Additionally, what methods have you found effective for identifying trends and collecting reliable demand data — whether through surveys, market observation, or direct customer feedback?

If you buy it, make sure your rental numbers work with a 'no-garage' vacancy buffer

Don't get me started on emailing confidential data, Natalie.

I’m also a licensed contractor, so a lot of my focus sits at the intersection of acquisition, renovation, and operations.Lately that’s meant spending a lot of time on STR demand, pricing, and execution …not just what looks good on paper, but what actually holds up after hundreds of stays.We share a monthly STR market snapshot with real demand data, pricing pressure, and upcoming risk/opportunity windows.

Data-driven and ready to chat!

@JerryllYes I completely understand have been a professional data scientist since 2018 before i swapped it out for real estate development 2 years ago.

The Worcester Reality CheckLet's look at a specific market example, like Worcester, where data highlights the potential for misaligned expectations:Metric → Worcester DataRenter Median Income → $42,000City Median Income → $67,000Area Median Income (AMI) for Metro → $122,000Renter-Occupied Housing → 58%Median Credit Score → 629Using the standard 30% rule for rent affordability, these incomes translate to:- A $67k income allows for a maximum of $1,675 per month in rent.- The higher $122k AMI household income allows for up to $3,050 per month.The Mismatch: High Expectations vs.

RECOMMENDATION - Clear GO/NO-GO with specific reasoning - If GO: Key value drivers and execution priorities - If NO-GO: What would need to change for deal to work - Due diligence action items TARGET CRITERIA: - Markets: TN, KY, FL preferred (pro-landlord states) - B and C+ class neighborhoods preferred (A class = lower returns, D class = higher risk) - Value-add opportunities through renovation and rent growth - Conservative underwriting with realistic expense assumptions - Cash flow target: Varies by deal size - provide actual monthly cash flow projection (Note: Portfolio approach may combine multiple smaller deals to reach aggregate targets) CASH FLOW PRESENTATION: - Always show: Monthly cash flow at stabilization - Always show: Annual cash-on-cash return % - Let the numbers speak - no arbitrary minimums per deal - Flag if deal is cash flow negative or marginal (<$2,000/month) OUTPUT STYLE: - Lead with executive summary: property class, neighborhood grade, and recommendation - Present demographic data in clear tables - Show all financial assumptions and calculations - Be direct about weaknesses - crime, poverty, or demographic concerns that affect risk - Flag if neighborhood quality doesn't align with investment criteria - Provide specific action items for due diligence RESEARCH APPROACH: - Use web search to gather current crime statistics, census data, and economic indicators - Cross-reference multiple sources for demographic accuracy - Compare area metrics to county/state/national averages for context - Identify trends (improving vs. declining neighborhoods)Is anybody else using something similar to do a quick vetting of deals? 

Are you planning to keep some extra buffer for those gaps between draws?

It's a real estate investment simulator that runs on historical data — real mortgage rates, real home prices, real inflation from FRED.