Libardo Lambrano is a strategic leader at the intersection of hospitality data and investment management. Currently at Hyatt and formerly with Hilton, he leverages deep expertise in data analytics and insights to identify trends and drive performance in the global hotel sector. This data-driven approach carries over into his investment ventures: he specializes in the niche condo-hotel market through Condo Hotel Partners and serves as a Fund Manager at Dub Advisors, where he manages a strategic stock market portfolio.

Hospitality Insights: Data analytics leader at Hyatt (ex-Hilton), specializing in sector-wide performance trends.
Real Estate Strategy: Expert in condo-hotel investments and founder of Condo Hotel Partners.
Fund Management: Data-driven Fund Manager at Dub Advisors, overseeing the All Weather portfolio (ticker $PRMSHLD.
I help hospitality and travel brands turn market data into decisions about where to invest, how to market and how to grow. 15+ years at Hyatt, Hilton and Univision building the analytics programs marketing teams rely on.

I've spent my career where marketing, data and hotel performance meet. I built Hyatt's field marketing analytics program from the ground up, led the insights behind Hilton's Americas co-op media investment, and assisted Dr. Arthur Huang in developing UCF Rosen College's AI & Business Analytics program for hospitality leaders.
I'm as comfortable building dashboards with AI tools as I am presenting to hotel owners or leadership, in English or Spanish.
Reporting programs, KPI frameworks and decision tools in Adobe Analytics, Tableau and ThoughtSpot.
Rebuilt global reporting with ChatGPT, Codex and Claude, producing reports about 90% faster.
Market demand, benchmarking and campaign ROI for owners, operators, revenue and brand teams.
years in hospitality, travel and digital marketing
hotels in 20 countries supported by the analytics program I built
average ROI across 24 hotels in 11 LatAm & Caribbean countries
Hilton co-op media budget guided by my market insights
Working examples on synthetic or public government data. Each one opens live in your browser.

One hotel against its compset, market, brand and tier, with MPI, ARI and RGI indexes and minimum-peer rules.
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Occupancy on the books vs. last year across 50 markets and every future stay month, to catch softening demand early.
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How each hotel is growing on an online travel agency versus its competitive set, with a scorecard and hotel detail.
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Animated charts on the forces shaping the hotel industry, like Treasury yields vs. lodging construction since 1970.
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U.S. international air departures by destination, 2011–2026, built from National Travel and Tourism Office data.
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Photo quality scores for 1,452 hotels across 25 monthly reports, showing where each property loses points.
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Tracks photo licences nearing expiry by brand and property, fed by a Python data-cleaning pipeline.
Open dashboard ↗Every dashboard is one self-contained page, with the data pipeline and design notes in its GitHub repository.
Vendor research organized into AI-searchable libraries, plus executive summaries for functional and operational teams. Happy to walk through how it was built and used.
Assisted Dr. Arthur Huang with the data and program structure for UCF Rosen College's executive certificate: 3 courses and 15 modules.
Why some hotels look healthy on occupancy while the economics underneath are failing, and what the data shows.
Read on LinkedIn →What shorter booking windows mean for demand forecasting, pacing and how hotels plan their marketing.
Read on LinkedIn →I'm exploring Senior Manager and Director roles in marketing analytics, commercial strategy and performance marketing across hospitality and travel. I'd be glad to walk you through my work.