To enrich the lead list, we'll follow these steps:

1. Scrape the Company Website: Use the URL Scraper node to extract the website content for each company.

2. Summarize the Company Description: Pass the scraped website content to a large language model (e.g., GPT-4) to generate a concise summary of what the company does.

3. Categorize the Industry: Use a Categorizer node to classify each company into either the "Healthcare" or "Industrials" industry based on the company name and website content.

4. Classify the Lead Type: Analyze the job title to determine if the lead is in an IT/technical role or an operations role.

5. Classify the Lead Level: Categorize the lead's seniority level as C-suite, VP, Director, or Manager.

6. Write the Data to a Google Sheet: Use the Google Sheet Writer node to populate the "Industry", "Summary", "Lead Type", and "Lead Level" fields in the lead list.

This automated workflow allows you to enrich the lead list with valuable insights, making it easier to personalize your outreach and run analyses on the data.

To categorize the leads by industry, we use a categorizer node in the "lead enrichment sub-pipeline". This node takes in the company name and website information, and classifies the company into either the "healthcare" or "industrials" category.

The categorizer node is configured with the following settings:

• Categories:
  • Healthcare: Companies in the healthcare industry, such as hospitals, pharmaceutical companies, etc.
  • Industrials: Companies in the industrial sector, such as manufacturing, materials, etc. This category acts as a catch-all for companies not classified as healthcare.
• Categorization Logic: The node will classify the company based on the information provided in the company name and website. Companies that are not classified as healthcare will be categorized as industrials.

The output of the categorizer node is then piped into the "industry" column of the Google Sheet, providing a standardized industry classification for each lead.

This industry categorization allows for further analysis and segmentation of the lead list, enabling more targeted outreach and personalization in the sales process.

To classify the lead titles by type (IT or Operations) and level (C-Suite, VP, Director, or Manager), we'll use a two-step process:

1. Classify Title Type:

   • We'll create a text field that instructs the categorizer to classify the title as either "IT" or "Operations".
   • The categorizer will use this prompt to categorize each title in the list as either IT-related or Operations-related.
   • The categorized title type will be stored in the "Lead Type" field.

2. Classify Title Level:

   • We'll create another text field that provides examples of C-Suite, VP, Director, and Manager titles.
   • The categorizer will use this prompt to classify each title in the list into one of these four levels.
   • The categorized title level will be stored in the "Level" field.

By performing these two classification steps, we can now have a standardized way to understand the type and seniority of each lead in the list, which can be used for further analysis and personalized outreach.

In this tutorial, we have demonstrated how to build a comprehensive lead enrichment pipeline using Vector Shift. We started by creating a sub-pipeline that scrapes the website, generates a summary, and categorizes the industry of each lead. Then, we built the main pipeline that reads the lead data from a Google Sheet, applies the sub-pipeline to each lead, and writes the enriched data back to the sheet.

The key features of this workflow include:

1. Website Scraping: Using the URL Scraper node, we can extract relevant information from the company's website.
2. Summary Generation: Leveraging a large language model (LLM) like GPT-4, we can generate a concise summary of the company's activities.
3. Industry Categorization: The Categorizer node allows us to classify each lead into predefined industry categories.
4. Title Analysis: We use additional Categorizer nodes to determine the job level (e.g., C-suite, VP, director, manager) and function (IT or operations) of each lead.
5. Bulk Processing: The List Build feature enables us to apply the entire enrichment process to every lead in the list, ensuring efficient and scalable data augmentation.
6. Google Sheet Integration: The pipeline seamlessly integrates with Google Sheets, allowing for easy data input and output.

This workflow demonstrates the power of Vector Shift in automating and streamlining lead enrichment tasks, which can be invaluable for sales, marketing, and business development teams. By leveraging this pipeline, you can quickly and accurately enhance your lead data, enabling more personalized outreach and better-informed decision-making.