#realestateanalytics

Looking for reliable US real estate data? Discover the top free public data sources from county records and GIS portals to federal datasets for accurate property insights.

Learn how to collect, standardize, and manage data at scale for ownership tracking, market analysis, and investment decisions.

Read more: https://www.hitechbpo.com/blog/real-estate-data-collection-public-sources.php

Real estate investors rely on data to make better decisions.

Two platforms often considered for property analysis are PulseReal and DealCheck.

While both help investors evaluate opportunities, they focus on different parts of the investment journey.

What Is DealCheck?

DealCheck is a property analysis platform designed to help investors quickly evaluate rental properties, BRRRR projects, flips, and commercial real estate.

Its strength lies in financial analysis.

Users can calculate:

cash flow

cap rates

ROI

rental income projections

financing scenarios

For many investors, DealCheck acts as a deal calculator.

What Is PulseReal?

PulseReal is an AI-powered real estate intelligence platform.

Instead of focusing only on financial calculations, it helps investors analyze properties using AI-driven insights, renovation intelligence, market analytics, and predictive decision-making.

The platform is designed to help users discover opportunities and understand a property's potential before making investment decisions.

Core Difference

The simplest way to compare the two:

DealCheck helps you calculate deals.

PulseReal helps you discover and evaluate opportunities using AI.

Property Analysis

DealCheck focuses heavily on investment metrics and financial modeling.

Investors can quickly estimate returns and compare scenarios.

PulseReal adds another layer by analyzing property conditions, market signals, renovation opportunities, and investment potential through AI-driven insights.

Renovation Intelligence

This is where PulseReal stands out.

PulseReal helps investors understand:

potential renovations

property improvement opportunities

renovation ROI

value-add possibilities

DealCheck primarily focuses on the numbers after assumptions have been entered.

PulseReal helps generate some of those insights before the financial analysis begins.

AI-Powered Insights

DealCheck relies on user inputs and financial models.

PulseReal uses AI to identify patterns, opportunities, and market intelligence from property data.

This can help investors make faster decisions with less manual research.

Predictive Analytics

PulseReal incorporates predictive analytics to help users understand potential future outcomes.

This includes:

market trends

property performance indicators

growth opportunities

investment forecasting

DealCheck focuses more on current deal performance and financial projections.

Who Should Choose DealCheck?

DealCheck may be a good fit if you:

want a dedicated deal calculator

focus heavily on cash flow analysis

compare financing scenarios regularly

need quick investment projections

Who Should Choose PulseReal?

PulseReal may be a better fit if you:

want AI-powered property insights

analyze renovation opportunities

seek predictive market intelligence

want to identify hidden investment potential

prefer data-driven decision-making beyond spreadsheets

Final Thoughts

Both platforms serve real estate investors, but they solve different problems.

DealCheck is a strong choice for financial modeling and investment calculations.

PulseReal goes beyond calculations by using AI to uncover opportunities, analyze renovation potential, and provide predictive real estate intelligence.

If your goal is simply to evaluate numbers, DealCheck is a useful solution.

Overview

A leading real estate brand sought deeper visibility into rental trends across major cities to improve pricing strategies and market positioning. By leveraging Extracting Property Listings from RentHop — City-Level Rental Analysis, we enabled access to accurate, city-level data for better decision-making and competitive advantage.

Using advanced analytics and structured datasets, the client gained actionable insights into rental pricing, demand patterns, and property distribution. This approach empowered the brand to optimize listings, enhance customer targeting, and improve overall performance in a competitive real estate market.

Key Highlights

Data Extraction Excellence: Enabled Extracting Property Listings from RentHop — City-Level Rental Analysis for accurate city-level rental insights.

Comprehensive Listings Data: Delivered Scrape RentHop City-Level Property Listings Data for deeper understanding of rental supply trends.

Automated Data Solutions: Implemented RentHop City-Level Rental Data Scraper ensuring real-time updates and scalable data collection.

Advanced Market Insights: Powered decision-making with RentHop Property Listings Analytics and enhanced Real Estate Analytics capabilities.

Strategic Pricing Advantage: Achieved competitive edge through Price Benchmarking and improved rental pricing strategies across multiple cities.

Client Overview

The client is a fast-growing real estate analytics firm focused on delivering rental insights to property investors, brokers, and urban planners. Their primary markets include major metropolitan cities where rental demand fluctuates frequently. To stay competitive, they required a reliable data source that could provide accurate and timely rental listings at a city level. By leveraging Extracting Property Listings from RentHop — City-Level Rental Analysis, the client aimed to strengthen their data-driven decision-making capabilities.

Additionally, the client needed scalable solutions for RentHop Property Listings Data Scraping to monitor thousands of listings across different neighborhoods. Their goal was to gain visibility into pricing trends, property availability, and tenant demand patterns. With a strong emphasis on analytics and reporting, the client sought to enhance their platform with real-time insights, enabling users to make informed investment and rental decisions. This collaboration allowed them to transform fragmented data into structured intelligence for strategic growth.

Objective

Enable accurate Scrape RentHop City-Level Property Listings Data for comprehensive rental market coverage.

Implement Marketplace Data Tracking to monitor listing changes, price fluctuations, and availability trends.

Improve visibility into city-level rental demand and supply patterns.

Support data-driven pricing strategies and investment decisions.

Automate data collection processes to reduce manual effort and improve efficiency.

Deliver structured datasets for advanced analytics and reporting.

Data Extraction Scope

Platforms Monitored The project focused on extracting data from RentHop, utilizing the RentHop City-Level Rental Data Scraper to capture detailed property listings across multiple cities.

