AI-Sales-Signal

Introduction

The ai_sales_signal configuration is designed to intelligently analyze articles related to sales signals and provide structured insights about them. This document explains the structure and provides instructions on how to understand the components of the configuration.

Components

1. Metadata

• name: The name of the sales signal model.
• version: The current version of the model.

2. Analysis Input

The analysis_input field contains information about the article that needs to be analyzed and instructions for the analysis:

• instructions: Detailed steps on how the analysis should be conducted.
• article: Contains details about the article like title, snippet, publisher, datePublished, articleLink, textContent, and length.

3. Desired Output

analysis_desired_output provides a schema of what the desired output structure should look like after the analysis.

4. Analysis Engine

The heart of the configuration. This section dictates how the article is to be classified and reasoned upon.

Classification

The classification field is broken down into multiple categories, each with its own subcategories:

• Signal Category: Broad categories into which the sales signal can fall, such as:
  • Growth
  • Financial
  • People
  • Awards & Recognition
  • Events & Marketing
  • Corporate Updates
  • Negative News

Each of these categories further have Signal Types that describe specific events or updates within the category. For instance, under Growth, you have types like Partnership or Joint Venture, New Geography, Fundraising, etc.

Each Signal Type has:

• description: A brief explanation of the signal type.
• api_tag: Tags that can be used to categorize the signal in an API system or database.

Reasoning Frameworks

The reasoning_frameworks provides the methodologies used to derive insights. Currently, it has Inductive reasoning which helps in forming general conclusions from specific observations.

How to Use

1. Pass the article details into the analysis_input field.
2. Follow the instructions in the analysis_input field to analyze the article.
3. Use the classification field of the analysis_engine to classify the information in the article.
4. Based on the classification, use the reasoning_frameworks to derive inductive insights about the article.
5. Format the output according to the schema provided in analysis_desired_output.

Conclusion

The ai_sales_signal configuration is a powerful tool for sales and marketing professionals to gain insights from articles and news. By following the provided structure and instructions, one can derive valuable information and classify sales signals effectively.