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Data Analytics – Why Do You Need it as a Real Estate Investor?

Real Estate Investor

Author: Bizzman; Published on: April 6, 2020

Earlier, real estate investors used to make big decisions by speculations and gut feelings due to which they have suffered massive losses at times. Nowadays, most of them are using data analytics to make informed decisions about investments that minimize your risk. A data-driven real estate market analysis helps to build wealth and give yourself a competitive edge over others. So, what is exactly real estate data analytics? It is the process of examining raw data with the aim to make profitable decisions on the basis of collected information. This blog discusses how it is required for any investor.

What are the Major Reasons to Use Real Estate Data Analytics?

Here are the key reasons:

Determine Location

As a real estate investor, you can use data to get an insight into the latest trends and determine locations on the basis of variables such as nearby school ratings, traffic conditions, proximity of amenities, and life quality. You can also assess how profitable a location is according to occupancy rates, average rental income, and ROI in that particular place. When you identify the right locations fast, you can stay ahead of your competitors in finding rental properties. It saves you from the time and hassles to conduct extensive searches implementing the traditional research techniques.

Price Optimization

No matter if you are about to sell or buy properties, price optimization is essential. You need to understand the market in which you are operating to make the most favourable pricing decisions. Data analytics is not only about buying and selling prices. This can also be applied to other aspects of real estate such as pricing of taxes and pricing, statistics, rental data, pricing services and setting prices.

Accurate and Fast Appraisals

Before buying or selling properties, it is necessary to get an appraisal. Data analytics provide you with an ample of precise information regarding sales for different properties in the same locality. With the investment property analysis, the evaluator can offer proper price estimations to you quickly.

Consumer Trends

Commercial real estate investment is larger and more complicated than residential property investment. Thus, commercial property investment demands a thorough real estate data analytics on consumer trends. You get to understand what consumers are looking for, competitors in the industry, the intensity of demand for a new shopping mall, parents’ preferences for new schools and deficiency in restaurants. Real estate data analytics provides you with precise answers to these questions and thus, helps you to make a favourable decision.

Competition Analysis

As a real estate investor, you can review the performance of your competitors in the business. You can find out who is earning the maximum profits, which companies are the most reliable, customer ratings they have and the marketing strategies they use. You can also use data analytics to know about sales figures, profits and consumer reviews that help you to assess their performance.

Targeting Tenants

With predictive real estate data analytics, you can predict your future tenants for a few years. You can learn if there is a consistent demand for rental units in your nearby areas and if a particular property will have tenants in the coming 2 to 3 years. By implementing data analytics, you can get an idea about changes in the composition of tenants in the coming 5 years. Landlords can decide on which groups such as college students, young families and independent professionals to target. The data analysis makes it simpler to target tenants appropriately.

The real estate market is unpredictable, complicated and constantly changing. Thus, you need thorough data analytics to make smart decisions and increase your return on investment. As an investor, you can quickly decide where and how much to invest and the precise value of properties. You also get to know about important metrics including price forecasts, market cycle risks and desirability analytics. Thus, it can be said you need data analytics to make it big as a real investor.

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