DATA COLLECTION IN EMERGING MARKETS

The rapid development of the real estate industry in several emerging markets has become a benchmark of the geographical segment’s overall growth pattern. However, it has not been without its problem areas which currently cause a negative impact on market trends and behaviors.?

Among the most notable, are the rapid rise of residential housing prices and the high vacancy ratio of commercial properties which are still suffering the effects of the Covid19 pandemic. Causing investors and project developers to scramble to find solutions to maintain profit margins in the competitive environment, which is made complex and inefficient since they have limited access to data.?

There are several problems to be solved here, depending on emerging models used to leverage predictive analytics and algorithms to discover trends and make better-informed decisions.?

A closer look at some of the data points that can help real estate investors and project developers navigate through market cons is by collecting the following data.??

• Geographic Information?
• Local Economic Conditions
• Crime Rate
• Competitor Analysis
• Pricing Comparables
• Predictive Property Potential
• Predictive Consumer Behavior
• Building Performance Strategies

Fortunately, such data is out there, be it fragmented and at times hiding behind legacy systems and sources. Often requiring taking deep dives into market segments not directly correlated with a real estate investment opportunity, but can still affect its viability.??

The Reicrowd data collection model

After sourcing and collecting the data, the key is to use an efficient data analyzing tool to transform the raw data into knowledge and information, otherwise, it will just be a “data tomb”. The process involves feeding the analytical tool with a healthy mix of standard industry metrics such as, (Number of listings for sale, Median property price, Average price per square foot, Days on market, Number of traditional rental/Airbnb rental listings for sale, Monthly rental income, Cash on cash return and Cap rate), with additional, yet extremely important data to the mix.?

Reicrowd implements a granular approach to its data collection and analytics model when evaluating an emerging market. Leveraging emerging technology with the goal of delivering the most accurate risk ratings possible for each offering on our platform.?

In my next post on data collection strategies in emerging markets, I will share some examples of Reicrowd’s granular data collection models, and how they are used to classify an emerging market.?

Cheers and Happy Holidays!

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