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    Revenue Optimization case study: after 6 months with ai pricing: with SelectCursor
    Revenue Optimization

    After 6 months with AI pricing:

    +23% Revenue increase-35% Vacancy rate reduction500+ Properties optimized

    The Challenge

    Ultimate Rentals manages 500+ vacation rental properties across Europe. Their manual pricing approach โ€” adjusting rates based on season and gut feel โ€” was leaving significant revenue on the table. They needed a data-driven solution that could optimize pricing in real-time based on demand, competition, and market conditions.

    Key pain points:

    Static pricing โ€” Rates updated weekly at best, missing demand spikes

    Missed revenue โ€” Underpriced during high-demand periods

    High vacancy โ€” Overpriced during shoulder seasons

    Our Approach

    We built an AI-powered revenue management system that automatically optimizes pricing based on hundreds of data signals.

    We built a comprehensive data pipeline:

    We developed a multi-factor pricing model:

    Historical booking data (3 years, 500+ properties)

    Competitor rate scraping (10,000+ comparable listings)

    The Outcome

    After 6 months with AI pricing:

    +23% revenue increase year-over-year

    -35% vacancy rate (from 22% to 14%)

    +18% ADR (Average Daily Rate) during peak periods

    Pricing updated 24x/day vs. weekly manual updates

    โ€œ"The AI pricing system paid for itself in the first month. We're capturing revenue we never knew we were missing. The team's ability to combine data science with practical business constraints was impressive."โ€
    CEO, Ultimate Rentals,

    Technologies Used

    React
    Booking.com
    LSTM
    VRBO
    AI
    Airbnb

    Timeline

    • We built a comprehensive data pipeline:Phase 1: Data Infrastructure (4 weeks)
    • We developed a multi-factor pricing model:Phase 2: ML Model Development (6 weeks)
    • Integration: Connected to Booking.com, Airbnb, VRBO APIsPhase 3: Implementation (4 weeks)

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