Irfan U.

I help short-term rental operators and property managers capture more revenue by diagnosing where their listings actually stand not against broad market averages, but against their true competitive set. Every analysis I run is segment-controlled: same bedroom count, same property type, same neighborhood. The diagnosis comes before the pricing adjustment. PriceLabs setup, audit, and optimization across 26 listings. Comp set calibration, base price anchoring, minimum stay strategy, and event-driven pricing configured against real segment data, not default settings. Listing optimization based on title and description analysis across 250+ Airbnb listings in 5 markets. Only 5.6% had a strong SEO foundation. The most common gaps were keyword coverage (67%), title clarity (63%), and location signal (59%) features present but not communicated to the guest. Revenue diagnostics separating pricing problems from demand-capture problems. In my analysis of 2,262 London 3BR listings, 42% were undercapturing demand relative to what their price position should support. The issue was rarely price alone check-in experience, communication, and value perception were stronger occupancy drivers than ADR. Research foundation: 60,000+ Airbnb listings analyzed across 7 markets and 3 countries (Austin, Nashville, New Orleans, Montreal, Quebec City, London, Sydney). Multi-market pricing corridor analysis, demand leakage diagnostics, review-language trajectory modeling, and listing recovery analysis. Tools: PriceLabs, Hostaway, OwnerRez. Familiar with Guesty, Hospitable, Hostfully. Python, LightGBM, XGBoost, CatBoost, NLP, SQL. Background: MPhil in Mathematics, 10+ years teaching university-level Mathematics and Statistics, 5+ years applied data science. Top Rated on Upwork, 100% Job Success Score. Available UK and US business hours for STR revenue consulting, listing optimization, pricing strategy, and market research.