About Cocoonr

Cocoonr operates 5,000 properties across France, with on-site agencies in 20 major cities and nationwide coverage under its secondary brand, Cocoonr Distribution. Success, as their team sees it, is a mix of three things: growing the portfolio, maximizing revenue from current properties, and preventing client churn. With 5,000 properties, mastering churn is almost as important as signing new ones, and with a decade of operating history, Cocoonr is confident in its ability to perform and make the most of its existing properties.

The challenge

Before AirDNA, Cocoonr relied on internal data, manual market research, and publicly available information from platforms like Airbnb. This approach was more time-consuming and less reliable, especially in areas with limited portfolio history. Benchmarking comparable properties, optimizing pricing strategies, anticipating market trends, and providing owners with concrete, data-driven insights into performance potential were all more difficult than they needed to be.

The breaking point was a lack of visibility into how supply and demand evolved over time within a market. Without that view, it was difficult to anticipate booking windows, demand peaks linked to events or seasonality, or shifts in market dynamics. Performance on specific dates and seasons suffered as a result.

• Evaluating opportunities in markets where internal benchmarks were thin
• Validating pricing assumptions without reliable comparables
• Understanding local demand trends and booking windows
• Supporting owner conversations with credible market data

How they use AirDNA

All five members of Cocoonr's Revenue Management Department use AirDNA every day. They reach for it primarily when they don't have enough internal data on a specific city or area, for potential studies, new property launches, pricing base creation and adjustment, and broader market analyses, including events.

The most valuable components are the Advanced Insights tabs, which allow the team to identify comparable high-performing properties, analyze revenue ranges, and track key metrics: occupancy rate, ADR, RevPAR, seasonality, and booking windows. Detailed historical data on specific listings helps refine pricing strategies and ground owner discussions in reality.

Results

Cocoonr noticed the first results quickly — within a few months. They were able to provide more accurate revenue projections, identify demand peaks and raise prices at the right moment, and set the right prices from the launch of new properties in new markets.

AirDNA now plays a role on both the commercial and revenue-optimization sides of the business. The team can evaluate new opportunities faster, strengthen property potential studies, validate pricing assumptions, and support commercial discussions with more reliable market benchmarks.

On pricing alignment with owners, the team primarily uses AirDNA data to convince them to adjust specific pricing strategies that they believe in, but that aren't market-compliant — providing an objective, third-party basis for difficult conversations.

What changed most

The team is now able to turn intuitions into facts. As Cocoonr put it: "Everyone believes they know their market and are performing at their best. However, this remains highly subjective, and external data is needed to validate whether those intuitions are actually correct. Without external data, there will inevitably be missed opportunities and underperformance somewhere."

Looking ahead: Booking.com data integration

One aspect of Cocoonr that is particularly exciting is the integration of Booking.com data, the opportunity to gain visibility into a segment of the market that is often more professionally managed.

In many destinations, Booking.com tends to have a higher concentration of professional property managers, serviced apartments, and hospitality operators, whereas Airbnb includes a broader mix of both professional operators and individual hosts. Professional operators typically rely on more sophisticated revenue management practices, dynamic pricing strategies, and performance monitoring. As a result, Booking.com data can provide valuable additional insights into how professionally managed inventory reacts to market demand, pricing fluctuations, seasonality, and major events.

For Cocoonr, this is especially important because it allows them to benchmark against operators whose management practices are often closer to their own. It also helps create a more representative view of overall market performance, rather than relying on a single distribution channel.

By combining Airbnb and Booking.com data, AirDNA will provide a richer and more comprehensive understanding of occupancy trends, ADR evolution, booking behavior, and revenue performance, helping Cocoonr make even more informed decisions when evaluating property potential, building pricing strategies, and advising property owners.