With markets feeling more segmented lately, I’ve been rethinking how I anchor ARV during early deal analysis.Instead of relying on a single comp or peak-sale comparison, I’ve been leaning toward:• ARV ranges (low / mid / high) rather than one number• Heavier weighting on the most recent 60–90 day sales• Noting spread between list vs. sold prices in the same pocket• Treating appreciation as a bonus, not a givenI’m finding that even within the same zip code, buyer demand and pricing tolerance can shift block by block depending on condition, financing availability, and buyer profile.Curious how others are handling market data right now:Are you tightening ARV assumptions, using wider ranges, or changing how you comp altogether?

Thank you.OWNERSHIP ENTITY- Obtain copy of deed to confirm legal owner- If domestic LLC, confirm annual registration is current & who can legally sign- If foreign LLC, confirm registered in Michigan (where we & property are) & who can legally sign- If Trust, get paperwork showing who can legally sign- Confirm city assesssor & water dept have correct owner & mailing addressPROPERTY- Confirm we are added to insurance policy- Confirm property taxes are current- Lookup public records for property data- Confirm rental license active- Confirm no outstanding permits, assessments, etc.- TakeOver Evaluation Video & Property Data Sheet, share video with owner for possible repairs- Per owner selections on our PMA, have tax docs, water bills, etc. mailed to us.TENANTS- Send tenant(s) Welcome Aboard Package with TakeOver Questionnaire (confirms occupants, pets, how long there, rent rate, security deposit, who owns appliances, etc.)- Review previous rent ledger for patterns to be aware of, note their lease in PMC software- Try to convert to our Lease, to make it easier on our staff (we don't tell tenants they don't have to do this)- Opportunity to renew/extend lease with increase?

This guy is a CEO who is promoting his website.There is very little real data on mid-term rentals, so if you are considering them, please be on high alert when picking a market.

Ensure the amounts & all the data are correct.

The numbers tell the story every year when I prepare the data for my CPA.It works.

Most new wholesalers spend months learning what you already know: how to comp properties, read MLS data, understand what buyers are looking for, and talk to sellers.A few ways to connect with local wholesalers in Orange County: First, hit up your local REIA meetups.

I’m also a data scientist, so the idea of a ZIP-level screener definitely resonates.A few things that could make this more useful:• clearer sourcing/definitions for metrics (e.g. whether home price reflects list prices, sale prices, or a model)• visibility into which ZIPs are included in the upgrade• coverage beyond core cities to include inner-ring suburbs• more market context (e.g. competitiveness, school ratings, renter/owner mix)• ability to segment by property type (e.g.

I'm calling on Title companies to get a list but learned that they charge a fee for some data

If you look at the data, the issues start well before 70 units:1 listing: 4.8 avg review2-20 listings: 4.7 avg review21-100 listings: 4.6 avg review101-1000 listings: 4.5 avg review1000+ listings: 4.4 avg review(https://www.phocuswire.com/power-of-reviews-in-the-short-term-rental-sector)This was the inspiration behind Fairly: to capture the customer satisfaction of small hosts, and pair it with industry-leading yield management, automation, etc.And our results have proven this out: with over 5,000 guest reviews, our average home has a 4.95 rating (and our median home has a 5.0!) 

You can read all the details for yourself here:Why Viceroy Research is Short on Arbor Realty TrustBelow are some snippets that are included to link this report to individuals and entities that have promoted here or have had investors discuss the investment here so when people search for them they can find this data."