Welcome to real estate competitive intelligence

The CASAFARI blog offers data-driven analysis of the real estate market. By leveraging machine learning and Big Data, our team of data scientists overcomes the absence of a centralized MLS in Europe, enabling professionals to track asking prices, property histories, and market trends in real time to optimize their business.

1. The real estate agent problem solved by CASAFARI

The buyer’s perspective

High-net-worth buyers often use real estate services that remain largely manual. Most listings are non-exclusive, resulting in frequent overlaps between agency portfolios.

Agencies manage hundreds of listings and struggle to provide detailed, consistent information. According to a CASAFARI data analysis from 2022, floor space and room counts in listings showed an average variation of 136%, while asking prices for the exact same property differed by up to 46% (for instance, Villa “Cielo de Bonaire” in Alcudia, Balearic Islands, had asking prices ranging from €28,000,000 to €50,000,000 listed by different agents).

Supporting real estate agents

In European countries, real estate agents manually supervise the updating, marketing, and sale of hundreds of listings without a centralized MLS (Multiple Listing Service), which is standard practice in the United States.

Daily tasks for European agents include manually sourcing new listings, lead generation, and viewings. This leaves them little time to react to market changes and keep their portfolios up to date. Displaying overpriced or outdated listings on portals or their own websites can severely damage an agent’s reputation.

Buyers notice these anomalies directly in listings or through a simple image search on Google. This makes current lead generation inefficient, as agents lose many of their most valuable leads due to discrepancies across portfolio listings.

The complexity of the property market, combined with a lack of exclusivity and complex property histories in Europe, makes keeping track of price changes and listing data nearly impossible manually. We use algorithms to support estate agents and built a team of data scientists holding PhDs in Artificial Intelligence and Computer Science to solve these challenges.

How we set out to help agents

After analyzing the market and interviewing industry professionals, it became clear what CASAFARI is and how the platform works: an automated system designed to make the market transparent and relieve agents of manual workload.

Unlike many emerging PropTech startups, we do not aim to replace existing players; on the contrary, our goal is to empower and reinforce the agent’s role. We recognize that the real estate market cannot exist without estate agents, whose local expertise provides immense value to property investors.

2. Solution: CASAFARI Smart Property Sourcing + Market Analytics

We simplify real estate agents’ work by optimizing and, where possible, automating it. We help them gain deeper property insights by giving them full access to market data through CASAFARI Property Search and enabling them to source new listings based on Big Data analytics. Combining CASAFARI property sourcing and market analytics with Area Insights allows agents to generate and qualify leads and close more sales. We help them to:

• source new property listings;
• track all price changes in real time;
• know when and through which agency a property is listed, monitoring both asking prices in listings and actual closing prices;
• compare estate agency portfolios across any given area;
• obtain the data required for informed client consultations.

In short, CASAFARI is a comprehensive real estate Big Data and market analytics toolkit built to save real estate agents time and money. Property buyers also receive a higher level of service and, as a result, gain access to better deals.

Why should you visit this blog?

What are we blogging about?

Despite the abundance of information online, finding reliable and accurate property data remains a challenge. We started this blog as a free resource for real estate professionals and buyers who need clear, data-driven direction when analyzing and understanding the prime and second-home market. We are proud to share with you this unique, unbiased view of the prime real estate sector.

Our editorial plan for the coming months focuses on analyzing the state of the property market in countries such as Spain, Portugal, France, and Italy. We believe this is a crucial topic across these regions, where sales transaction volumes continue to outpace price growth.

With a focus on real estate professionals, we will highlight our Big Data solutions and compelling hyper-local insights. Our data-led articles rely on open data resources provided largely by local and national governments, the European Commission, research institutes, and other official open databases.

In collecting and utilizing this data, we adhere to the Open Data Commons Open Database License (ODbL). We also analyze thousands of data points available through web search. Along the way, you will hear from expert members of the CASAFARI team as well as guest industry specialists.

To make this blog as engaging as possible, we will share infographics, research articles, e-books, multimedia content, and more.

You are welcome to submit questions or suggest topics of interest for upcoming insights.

Have your say

The goal of this blog is also to foster an ongoing dialogue with our readers. Every form of feedback is welcome, and you can let us know which topics you would like to see covered in future articles in the comments section.

To stay updated on the latest news and features, follow CASAFARI across our social channels (Facebook, Twitter @CASAFARIRE, LinkedIn, Instagram, and Pinterest).

Thank you for visiting, and enjoy your reading.

Frequently asked questions

Why do property market data across European markets often contain discrepancies?

In European countries, there is no centralized MLS system, and most listings are not managed on an exclusive basis. As a result, agencies manage hundreds of properties manually, leading to overlapping portfolios. This fragmentation causes frequent discrepancies in floor space, room counts, and listed asking prices across portals.

How does CASAFARI support the daily work of real estate agents?

Rather than replacing estate agents, CASAFARI automates manual research using machine learning and Big Data. The platform enables professionals to source new listings, track real-time price changes, and compare local agency portfolios, allowing agents to deliver advice backed by accurate market data.

What tools does CASAFARI offer for property sourcing and market analytics?

CASAFARI provides advanced tools, including Property Sourcing and Area Insights. Through CASAFARI Property Search, agents gain access to a complete overview of listings and asking price histories. Integration with Area Insights allows them to analyze local market trends to make strategic decisions and perform accurate valuations.

Which geographic markets are analyzed on the CASAFARI blog?

The CASAFARI blog analyzes property market dynamics and hyper-local data across major European markets. Focus is given to Italy, Spain, Portugal, and France, delivering data-driven insights for professionals and investors.

What sources are used for the data analyzed in CASAFARI articles?

CASAFARI aggregates and indexes thousands of web data points to track listing asking prices. For actual closing prices and broader market analytics, this is combined with open government data, European Commission sources, and official databases such as the Agenzia delle Entrate in Italy. You can log in to the CASAFARI platform to access these real-time analytics.