I'd be mainly active at night?
3-4 hours a night is enough. Treat your limited time as an advantage—forces focus on revenue-generating activities. You'll outperform people with more time if you're ruthless about what moves the needle. Don't worry about Pacific vs. Eastern time; book meetings when you can. Most tasks can be done in 1-2 hours a day. You're in a good spot.
Question 2
How would you approach lead intake for a car dealership that currently uses Facebook ads and DMs with a single rep, and is considering automation with a chatbot?
Don't use a chatbot for lead intake unless you have overwhelming volume. Chatbots save little money and hurt conversion rates. A human rep converts better and the labor cost is low. Automating this saves $1,200/month but can lose $12,500/month in sales from worse conversions. Only use chatbots at scale for support, not front-end sales. Hire more people if needed.
Question 3
What is your take on GoHighLevel (GHL)? Should someone dive into it?
Check out a 30-minute tutorial, create a test environment, maybe build a simple automation. Don't go deep until a client specifically asks for GHL. Don't waste time learning platforms before there's demand—let customers direct your learning.