Are Taylor homes moving fast, or is the market taking a breather? If you live, work, or invest in Lackawanna County, you know small boroughs can shift quickly from month to month. You want a clear, local snapshot you can trust, without the noise. In this guide, you’ll learn exactly which Taylor metrics matter, how to pull and read them, and what each signal means for your next move. Let’s dive in.
What drives Taylor’s market
Taylor is a small borough within the Scranton–Wilkes‑Barre metro. Monthly sales and listings can be low, which means a single closing can swing percentages a lot. That is normal for small markets. The best way to manage this noise is to track a 3‑month rolling average alongside the single‑month number.
Local factors often outweigh national headlines. Proximity to jobs in Scranton, commute times, school district boundaries, and nearby amenities can shape demand and pricing. To confirm what you see in Taylor, compare it to trends for Lackawanna County or the broader Scranton MSA. If Taylor moves differently than the region, dig into why.
The snapshot you need each month
Use this set of metrics for a clean, repeatable Taylor market read. For each, record the single‑month value and a 3‑month rolling average.
Prices
- Median sale price: The middle sale price for homes that closed this month. It reduces the effect of outliers and renovation one‑offs.
- Median list price: Median price of active listings at month end or of new listings added during the month. Use one definition consistently.
- Price change: Report percent change month over month and year over year using the standard formula. Pair percentages with raw counts.
Inventory
- Closed sales, new listings, active listings: Pull counts for each. These frame supply and demand in real terms for a small market.
- Months of inventory (MOI): Active listings at month end divided by the average monthly closed sales over the past 3 months. Less than 4 months often signals a seller’s market, 4 to 6 months is balanced, more than 6 months leans buyer friendly.
Speed and competition
- Median days on market (DOM): Time from list date to contract. Under 30 days suggests a hot market, 30 to 60 is moderate, over 60 is slower.
- Sale‑to‑list price ratio: Median sale price divided by median list price, times 100. Above 100 percent points to bidding pressure, around 98 to 100 percent is typical, below 95 percent suggests buyer leverage and possible concessions.
- Pending ratio: Pending sales divided by new listings. A high ratio indicates quick absorption.
How to pull reliable Taylor data
Follow this simple workflow each month. It keeps your snapshot consistent and comparable over time.
- Pull closed sales for Taylor borough for the target month and the prior 2 months from the local MLS. If MLS access is not available, use Lackawanna County Recorder data with care for timing lags.
- Capture for each property: list price, sale price, list date, contract date, DOM, property type, square footage, and sale type if available.
- Compute medians and counts, then build 3‑month rolling averages and year‑over‑year comparisons.
- Record active listings at month end and new listings added during the month.
- Calculate months of inventory using the 3‑month average of closed sales. Note that one extra listing can shift MOI in a small market.
- Cross‑check MLS exports with county public records to catch anomalies.
- Pull a county or MSA comparison set to see if Taylor is leading, lagging, or matching the region.
- Flag outliers, such as a unique luxury property or a distressed sale that could distort the median.
How to read the numbers
Small samples are noisy, so combine the single‑month reading with the 3‑month average before drawing conclusions. Pair every percentage with raw counts to keep perspective. Then apply these signals to your situation.
If you’re selling
- Tight market signals: MOI under 4, DOM under 30 days, and a sale‑to‑list ratio above 100 percent suggest strong demand. Price close to market, prepare for quick showings, and be ready to respond fast to clean offers.
- Softening signals: MOI rising, DOM lengthening, and a falling sale‑to‑list ratio point to slower conditions. Focus on accurate pricing, complete pre‑listing repairs, and consider credits or rate buy‑downs to widen your buyer pool.
If you’re buying
- Competitive stretch: When inventory is thin and DOM is short, bring a pre‑approval, strong earnest money, and straightforward terms. Use escalation clauses carefully with a ceiling you can live with.
- More leverage: When MOI rises and the sale‑to‑list ratio slips, you can ask for credits, tighten inspection timelines to your comfort, and protect against appraisal gaps.
If you invest
- Watch absorption and scale: Low monthly sales volume means longer hold times if you plan to resell quickly. Balance this against your cash flow plan.
- Validate rent demand: Check employment hubs in the Scranton area, vacancy indicators, and county data to frame realistic rent assumptions. If cash or investor purchase share is available, track it month to month to gauge competition.
A simple Taylor snapshot template
Use this quick structure for your monthly post or decision brief.
- Month, Year
- Median sale price — percent change MoM and YoY
- Median list price
- Closed sales, new listings, active listings
- Months of inventory (MOI)
- Median days on market
- Median sale‑to‑list price ratio
- One‑paragraph summary: What changed, what it likely means, and one sentence of advice for buyers and for sellers
Data cautions for a small borough
- Small sample sizes: A handful of sales can shift medians and percentages sharply. Always show counts next to rates.
- Timing lags: MLS data is most current. County records and some public datasets can lag, so reconcile when possible.
- Definitions: Be consistent with list price definitions and what “days on market” includes.
- Outliers: Unique properties can distort the median. Consider noting the median with and without obvious outliers if you see a big swing.
- Geography: Confirm the data reflects Taylor borough boundaries, not a broader ZIP or census group.
- Seasonality: Compare to the same month last year, and supplement with a 12‑month trend.
Quick monthly checklist
- Pull MLS data for Taylor and compute medians, counts, and a 3‑month rolling average.
- Calculate MOI using active listings divided by the 3‑month average of closed sales.
- Check DOM, sale‑to‑list ratio, and the pending ratio to gauge speed.
- Compare Taylor results to Lackawanna County or the Scranton MSA for context.
- Note any one‑off events that may explain unusual moves.
- Summarize what the signals mean for buyers and sellers in two or three sentences.
Local guidance when you need it
You do not need a wall of charts to make a good decision. In Taylor, clarity comes from the right few numbers tracked the same way every month. If you want a current Taylor snapshot and a clear plan, reach out for an MLS‑backed briefing tailored to your block and property type.
Ready to see where you stand in today’s Taylor market? Schedule a Call with Unknown Company and get your custom pricing, inventory, and timing read.
FAQs
What is a good months of inventory number for Taylor?
- Under 4 months often signals a seller’s market, 4 to 6 months is balanced, and over 6 months leans buyer friendly.
How should I use days on market in decisions?
- DOM under 30 days suggests fast movement and strong demand, 30 to 60 is moderate, and over 60 points to a slower pace and more negotiation room.
Why do Taylor price percentages swing so much month to month?
- Taylor’s small sales counts mean a single closing can move the median sharply, so pair the single month with a 3‑month average.
Should I compare Taylor to county data before listing?
- Yes, comparing Taylor to Lackawanna County or the Scranton MSA helps confirm if a move is local or part of a wider trend.
What does the sale‑to‑list price ratio tell me?
- Above 100 percent suggests bidding pressure, around 98 to 100 percent is typical, and below 95 percent points to buyer leverage or needed concessions.
How do I track investor activity in Taylor?
- If available, monitor the share of cash or investor purchases month to month and pair that with rent and vacancy context for the Scranton area.
