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Overview

Bitscale’s Link Scraper is a powerful tool that enables you to extract targeted information from websites and analyze metadata for deeper insights. This video showcases two key capabilities:

  1. Scraping and analyzing website text to identify relevant details.

  2. Accessing and interpreting website metadata to extract additional insights, such as third-party tools or chatbot services being used.

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Demonstration Use Case

To illustrate the tool’s functionality, we set up a workflow for a B2B support chatbot company focused on two goals:

  1. Classify prospects as B2B or B2C companies.

  2. Identify whether a prospect has a chatbot on their website and, if so, extract the name of the chatbot service.

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Step-by-Step Breakdown

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1. Scraping Website Text for Classification

Using Link Scraper, we:

  • Provided the URL column for a list of five prospects.

  • Wrote a prompt to classify each prospect into one of four categories based on their website content (e.g., B2B or B2C).

Result: The first column returned the classification for each prospect (e.g., “B2C” for one and “B2B” for others).

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2. Analyzing Metadata for Chatbot Identification

Next, we leveraged Link Scraper’s ability to parse website metadata to:

  • Check if a chatbot service is present.

  • Extract the name of the chatbot service (if available).

We achieved this by:

  • Adding a specific instruction in the prompt to analyze metadata for chatbot-related information.

  • Setting a fallback value to handle cases where no chatbot data was found (e.g., displaying “None” for such rows).

Result: The second column returned the chatbot name for applicable prospects (e.g., “Lime Chat”) or “None” where no chatbot was detected.

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Running the Workflow

After setting up the prompts, we ran the tool across all rows simultaneously. The results:

  • Prospects classified as B2B or B2C in the first column.

  • Chatbot details extracted in the second column, or “None” where no chatbot was detected.

For this use case, good leads for selling a B2B support chatbot were those prospects classified as B2B with no existing chatbot or where we could offer a better solution than their current provider.

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Key Features Demonstrated

  1. Text-Based Scraping: Extract relevant content directly from website text to classify prospects or gather other insights.

  2. Metadata Analysis: Analyze website metadata to identify third-party services, such as chatbot providers or trackers.

  3. Customizable Prompts: Use tailored prompts to direct Link Scraper’s focus for specific data needs.

  4. Efficient Workflow: Process multiple rows simultaneously, saving time and effort.

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Try It Out

Start enhancing your lead qualification with Link Scraper today: 👉 Grid Link to explore templates and workflows.

Pro Tip: Use fallback values in your prompts to ensure clean and complete data output, even when specific information is missing.