Birmingham sample: does local supply support negotiating?

DirectCairn

Homeowner
Established
Before using this sample to judge negotiating room, I have to establish whether it describes Birmingham at all. The properties range from £798,700 to £1,198,000, with reported movement of 10.5% and a median marketing time near 38 days, yet they are labelled coastal homes.

That may be a simple category error, but it could also mean different locations have been combined. Even a correctly defined area can show scarce finished stock alongside projects that repeatedly fail to attract buyers. My inclination is to confirm the boundary, period and meaning of the 10.5% first, then divide completed sales by condition. After that, would reductions, withdrawals or new-listing volume give the clearest indication of seller motivation?
 
Resolve the geography before interpreting anything else. Birmingham is not coastal, so that description may indicate mixed or incorrectly labelled locations. Also establish the period and starting measure behind the +10.5%—asking-price movement and completed-sale movement answer different questions. I’d begin with recent completed sales inside one tightly defined neighbourhood.
 
Condition could be hiding more than the median suggests. Split the properties into broadly ready-to-occupy and needing work, then compare their marketing times and price-cut timing separately. A buyer may skip an overpriced project while competing for a finished property on the next street, even though both appear as local supply in a small sample.
 
I’m not convinced buyers negotiate explicitly because “supply is high.” They usually express it indirectly: a lower offer, slower follow-up, or choosing a better alternative. Financing also matters in this price range. A buyer’s position can change quickly if the preferred property needs additional spending or the lender’s valuation does not support the agreed figure.
 
Good point. The missing number is how many genuinely new listings appeared during those 38 days. Relisted homes can make supply look deeper without creating another real option. Can you distinguish first-time listings from properties that disappeared and returned with a new price or agent?
 
I would also clarify what “marketing time” ends at. Is it removal from advertising, offer agreed, or completed sale? Those are not interchangeable. Seller motivation may explain the outliers too: an owner testing £1,198,000 can wait, while another seller may cut earlier even if the properties look comparable.
 
A workable sheet would have one row per property and columns for neighbourhood, original price, latest price, first-listing date, reduction date, withdrawal date, condition and current status. Add completed sale price only where you actually have it. That should reveal whether cuts cluster after a certain period without forcing the whole sample into one average.
 
One caveat to my own suggestion: don’t treat every withdrawal as failed stock. Some may return, while others may be gone for reasons the listing history cannot establish. Keep “withdrawn” separate from “sold” and “still available.” The count is still informative, but it should not automatically be read as proof that buyers rejected the price.
 
Neighbourhood boundaries may matter more than the headline range. Two Birmingham areas can serve different buyer pools even at similar prices, and calling all of them one local market could create the apparent +10.5% movement. I’d map the properties first, remove anything outside the intended area, and then rerun the median.
 
Taken together, I wouldn’t use 38 days alone to justify a low offer. I’d look for a stronger combination: several comparable active listings, recent completed sales below current asking prices, repeated reductions, and a seller who has already been exposed to the market for a while. Without that, buyers may indeed just move on rather than negotiate.
 
The quickest next step is probably to rebuild the sample with one precise Birmingham boundary and no coastal classification, then split by condition. After that, compare new-listing volume with sales and withdrawals over the same period used for the +10.5%. If the conclusion changes materially, the original result was mainly a classification problem rather than evidence about negotiating power.
 
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