trendFinder
T
Trendfinder
Overview :
trendFinder is a tool that leverages artificial intelligence to collect and analyze social media posts from key influencers. When new trends or product releases are detected, users are notified via Slack. It transforms the way marketing teams operate by saving time on manual social media searches, keeping them informed of real-time conversations, and enabling quick responses to new opportunities or industry changes. Key advantages include AI-driven trend analysis, social media monitoring, real-time trend detection and analysis, and instant Slack notifications.
Target Users :
Target users include marketing teams, brand managers, and social media analysts who need real-time insights into social media trends to swiftly respond to market changes and create impactful marketing campaigns.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 64.0K
Use Cases
When technology influencers start discussing a new AI tool, trendFinder detects this pattern in real time, allowing the marketing team to receive notifications via Slack and quickly create content or engage early with the trend.
Brands monitor competitors' social media activities through trendFinder, timely discovering competitors' new market strategies and responding accordingly.
Marketing teams use trendFinder to analyze trending topics during industry conferences, adjusting their marketing strategies based on these insights.
Features
AI-driven trend analysis: Utilize Together AI to process collected content and identify new trends and patterns.
Social media monitoring: Integrate with Twitter/X to track posts from selected influencers.
Firecrawl integration: Enhance the crawling of web data and context.
Real-time trend detection and analysis: Quickly identify product releases and important conversations.
Instant Slack notifications: Send instant alerts when significant trends are detected.
Scheduled monitoring: Use cron jobs to schedule monitoring tasks.
Express.js backend: Ensure reliable performance.
How to Use
1. Clone the repository to your local environment.
2. Install dependencies.
3. Configure environment variables.
4. Run the application.
5. Optional: Build and run the container using Docker.
6. Optional: Use Docker Compose to start and stop the application.
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