ChatGPT just qualified my email list

Key Concepts:

• Chat GPT Deep Research
• CSV lead qualification and quantification
• Domain analysis
• Demand assessment
• Targeted outreach

Using Chat GPT for Lead Qualification and Quantification

The speaker discusses using Chat GPT for deep research on a CSV file containing a list of leads (544 people) for a bulk ads creation tool he is developing. The goal is to assess the actual demand for the tool and avoid wasting time on a product with limited interest.

Process:

1. Data Input: The speaker uploads the CSV file to Chat GPT.
2. Prompt Engineering: He instructs Chat GPT to perform a "deep dive" of the domains associated with large brands or agencies within the email list. The prompt specifies the need to quantify the value of the list.
3. Domain Analysis: Chat GPT analyzes the domains, identifying the associated companies and their online presence (websites, LinkedIn profiles, etc.). It filters out generic email addresses (e.g., Gmail) that provide limited information.
4. Fit Assessment: Chat GPT determines how many businesses within the list are a good fit for the speaker's bulk ads creation tool.
5. Output: After approximately 12 minutes, Chat GPT provides a detailed analysis.

Results and Analysis:

• Unique Businesses Identified: Chat GPT identified 227 unique businesses from the list of 544 leads.
• Fit Quantification: The majority of the identified businesses were deemed a "really good fit" for the bulk ads creation tool.
• Detailed Table: Chat GPT generated a table containing information about each business, including:
  • Website
  • Industry
  • Company Size and Scope

Application and Benefits:

• Targeted Outreach: The speaker plans to use the generated table to create a "hit list" of companies to contact individually and offer the tool.
• Time Savings: The speaker emphasizes that Chat GPT performed a task that would have taken him hours to complete manually.
• Data-Driven Decision Making: The analysis provides data to support decisions about product development and marketing efforts.

Notable Quotes:

• "Chat GBT Deep Research just did something that would have taken me hours to do."

Conclusion:

Chat GPT Deep Research can be used to efficiently qualify and quantify leads from a CSV file. By analyzing domains and associated businesses, Chat GPT can provide valuable insights into the potential demand for a product and identify high-value leads for targeted outreach. This process saves time and enables data-driven decision-making.