Delhi townhouses: is 2.4% movement meaningful with 80 days on market?

S

StillPorch

Real estate agent
Established
I have checked the active Delhi townhouse listings and their visible marketing periods, but the meaning of the headline movement remains unclear. The properties range from ₹43,420,000 to ₹65,130,000, show 2.4% movement and have been advertised for about 80 days.

My first thought was that transaction costs were driving much of the variation in negotiations. Condition provides an obvious counterexample: two homes at similar asking prices could attract very different offers if one needs immediate work. Seller motivation and the timing of reductions may matter just as much.

Would you treat the 80 days as useful only after comparing recent completed sales and recording each price cut? It would also help if comparisons identified the Delhi neighbourhood, the exact townhouse type and whether the 2.4% refers to asking prices, achieved prices or the gap between them.
 
I wouldn’t attribute the spread mainly to fees yet. Those costs may affect a buyer’s total budget, but condition and seller motivation can produce very different negotiated prices within the same asking range. Start with recent completed sales rather than active listings.
 
What exactly does the 2.4% represent: movement in asking prices, achieved prices, or the difference between the two? Also, over what period? Without that, the 80-day figure could describe a slow market, stale overpriced stock, or simply normal negotiation time.
 
There is another missing detail: are all these townhouses inside one clearly defined Delhi neighbourhood? Crossing even an informal neighbourhood boundary can change the comparison. I’d separate the sample before drawing anything from the overall average.
 
Withdrawn stock matters too. If difficult properties disappear rather than completing, the visible 80-day number may favour the better listings. Track withdrawals and relistings alongside sales; otherwise condition can look less important than it really is.
 
Agreed on relistings. I’d also match by photos, description and location rather than listing reference alone. A property returning with a new presentation or revised price should not automatically restart the clock for this exercise.
 
I’m not convinced transaction fees explain why one seller accepts a larger discount than another. Unless those fees differ materially between the compared properties, they affect both buyers. Deferred repairs, awkward layout or urgency to sell seem more direct explanations.
 
Buyer financing could connect the two arguments. A buyer with a fixed total budget may reduce the offer after accounting for transaction fees and necessary work. That still means condition matters; fees are part of the affordability calculation rather than a separate market signal.
 
One addition: separate financed offers from offers not dependent on financing if that information is available. A long negotiation caused by funding uncertainty is different from 80 days of weak interest.
 
Price-cut timing would be more informative than the headline days. Did the eventual transaction happen soon after a reduction, or did the property sit for weeks after the cut? The first pattern suggests unrealistic initial pricing; the second points elsewhere.
 
I’d record every asking-price change by date, not just the latest price. Otherwise a townhouse listed high for most of those 80 days and reduced near the end gets treated like one that was sensibly priced from day one.
 
The label “townhouse” may also be too loose for comparison. Confirm that the listings represent genuinely similar property types, condition and usable space. A portal category can group homes that buyers do not regard as substitutes.
 
Before comparing with the rest of India, I’d solve the Delhi sample first. National comparisons can hide local differences in buyer pool and transaction process. A neighbourhood-level set of completed sales is more useful than a broad claim that the whole country matches.
 
To answer the earlier question, if 2.4% is only asking-price movement, I would give it little weight. Sellers can adjust expectations without any transaction occurring. Achieved prices, including how long each property spent at its final asking level, would be the stronger evidence.
 
A simple table should settle much of this: neighbourhood, property type, first asking price, each cut and date, final outcome, total days listed, condition, financing dependency and whether it was withdrawn. Keep fees in a separate total-cost column rather than assuming they caused the discount.
 
That table should include seller motivation where it is actually known, but not guessed from a price cut. A reduction may reflect urgency, an ambitious starting price or feedback about condition. Those explanations have very different implications for another buyer.
 
I’d divide the ₹43,420,000–₹65,130,000 range into comparable groups rather than treating it as one band. The upper and lower ends may attract different buyers, so one combined 80-day figure could conceal opposite patterns.
 
And calculate days on market both with and without withdrawn listings. Neither version is perfect, but the difference will show whether disappearing stock is distorting the result.
 
Condition needs a consistent description. “Needs work” can mean cosmetic updates in one listing and substantial work in another. Even a basic scale, supported by the listing details, would make the negotiated discounts easier to interpret.
 
One caution on completed-sale information: the available price and timing details may not always be equally complete. Mark uncertain entries rather than filling gaps with assumptions. A smaller clean comparison is preferable to a larger set mixing asking and achieved figures.
 
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