LLM-Powered Creator Profiling & Matchmaking Pipeline for Influencer Campaigns

Brands and operations teams faced significant challenges in creator profiling and collaboration suitability. Manual discovery and evaluation were highly time-consuming and subjective, frequently leading to mismatched creator-brand collaborations. These suboptimal matches resulted in poor campaign reach, low audience engagement, and wasted ad spend. The team needed an automated, data-driven way to deep-profile creators based on their actual content and evaluate campaign fitment at scale before shortlisting.

Built an end-to-end automated profiling and evaluation pipeline powered by LLMs and vector search: •⁠ Reel Analysis & Classification: Processed recent Reels for each creator, classifying and multi-parameter profiling them across content philosophy, visual tone, niche, and audience pointers. •⁠ Comprehensive Creator Profiling: Aggregated individual Reel metadata and historical performance metrics into a unified creator profile highlighting core target audience, key themes, and content philosophy. •⁠ Discovery via Full-Text & Semantic Search: Ingested enriched profiles into Google Cloud Storage (GCS) to power full-text and semantic discovery for brand teams searching for specific creator personas. •⁠ Automated Campaign Fitment Evaluation: Built an evaluation module that automatically scores applied creators against campaign briefs and specs to quantify alignment, engagement potential, and relevance before selection.

•⁠ Time Efficiency: Significantly reduced manual discovery and evaluation effort for brands and the operations team, saving hours per campaign cycle. •⁠ Higher Campaign ROI: Eliminated guesswork in creator selection, substantially decreasing mismatched collaborations. •⁠ Improved Engagement & Reach: Creators shortlisted through the automated fitment evaluation achieved measurably higher reach and engagement rates across collaboration Reels.