Benefits
This use case orchestrates a multi-stage AI agent workflow to evaluate influencers for brand campaigns, leveraging sentiment, audience alignment, and engagement performance from analytical scoring to report delivery for campaign teams.
Problem Addressed:
Brand managers often struggle with inconsistent influencer fit, poor audience alignment, and reputational risk. This chain evaluates and scores influencers programmatically, ensuring only relevant, well-aligned, and low-risk influencers are recommended.
What the Agent Does:
• AI Scoring AgentCalculates influencer fit using four scoring dimensions: ToneMatch, ValueResonance, Audience Match, and Risk.
• Fitment Ranker AgentConverts AI scores into final fitment ranks and comments on strengths/risks, generating CSV output for business review.
• Campaign Report Deliver AgentJoins fitment results with influencer profiles and generates campaign-specific reports with logic-based "Fit Status."
• Data Replacer AgentReplaces datasets (ai_analysis_results, fitment_scores, Report_Delivery) with the latest fitment results in exact formats.
Standout Features:
• 100-influencer processing limit
• Category validation to ensure relevance (e.g., Beauty, Fashion only)
• Four-dimensional AI fitment scoring
• Multi-level scoring rank + summary fit status (Recommended / Consider / Not Recommended)
• Report delivery in dataset-safe List[Text] format
