Real Estate Data Analytics Solution

• Project: Implementation of data analytics and reporting software tools for the real estate sector
• Duration: 1+ month
• Technologies: Vue.js, Laravel, AWS Cloud Services, PostgreSQL
• Target audience: Real estate firms, recruiters, and industry consultants

Real Data Strategies provides data and consulting services for the real estate industry. Their clients benefit from Multiple Listing Service data aggregation that leverages information about real estate sales activity and market share. The company offers a range of tools for a customized analysis of real estate data.

The Client’s Request

The real estate market is very dynamic. In order to keep up with its pace and address their clients’ needs, it was essential for RDS to extend its platform’s analysis capabilities. Thus, they turned to our team to revamp their web-based application and add new reporting functions.

Challenges

Real Data Strategies consolidates a vast number of MLS databases. In effect, the number counts up to 2,500, which can rightfully be considered immense. The company aggregates a variety of digital information about real estate offices and agents, average sale prices, total volumes and units closed, all based on the location of either the property sold or real estate office.

However, it’s not enough to just collect such big data. It’s essential for RDS to present it in a way that can trigger profitable outcomes for its clients. Here, data analytics software comes to help as its role in the real estate market can’t be overrated.

The company’s application allows users to capture the value of data and harness it for quick and actionable insights. When RDS turned to Velvetech, its solution offered tools to scrutinize data about agents but lacked analytics functionality to do the same with real estate companies. That’s what our team was asked to help with.

The Process

The RDS solution was built by a third party; thus, before proceeding to development, our team first had to review the code and logic behind the application. At this stage, we noticed that its efficiency could be greatly enhanced.

Experienced in data engineering, our team also pointed out that database import — the process fundamental for the solution’s performance — required too much time and could also be optimized.

According to the client’s request and our team’s findings, the project scope included two major parts that could be implemented simultaneously:

• The first one was building analytics and reports for data related to organizations
• The second task was optimizing and refactoring the code

Implementation of New Analytics Reports

As one of the core steps of the project, we handled the development of reporting functionality to present statistics about real estate organizations depending on the MLS or user-defined regions in an MLS. Now, RDS clients can see the firms and corresponding numbers of agents, offices and sales production metrics like volume, units, and sale prices.

These reports are paginated and allow for sorting, filtering and grouping of data based on various criteria. For example, it’s possible to choose not only market area and time period but also set a filter by franchises or production metrics. On top of that, there’s an option to download a full report in the .csv or .xlsx format.

Another task that RDS required Velvetech to manage was building comparative and analytical reports to visually display various agents side by side. After the implementation of this feature, the platform allows its users to view real estate agent competition and see sales performance differences of a group of agents. In addition to numbers, the data is available in comprehensive charts and graphs that help uncover the meaning behind the figures and drive actionable insights.

Finally, to make data visualization and analysis more informative and structured, we’ve implemented customized dashboards that show data depending on the user’s query. This high-level and customized view of data is a good way to summarize numbers and have a 360-degree view of the market.

Code Optimization and Refactoring

Once our team reviewed the application’s code and logic, it became evident that there was some room for improvement.

In order to boost the platform’s efficiency, our developers revamped both backend and frontend parts by implementing optimization and refactoring practices. Reducing the number of code lines from 1,000 to 50, changing the logic and algorithm helped drive the app’s performance and make the code easier and display faster.

When the client introduced their solution to our team, all data processing was implemented on the backend side. Since the RDS platform handles complex filtering and large datasets, it was decided to move the logic from the application layer and let the database tier process all queries.

This was an essential change that decreased database import time to 5 minutes compared to 1 hour as it was before. Additionally, it reduced database calls and streamlined the backend server load.

Outcome

The implementation of new analysis and reporting features has reinforced the solution and allowed Real Data Strategies to offer its clients more tools to scrutinize real estate sales data.

With data-driven dashboards and charts that help visualize key values, real estate firms and sales professionals can transform statistics into strategy.

Comparative analysis of agents and relating reports provide new opportunities for the platform’s users and help significantly improve their decision-making process.

On top of that, the application got a revamped codebase and logic. As a result, the speed of database import is now 12 times faster than it was before, which helped the company optimize the server load. Overall, there’s a noticeable increase in the solution’s efficiency.

What’s Next

Our partnership with RDS continues to deliver tangible results with ongoing new reports and analysis. Velvetech also keeps working on code refactoring and optimization to further streamline the system, improve its performance, and make it even more coherent.