AI-Powered Influencer Analytics Platform

InfluenceIQ is a data-driven platform that helps businesses find the perfect influencers for their brand. By leveraging AI and machine learning, it provides deep insights into influencer credibility, engagement, and alignment with your brand. The platform uses realistic historical data, predictive analytics, and advanced metrics to ensure smarter influencer partnerships.

1. Influencer Matching:

   • AI-powered matching based on brand alignment, credibility, and engagement.
   • No bots—only authentic influencers.

2. Data-Driven Insights:

   • Detailed metrics: followers, likes, comments, engagement rate, and more.
   • Realistic historical data simulation for 36 months.

3. Predictive Analytics:

   • Linear regression for future trends (next 9 months).
   • Metrics: followers, likes, engagement, and quality scores.

4. Advanced Scoring:

   • Influence Score: Combines followers, engagement, and credibility.
   • Credibility Score: Ensures no bot followers.
   • Engagement Quality Score: Measures audience interaction.
   • Longevity Score: Tracks influencer consistency over time.

5. AI-Powered Text Analysis:

   • TF-IDF (Term Frequency-Inverse Document Frequency) for influencer content analysis.
   • Identifies keyword importance and content relevance to brand campaigns.

6. Custom Reports:

   • Concise, AI-generated reports using LLM models (e.g., Gemini API).

• Frontend: React, Tailwind CSS
• Backend: Node.js, Express
• Database: MongoDB
• Data Integration:
  • CSV datasets from Kaggle converted into APIs.
  • Custom API to replace Instagram Graph API.
• Machine Learning:
  • Linear Regression for trend prediction.
  • TF-IDF for text analysis.

1. Data Generation:

   • Historical data is simulated using generateHistoricalData.
   • Includes growth trends, seasonality, and randomness for 36 months.

2. Future Predictions:

   • Linear regression predicts metrics for the next 9 months.
   • Outputs slope, intercept, and r-squared for trend analysis.

3. Influencer Scoring:

   • Mathematically calculated scores (Influence, Credibility, Engagement Quality, Longevity).
   • Formulas:
     • Credibility Score: 0.4 × Influence Score + 0.3 × Engagement Rate × 100 + 0.3 × Reputation Score
     • Engagement Quality Score: (Average Likes / Followers) × 100
     • InfluenceIQ Score: Credibility Score + Longevity Score + Engagement Quality Score

4. AI-Powered Reports:

   • LLM models generate concise, data-driven reports for influencers.

5. TF-IDF Content Analysis:

   • Term Frequency (TF): Measures how often a word appears in an influencer’s content.
   • Inverse Document Frequency (IDF): Assigns importance to words that appear less frequently in the dataset, highlighting unique keywords.
   • Helps brands determine an influencer’s content alignment with their campaigns.

1. Explore Influencers:

   • View ranked influencers with detailed metrics.
   • Filter by followers, engagement rate, and credibility.

2. Generate Reports:

   • Use AI to generate concise reports for selected influencers.

3. Predict Trends:

   • Analyze future trends for followers, likes, and engagement.

4. Analyze Content with TF-IDF:

   • Extract key topics from an influencer’s posts.
   • Identify influencers whose content aligns with brand goals.