Quote from @Greg Scott:
Quote from @Schuyler G.:
Hi All,
Just incase you don't make it past this sentence, my first question is.. DOES THIS EXIST?
Summary: I’m currently working on a project to analyze rental market trends and help real estate investors, landlords, and property managers identify high-performing areas. My goal is to build a data-driven tool that provides actionable insights into which neighborhoods and property types are in the highest demand, based on metrics like:
- Time on market: How quickly rentals are being leased.
- Property characteristics: Bedrooms, bathrooms, size, and amenities.
- Pricing trends: Rental rates relative to market demand and property features.
- Visual quality: Leveraging property photos to analyze the style and condition of rentals that perform well.
The tool will allow users to:
- Pinpoint areas with the fastest rental turnovers.
- Understand what types of properties (size, price range, features) rent the quickest.
- Gain deeper insights into property presentation and amenities that correlate with high demand.
Thank you in advance for your feedback. I’m excited about the potential of this project and hope it can bring value to the real estate investment community.
Looking forward to hearing from you!
Not to be a downer, but I'm not clear how I would utilize this metric to manage my properties. Knowing how fast or slow things are turning would not cause me to change how I manage my business.
I'm more concerned about current market rents All else equal, I know that by lowering my rents $50 or $100, I can lease up my units almost instantly. In other words, I can control how quickly I lease up based on how I price my units vs the competition. What I don't control is the market price.
The specific business situation where this may be useful is on absorption of a new apartment complex units, but then they have a metric for that, absorption.
Thanks for sharing your thoughts Greg. I completely understand your point about pricing adjustments driving faster leases, but my experience has shown that other factors play a significant role in a rental's performance over time.
For example, I own three rentals with very different dynamics:
1. One of my rentals always rents quickly, consistently performing well in terms of tenant demand.
2. Another rental is in a great area but has struggled recently due to increased competition from newly built apartment complexes. The rent dropped from $2,750 last year to $2,450 this year, and it took two months to lease. There were a couple of variables at play like time of year and agent showing the property..
3. The third property is more niche—a premium rental with a large RV garage. This one requires a very specific tenant who values that feature.
This variation got me thinking: How can I identify more properties like my first one? Rentals that are market-rate but lease quickly often reflect strong and steady demand. By analyzing metrics like average days on market over several years, I believe it’s possible to pinpoint investment opportunities in areas where specific property types (e.g., 2bd/2ba single-family homes) consistently perform well.
Building on this, you can also analyze current rental rates relative to nearby "for sale" comps to estimate ROI. The idea is to find a pocket or neighborhood that offers the right combination of estimated ROI and rental demand, giving a balance of cash flow and tenant demand.
In my view, this approach provides a more reliable signal of demand than relying solely on pricing adjustments or short-term market trends. It’s about uncovering high-demand niches that hold up even during fluctuations in the broader market.
What I’m describing aligns partly with absorption, but I’m looking for a tool that allows me to drill down into the components of that absorption rate—filtering by factors such as the number of bedrooms, bathrooms, home type, amenities, and more.
Do you see merit in this approach? Are there additional factors you think are worth considering? What tools are you using to evaluate markets?
Thanks for your reply and merry Christmas!