Airbnb Pricing Strategy Analysis

Organization & Duration

Envision Virtue | 7 Days

Techniques & Tools

• Regression Analysis, Price Binning, Feature Engineering
• Python, Pandas, Power BI

Key Outcomes

• Optimized price recommendations by location, room type, and review volume.
• Identified pricing anomalies and customer sentiment drivers.
• Developed neighborhood‑based performance reports.

Insights

• Entire Home/Apt listings in certain neighborhoods had price‑to‑availability ratios exceeding optimal thresholds.
• Pricing anomalies were strongly linked to review volume and host rating → ideal for dynamic pricing.
• Recommended geo‑targeted pricing strategies and seasonal adjustments to maximize revenue.

Business Impact

This analysis provides a data‑driven foundation for Airbnb pricing optimization. By combining regression modelling with feature engineering, the project reveals actionable insights for dynamic pricing, neighborhood targeting, and seasonal revenue planning.

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