Mad about Metrics

Houseprice.AI Value

We have introduced 5 different metrics to suit all of our property clients. As a company we are mad about metrics and passionate about using AI data analytics.
A core part of this is to interpret and predict the fairest and most accurate value.

We realise that each sector of the property market has different needs. As an example, an agent wants sales regression for an accurate appraisal, a consumer wants our fair value to protect their investment, whilst a vendor the guided listing price to get the the maximum return on the property.

We give you the tools to help you to make the right decisions for your property interests.

Current estimated value This value is what we call the fair price, property can go higher or lower but this is our AI deduced benchmark value based on over 40 drivers.

Range Includes variables relating to changes in factors such as, aspect, environmental factors, fittings and improvements.

Sales Regression Method used by traditional AVMs. Deriving a value by fitting a line between the recent sales of comparable properties factored for PSQM/PSQF .

Weighted Average A weighted average of sale prices over the past 6 months

Guided Listing price Recommended listing price based on analytics of time on the market and supply demand measures for the area.

Confidence level Statistical measure that is based on how many observations there are for the specific area/property type and deviation from the mean.

Adjusted Value
Gain more precision by adjusting property details and watch the value adjust instantly. The more details you are able to provide, the more precise our adjusted value will be.

Vivienne Brooks is the CCO of Houseprice.AI She has a long history as a Technical Software Support Guru, is a graphic artist and also has a strong background in Marketing.
Need More Information?

Please contact us if you have questions about Houseprice.AI , our AI data analytics app, want access to our API, or would like to schedule a demo.


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Vivienne Brooks

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