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Decision Analytics for House Location Selection

Decision Analytics for House Location Selection

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Decision Analytics for House Location Selection

Everyone has various priorities when it comes to purchasing a property. People will be concerned about safety, accessibility, and the availability of all amenities, to name a few concerns. Real estate is a pretty good option to invest your hard earned money. Evaluate your real estate property.

However, this investment, like any other, comes with its own set of risks. Due to the length and complexity of the purchasing process, it's easy to become sidetracked and lose out on the greatest deals. To guarantee that we achieve the greatest results, we must conduct some study and analysis before making any decisions.

Solutions for Selecting Best House Location

The goal of real estate decision analytics is to extract useful data from a dataset of existing property listings. After that, modern data science techniques are used to evaluate and assess the data, providing a collection of useful insights. This analytics offers valuable real estate statistics that may be used to make property recommendations based on customer preferences.

Predictive Analytical Process

An AI-based recommendation system predicts the best-suited property based on the customer's wants and desires.

Location

From these Sample analytical dashboards, People can observe how rates vary according to the location. They can examine how the property's zone, such as whether it is a low or high residential, or commercial property, affects the prices. The dashboard also shows how surrounding locations, such as whether they are near a feeder street or a railway line, affect the rates.

User Story

The dashboard in Fig 1 illustrates the price variance if a buyer wants to live near an arterial road so that he or she may easily use transport for employment.

  • Properties in Washington will cost the most, while properties in Oklahoma would cost the least because Washington is a hub for the tech industry.
  • The highest prices are found in the residential medium zone, while the lowest are found in the residential high zone because most people do not want to live in an area where houses are overcrowded or too far apart. As a result, the medium residential zone is the most desirable, which is why it is in high demand and so has high pricing.
  • Flat-land-contour properties get the highest values, whereas hillside and banked-quick homes command lower prices than flat-land-contour properties.

Infrastructure

From these Sample analytical dashboards, People can look at how a property's configuration influences its price, such as if it's at a dead end road or surrounded on three sides by other houses.

They can also use this dashboard to learn how the area and age of the property affect the costs. It also reveals how the type of home, such as a single-family detached home, a duplex, or a townhouse, affects values.

User Story

If a buyer desires to purchase a single family detached kind of dwelling for his or her family, the dashboard in fig 2 indicates the price variance with Property infrastructure.
  • Houses with configuration of dead end roads have the highest values, while those at corners have the lowest. because in urban planning, dead ends are placed to road layouts to minimise through-traffic in residential areas. As a result, people are more interested in that type of property.
  • A general trend we've noticed is that as the size of the area grows, so do the prices of properties.
  • There is a declining slope in property age and pricing. As the age of a property grows, its value decreases. Because vital components of the house, such as plumbing, electrical, the roof, and appliances, are newer and thus less prone to fail, a buyer can save money.

Safety

From this Sample analytical dashboard, People can observe how the volume of robberies, homicides, and violent crimes in a city varies in relation to the population.

User Story

As we can see from Fig 3 Chicago has the highest crime rate so it is the least secure place to live.

End Customer Value

Users can compare several locations and choose the one that best matches their needs. They can also compare crime, climate and connectivity in various areas. As we all know, a residential property's market price is directly determined by its location in a city. Each location symbolises accessibility, neighbourhood, traffic, socioeconomic level, and proximity to green places, to name a few.

Why XenonStack?

Xenonstack makes recommendations on how to secure the best deal possible, taking all risks into account, and offering the property at the best possible price. Also verify whether the area has all of the amenities and conveniences that the client desires.

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