Taking the Guesswork out of Valuations
Property valuations have always been a slippery slope for agents and sellers alike.
Historically property valuations were a combination of CMA (Comparative Market Index), previous sold prices for the area (or area closest to area) and the estate agent’s best guess for what the property could fetch based on what it physically looks like both in- and outside. Typically though, most sellers would have already decided on a selling price before the agent ever stepped foot on their property and that was usually the price the property had to be listed for.
This keeps the seller happy, and typically the agent would not disagree, to both keep the seller happy, but also as they would earn a higher commission if the property ever did sell for higher than their estimate.
Unfortunately for the seller the figure they list for may sound great, but is usually not based on current market value or perception, nor does it take any other factors into consideration, such as potentially what other properties are listed in the area concurrently (and how do they compare), what are schools (or other facilities) like in the area, peak traffic, crime statistics, or even general amenities such as potentially whether it is in a security complex or not. The result is typically that houses sit on the market for much longer than they should. And the consequence thereof is that the seller is unhappy as their house is not getting the views it should, nor any offers to purchase, and then feel this reflects on the agent’s ability who in turn needs to have the difficult conversation of trying to convince them to drop their listing price.
There is a way to Create Objective Valuations through Data Driven Technology
There is a better way for agents to show the true market value of properties to owners that not only looks at the subjective considerations, but also the objective ones – the latter which usually play a far more active role in the final valuation and selling price.
Artificial intelligence driven technology can gather all the statistical information (including that of real-time and similar properties), and a weighted algorithm provides a very objective listing price based on numerous amounts of data. Image recognition AI is still in its infancy, so subjective input for physical attributes is still required by agents. The combination of the objective and the subjective (whether by means of walk-through of property or photos) provide a far more accurate depiction of what the listing price should be.
Having this information at hand to show sellers in such an objective way helps to rationalise and convince them why a particular price is recommended.
At PropertyFox we have fine-tuned this process to such an extent that our properties typically sell within 5% of asking price. A market related valuation helps to secure increased attention and viewers, and properties typically sell faster too – due to the increased demand. Where sellers still wish to list outside of the valuation, we can also with 100% near accuracy predict how long the property will sit on the market, and by using our data-driven valuations, realise early on that they either need to drop for a faster sale, or aren’t able to afford to sell in a bad market, saving them time and heartache.