WORLD PARITY REPORT | OCTOBER WAVE 2023
GLOBAL RESULTS
Three key takeaways emerge from the data. Firstly, we learn that major OTAs offer rates lower than direct hotel prices the most in high-traffic periods, such as default search parameters and popular booking windows. Same-day and one-night stays prove particularly lucrative. Secondly, a correlation exists between higher hotel prices and increased instances of OTAs undercutting direct rates. Lastly, smaller OTAs often adopt a more aggressive pricing strategy, consistently offering lower rates compared to hotels on any occasion, resulting in higher “Lose” rates.
Graph 1. Global BML in all 61 Locations.
The competitive landscape of hotel pricing is significantly influenced by Online Travel Agencies (OTAs). The competition across the entire OTA spectrum is fierce, with OTAs undercutting hotel rates in 79% of cases. Being price the most important decisive factor for travelers when deciding what channel to use to book incentivizes OTAs to ensure reservations through competitive rates.
These dynamics change when focusing on the established duopoly of Booking and Expedia. These major players are less likely to undercut hotel rates, with the incidence dropping to 49%, a factor potentially influenced by the strength of their brands and powerful loyalty programs.
When examining the top 15 OTAs by volume of impacts, a clear disparity emerges. Established OTAs exhibit a “lose” rate, where they undercut hotel prices, ranging from 24% to 33%, and a ‘meet’ rate between 26% and 30%. As mentioned above, the power of their brand and their strong loyalty programmes offer travelers an additional value than price. Smaller, newer, or regional OTAs demonstrate a significantly higher “lose” rate, often exceeding 40% and reaching as high as 60% (i.e. Vio), because on this type of OTAs price is the only value they can offer to attract customers.
Graph 2. BML by OTA (Top 15 OTAs by Impression share).
ORIGIN
The left graph illustrates the US market, where there is a consistent distribution of Beat, Meet, and Lose rates across both local and international bookings. In contrast, the right graph highlights a distinct trend in the European Union markets, with the Beat rate significantly surpassing the Meet and Lose rates. It shows Europe as a more competitive landscape for hotels. This heightened ‘Lose’ rate is more prevalent in the other markets (non-US, non-EU). These regional differences in pricing strategies between International and Local travelers ultimately balance out, resulting in a global average that shows minimal disparities (see Graph 3. BML by Origin)
Graph 3.1. BML by Origin (US Market).
Graph 3.2. BML by Origin (EU Market).
ANTICIPATION
The disparity between OTAs and hotel direct prices is significantly influenced by booking anticipation.
‘Lose’ rate is most pronounced with same-day bookings. This trend enhances the performance of OTAs, particularly in scenarios where hotel room rates are significantly higher due to last-minute bookings and periods of heightened demand.
Furthermore, searches for same day or same week stays are common default options, influencing the earliest stages of the customer journey and driving substantial traffic. These factors collectively underscore the importance of booking anticipation in the travel industry’s pricing dynamics. OTAs leverage this by gaining a competitive advantage in last-minute bookings, capitalizing on the increased price disparity that characterizes these urgent booking scenarios.
Graph 4. BML by Anticipation.
LENGTH OF STAY
The disparity in pricing between OTAs and hotels directly correlates with the length of stay; shorter stays exhibit a significantly higher price disparity compared to longer stays, such as a week. A trend most pronounced in one-night bookings as opposed to longer durations.
We believe the larger price disparity for shorter stays can be attributed to a higher number of searches for one or two nights’ stay.
Graph 5. BML by Length of stay.
TRAVELER TYPE
The booking behaviors of different traveler groups suggests a direct correlation between demand and pricing disparities: as couples and solo travelers constitute a larger portion of the market, OTAs and hotels focus more on these segments, leading to steeper price differences.
This perspective aligns with the broader understanding that high demand tends to amplify disparities.
Graph 6. BML by Traveler Type.
DIFFERENT OTA TYPES, DIFFERENT PATTERNS
In light of these findings, it becomes evident that the strategies employed by different types of OTAs vary significantly. Mainstream OTAs adopt a more nuanced approach ,tailoring their strategies to specific situations and market conditions. In contrast, smaller, secondary OTAs often adopt a simpler tactic, consistently offering the lowest possible prices regardless of the contextual factors of the offer.
This distinction becomes clear when considering the variation in responses to the factors discussed earlier, which are more pronounced among the major OTAs.
HOTEL CATEGORY
The competition in pricing between hotels and OTAs is more pronounced for lower category hotels than for 5-star establishments. Notably, there’s a 10% greater price disparity in searches for 5-star hotels than for those in the 3-star category.
Graph 7. BML by Hotel Category
DEVICE
The practice of offering different prices on mobile platforms is commonly observed with larger OTAs like Booking.com and Expedia on the right graph, but is noticeably absent among many smaller OTAs on the left one (see the Graph 8. BML by Device).
Graph 8.1. BML by Device (Booking.com and Expedia).
Graph 8.2. BML by Device (Other OTAs).
LOCATION
In the context of city-specific pricing strategies, Paris stands out with the highest level of price parity.
The question arises whether the presence of banned parity clauses in various locations correlates with lower ‘Lose’ rate, as suggested by Paris’s leading position.
However, the contrasting example of Brussels challenges this assumption. A focused analysis on main OTAs indicates a potential relationship between these clauses and a location’s standing in the BML ranking. Yet, this correlation becomes less apparent when examining the BML across all OTAs by location.
Graph 9. Europe Zone.
Graph 10. AMER Zone.
Graph 11. APAC Zone.
Graph 12. MEA Zone.
METHODOLOGY NOTES
The “World Parity Report” presents an authoritative analysis of pricing parity across more than 50 key tourism destinations worldwide. This report, grounded in robust data collection and analysis, seeks to establish our position as experts in the field of hotel pricing strategies and parity.
Using a rigorous methodology that leverages demand data, we have meticulously selected a representative sample of properties from each destination to ensure a confidence level of 95% in most cases, with a minimum of 90% in others. Our study hinges on a comprehensive dataset obtained by scraping information from Google Hotels, aligning our inquiry with real-world consumer behavior and industry practices.
At the heart of our analysis are the Key Performance Indicators (KPIs) known as BML—beat, meet, and lose—where we compare Online Travel Agency (OTA) prices against direct hotel prices.
BML: BEAT, MEET, AND LOSE
BML is a metric used to compare hotel prices across different channels — whether a hotel’s direct price can beat, meet, or is higher (lose) compared to OTA prices.
Beat: Hotel direct prices are lower than OTAs prices.
Meet: Hotel direct prices are equal +/- 0,5% than OTAs prices.
Lose: Hotel direct prices are higher than OTAs prices.
