Research - Link Scraper
Discover how Bitscale’s Link Scraper tool extracts relevant data from websites, analyzes metadata, and powers intelligent lead qualification workflows.
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:
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Scraping and analyzing website text to identify relevant details.
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Accessing and interpreting website metadata to extract additional insights, such as third-party tools or chatbot services being used.
Demonstration Use Case
To illustrate the tool’s functionality, we set up a workflow for a B2B support chatbot company focused on two goals:
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Classify prospects as B2B or B2C companies.
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Identify whether a prospect has a chatbot on their website and, if so, extract the name of the chatbot service.
Step-by-Step Breakdown
1. Scraping Website Text for Classification
Using Link Scraper, we:
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Provided the URL column for a list of five prospects.
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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).
2. Analyzing Metadata for Chatbot Identification
Next, we leveraged Link Scraper’s ability to parse website metadata to:
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Check if a chatbot service is present.
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Extract the name of the chatbot service (if available).
We achieved this by:
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Adding a specific instruction in the prompt to analyze metadata for chatbot-related information.
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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.
Running the Workflow
After setting up the prompts, we ran the tool across all rows simultaneously. The results:
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Prospects classified as B2B or B2C in the first column.
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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.
Key Features Demonstrated
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Text-Based Scraping: Extract relevant content directly from website text to classify prospects or gather other insights.
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Metadata Analysis: Analyze website metadata to identify third-party services, such as chatbot providers or trackers.
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Customizable Prompts: Use tailored prompts to direct Link Scraper’s focus for specific data needs.
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Efficient Workflow: Process multiple rows simultaneously, saving time and effort.
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.