This workflow is manually triggered by providing a brand URL. It then uses GenFuse's scraping capabilities to extract content from that URL. The extracted content is sent to an AI model (like Google Gemini) for summarization and sentiment analysis, providing insights into brand perception. The final analyzed content can then be displayed or sent to another app.
This workflow automatically detects new customer feedback submitted via Google Forms (by monitoring a Google Sheet). It then uses AI to analyze the feedback content and extract impactful testimonial quotes. The extracted quotes are saved to a Google Sheet database, and an email notification is sent to the marketing team with the new testimonial.
This workflow monitors a Google Sheet for new customer feedback submissions. It then uses Gemini AI to analyze the feedback, extracting emotionally engaging and impactful testimonial quotes. Finally, the extracted testimonials are automatically added to a "Testimony" column in the Google Sheet, and an email notification is sent to the marketing team.
This workflow automatically generates detailed product comparison content. It can be triggered manually or when a new row is added to Google Sheets, taking two product names as input. An AI model then generates a compelling title, a feature-by-feature comparison, use-case recommendations, and an FAQ section. Finally, the generated content is saved into a Google Sheet for review or publishing.
This workflow helps marketing teams analyze competitor LinkedIn posts. It scrapes content from a given LinkedIn post URL, uses AI to extract insights like the post's intent, effectiveness, and key marketing takeaways, and then stores this structured competitive intelligence directly into a Google Sheet.
This workflow is manually triggered by providing a website URL. It scrapes the content of the given URL and then leverages AI to extract key topics and generate a comprehensive list of SEO keywords. Finally, the extracted information, including the URL, topics, and keywords, is stored or updated in an Airtable base.
This workflow triggers when new customer feedback is added as a row in Google Sheets. It then uses an AI model to classify the sentiment of the feedback as positive, neutral, or negative. Finally, the classified sentiment is updated back into the same Google Sheet.