Time Duration Data was collected over a continuous 6-month period to capture seasonal trends, demand fluctuations, and pricing variations across different regions.

Number of SKUs / Categories The dataset included over 50,000 property listings categorized by apartment type, number of bedrooms, location, and amenities, ensuring comprehensive market coverage.

Frequency of Tracking Data extraction was performed daily to ensure real-time updates and accurate tracking of listing changes, price movements, and availability status.

Data Points Collected

Using Web Scraping RentHop Rental Marketplace Data, we collected the following key data points:

Property Title — Name or headline of the listing

Location — City, neighborhood, and address details.

Rental Price — Monthly rent value.

Property Type — Apartment, studio, or shared housing.

Number of Bedrooms — Configuration details.

Number of Bathrooms — Additional property specifications.

Listing Date — Date when the property was listed.

Availability Status — Whether the property is available or rented.

Amenities — Features such as parking, gym, or pet-friendly options.

Listing URL — Direct link to the property listing.

Business Impact Delivered

By leveraging RentHop Property Listings Analytics, the client achieved significant business outcomes:

Improved Pricing Accuracy: Enabled precise rental pricing strategies based on real-time market data.

Enhanced Market Visibility: Provided comprehensive insights into city-level demand and supply trends.

Increased Operational Efficiency: Automated data collection reduced manual effort and improved productivity.

Better Investment Decisions: Data-driven insights helped identify high-growth areas and profitable opportunities.

Competitive Advantage: Access to real-time analytics allowed the client to stay ahead of competitors.

Scalable Data Infrastructure: Built a robust system capable of handling large datasets and expanding to new markets.

These improvements strengthened the client’s position in the real estate analytics industry and enabled sustainable growth.

Tools & Technology Used

The solution leveraged advanced tools and technologies to ensure efficient data extraction and analysis. A custom scraper was developed to handle dynamic website structures and large-scale data collection. API data feeds enabled seamless integration with existing systems, ensuring real-time updates.

Interactive dashboards were created to visualize data trends and provide actionable insights. Automation workflows ensured continuous data collection without manual intervention, improving efficiency and accuracy. Advanced analytics and visualization tools were used to process large datasets and generate meaningful insights.

By combining Real Estate Analytics with Extracting Property Listings from RentHop — City-Level Rental Analysis, the solution delivered a comprehensive data ecosystem. This enabled the client to transform raw data into actionable intelligence, driving better decision-making and improved business outcomes.

Client Testimonial

“Working with this solution has transformed our approach to rental market analysis. The insights gained from Extracting Property Listings from RentHop — City-Level Rental Analysis have significantly improved our pricing strategies and market understanding.

The data accuracy and real-time updates have been exceptional, enabling us to make confident decisions and deliver better value to our clients.”

— Head of Data Analytics

Final Outcome

The project successfully enabled the client to unlock the full potential of rental market data. By leveraging advanced analytics and structured datasets, the client achieved improved operational efficiency and enhanced decision-making capabilities.

A key outcome was the implementation of effective Price Benchmarking, allowing the client to compare rental prices across different cities and identify optimal pricing strategies. This not only improved competitiveness but also increased customer satisfaction.

Overall, the solution delivered a scalable and reliable data framework that supports long-term growth. The client is now equipped with the tools and insights needed to navigate the dynamic real estate market with confidence and precision.

Learn More: https://www.actowizmetrics.com/extracting-property-listings-renthop-city-level-rental-analysis.php

The rapid growth of AI in real estate is creating a new competitive landscape where PropTech AI leaders are defined by their data capabilities. Without a strong data-ready foundation, even the most advanced AI investments fail to deliver value.

By combining real estate analytics, modern data architecture, and intelligent automation, Hexalytics helps organizations transform raw data into strategic insights. This enables better decision-making, improved asset performance, and long-term scalability in a data-driven market.

Building a data-ready foundation is the first step toward successful PropTech AI adoption. Organizations that invest in data quality, integration, and governance are better positioned to scale AI in real estate and unlock advanced insights.

Want reliable property data without expensive subscriptions? Learn how real estate professionals and data aggregators extract high-value real estate information from public sources such as county assessor sites, GIS portals, tax records, census data, and listing platforms.

This approach helps you reduce costs, improve data accuracy, and build scalable datasets for investment analysis, valuation modeling, and market intelligence.

🏢📊 Real Estate Dataset — Prices, Listings & Location Intelligence by Actowiz Solutions

In a fast-moving real estate market, data clarity is the foundation of smarter decisions. Actowiz Solutions delivers a comprehensive Real Estate Dataset designed to help investors, brokers, analysts, and proptech platforms gain deep visibility into property prices, listings, demand patterns, and location-based insights.

This structured dataset consolidates fragmented real estate information into a single intelligence layer, enabling:

🔍 Accurate property price tracking across regions and property types

📈 Active listing analysis and market movement trends

📍 Location-driven demand and city-level performance insights

With continuously updated and standardized data, businesses can:

✅ Analyze market growth and pricing momentum

✅ Identify high-demand locations and emerging hotspots

✅ Compare residential vs commercial performance

From #realestate platforms and consultancies to investors and analytics teams, this dataset transforms raw listing data into actionable market intelligence — helping stakeholders move faster, reduce uncertainty, and make data-backed decisions with confidence.

At Actowiz Solutions, we specialize in turning complex real-world data into clean, scalable, and insight-ready datasets that drive smarter outcomes across industries.