Last Updated on November 10, 2021 by James Ewen
For real estate, there’s nothing more important than location Whether looking for a place to live or identifying the best place for commercial property – location is the most crucial factor.
Companies in the space are looking beyond simple location classifications like zip codes or areas. Instead, more robust modeling and new datasets have opened the door to understand how neighborhoods are changing and what the people who live in specific areas want from their location.
Let’s look at how data is innovating the in real estate space.
Data for real-estate investment
Evaluating and investing in new real estate opportunities requires extensive research and due diligence.
It pays to be the first to identify an up and coming area, but many companies have access to the same resources to try and understand where these hot neighborhoods are.
Emerging data sets, such as location are changing this. Movement data is giving real estate investment companies a head start, allowing them to understand the potential of a neighborhood before the competition.
Big data is allowing companies to answer the difficult question such as:
- How to identify new neighborhoods or areas that are good prospects for investment
- How to understand regional risks when investing
Location data is incredibly valuable in this area, not just because of the geographical nature of real-estate, but because the value of a property or area is determined by what happens in the surrounding area.
Real-estate value is closely linked to social and economic conditions – concepts that can be understood by using device location data. So the better your data, the better your insight into the investment potential of a specific region or area.
Utilizing location data alongside real estate demographic data and other third-party data sets allow real-estate to identify an investment opportunity early and measure and analyze the investment that you have already made.
Planning and development
For commercial real estate, the power of data is just as impactful as in the residential sector. Forget about costly to integrate footfall management systems. Location data can understand footfall across all real-estate properties, including your competitors. The most successful companies are using these real estate data analytics to adapt and plan in real-time.
Identify the most valuable spots
Location data can identify footfall in retail properties, both passing by and entering. Detailed metrics into visits and visit length can help understand the value of each location.
These insights can even lead to dynamic rent pricing or could also function as an add on product for tenants wanting to understand the benefits of their commercial property.
Increase operational efficiency
Real estate data can also help to improve operational efficiency. For commercial properties with vast amounts of footfall, such as airports, understand patterns around movement can significantly contribute to enhancing operations and optimized unused space.
These insights can be extended when developing new properties and planning from the initial placement of the project, to individual placement of retail booths inside. Predictive analytics in real estate is now commonplace and is having a huge effect on planning and development in the industry.
Advertising and marketing
Data isn’t just for planning and investment. Data has transformed the world of advertising and marketing, and this is true for the real estate industry.
Over 90% of home buyers start their search for a house online. Data is filling in the gaps between what the consumer wants and the ads that real estate delivers to these potential customers.
Datasets are making marketing and advertising more personal for these prospective customers. Ads can be targeted to those who have visited estate agents or personalized based on regular behavioral patterns. All allowing the real estate company to engage with a new audience in a personalized way.
This behavioral data can also be used to create a more engaging search process – where results are tailored to the user. This extends through to any consultation process, with the rise of chatbots, such as WhatsApp Chatbot and automation solutions requiring powerful data to be more productive.
See what you can do with data
James is the head of marketing at Tamoco