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Measuring Product Quality Using Images: The CLIP Q-Score and an Application to Real Estate

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  • Fabian Slonimczyk
  • Danila Karapsin

Abstract

The CLIP Q-score is a novel, safe, fully reproducible, and computationally efficient method for extracting objective product quality metrics from visual data using contrastive language-image pre-training. We introduce the technique and provide an extensive application to real estate data from an online platform ($\sim500,000$ images). Our open-source metric aligns with LLM assessments and proves to be a powerful predictor of housing market prices for both sales and rentals. We also show that a higher CLIP Q-store is associated with better liquidity (reduced time on the market), especially for properties on sale.

Suggested Citation

  • Fabian Slonimczyk & Danila Karapsin, 2026. "Measuring Product Quality Using Images: The CLIP Q-Score and an Application to Real Estate," Papers 2608.01544, arXiv.org.
    • Handle: RePEc:arx:papers:2608.01544
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