Image for reference.

Here’s how they approached it:1.Scraping Listings: They used web scraping tools like Beautiful Soup and GPT APIs to scan Airbnb for properties in their target areas.2.Image Analysis: They trained an AI model to analyse listing photos, identifying homes with solid potential (good structure, layout, location) that were undervalued due to low-quality photos.

•Our company has proprietary AI models designed to accurately assess listing quality through images, which would power this feature.2.Smart Weighting:•Automatically weigh comps based on their reliability.

People coming into town to visit family, reunions, weddings or professionals on contracts.All that to say, don't count yourself out.

It's the second Wed of every month, a small group of people and variety of investor experience levels.

Sometimes life happens faster than you think (weddings, job changes, market shifts), so it helps to know your break even point in case you need to move on sooner rather than later.

Need about $125,000 in CAPEX between the units to bring them up to current Subway image. 

I guess sports tournaments or other festivals/events/weddings.   

Use tools like:Airbnb Analytics: Monitor impressions, clicks, and overall CTR.IntelliHost: Analyze your listing for category placement and CTR improvements.RankBreeze: Track your listing's performance and ranking changes.You can also A/B test your photos by rotating lead images or running Meta Ads (Facebook/Instagram) or Google Ads to measure which photo drives the most engagement.The Airbnb algorithm is continuously evolving and every host should pay attention as new features are rolled out. 

Aiming to maximize cashflow to fund future investments, but as newly weds rent by the room doesn't feel practical right now.