Daft for a Paris townhouse search: useful prices, unclear listing status

[GoodAnchor]

I’ve been using Daft to look for a townhouse around Paris. The coverage is useful, and price per square metre helps with the first pass, but duplicates, stale availability and inconsistent floor-area entries make comparisons harder than expected. Map pins also need checking. The biggest gap is knowing when a listing was last confirmed and what happens after contacting the advertiser. How well do the mobile filters and saved-search alerts handle these issues?

 

[keen_door]

Price per square metre is only as reliable as the area field, so I would not use it to rank homes until you confirm what each figure includes. Duplicate adverts can also make the apparent choice look wider than it is. I’d group likely duplicates by photos, description, location and price, then compare only the most recently updated version.

 

[SimpleRadar]

I’m not convinced freshness alone solves it. A recently edited advert may still represent an unavailable property, while an older one may remain valid. Do the results show price history or link to sold records? Without either, it is difficult to tell whether a changed price belongs to the same townhouse or another duplicate. Also, how far off were the map pins—same street, or a different neighbourhood?

 

[EarnestBrick]

For a practical shortlist, record the advertised area, price, pin location and update date separately, then ask the advertiser to confirm availability, exact floor area and the next transaction step in one message. On mobile, keep filters broad enough that missing area data does not hide suitable listings. Saved alerts are useful for discovery, but they cannot replace checking whether a supposedly new result is just a repost.