The OTA growth flywheel is still turning, but regulation, price transparency, and AI are rewriting the rules of competition

Overview

This is an industry primer and in-depth analysis of the global online travel distribution landscape in 2026. The report reviews OTAs' business models and rise, explains how Booking and Expedia built their scale advantages, and analyzes the implications of weakening growth tailwinds, business model adjustments, regulatory changes, the Google traffic landscape, AI, and Airbnb's differentiated model.

Core views

The report first places OTAs within the travel industry's long history of reliance on intermediaries. OTAs connect hotels, airlines, vacation rental and experience providers with travelers, primarily using either the agency model or the merchant model. Under the agency model, hotels generally set prices and travelers pay at check-in or checkout; under the merchant model, OTAs handle more stages of the transaction, and travelers typically pay when booking. The core value of OTAs extends beyond displaying inventory to aggregating supply, acquiring consumers, processing payments, and assuming some transaction risk. The first OTA emerged in 1994, Expedia's model launched in 1996, metasearch services appeared in 1999, and Tripadvisor was founded in 2000. After Priceline acquired Active Hotels and Booking.nl in 2004–2005, it accelerated international expansion, and the industry subsequently became increasingly concentrated among a small number of large platforms. The first stage of OTA success involved moving a large amount of fragmented lodging supply online. Europe's hotel market was relatively fragmented, and Booking's lower-commission agency model made it easier to attract independent hotels, while supply expansion directly drove room-night growth. Since 2008, Booking's room nights have grown at a 22% CAGR, approximately 5 times the industry growth rate and 3 times Marriott's room growth rate. Even after its early supply advantage weakened, Booking continued to gain share through the efficiency of its established platform: in 2019, its hotel supply grew by only 5%, while room nights increased by 11%. The second stage involved using Google as the gateway to demand. The report estimates that by 2018, at least 55% of hotel searches began on Google. Booking was not directly favored by Google; instead, it gained an advantage in search rankings and ad auctions through higher or more effective click bids, expected click-through rates, conversion performance, landing-page quality, and price competitiveness. A sample of prices for 355 hotels covered by the research also shows that the lowest prices can generally be found through Google. Among OTAs, Booking's brands were, on average, more price-competitive than Expedia's brands. This suggests that OTAs may not always offer the lowest prices, but their search presentation, inventory breadth, and page conversion can give consumers a sense of a more comprehensive and attractive selection. The third stage involved converting traffic scale into a supply advantage. The more bookings a platform generates, the easier it becomes to secure better room allocations, availability dates, cancellation terms, payment conditions, and sometimes better prices from hotels. Better supply raises conversion rates, while higher conversion rates improve returns on traffic acquisition and attract more supply, creating a self-reinforcing “scale–traffic–supply–conversion” flywheel. Booking's breadth, visibility, and quality of supply make it the default platform for many travelers. Booking and Expedia currently account for only approximately 12% of global room nights combined, so the report believes OTAs still have room for further penetration and expects OTA room nights to grow at a mid-single-digit rate in the future. However, the traditional growth flywheel is evolving. Booking has shifted markedly from a relatively hands-off agency model toward the merchant model and discounted promotions, while advancing its “Connected Trip” strategy across hotels, flights, car rentals, and attractions. As of the second quarter of 2025, Connected Trip represented a low-double-digit percentage of transactions and grew 30% year over year. Its goal is to engage customers further upstream and reduce customer acquisition costs. Booking and Expedia are also increasing investment in loyalty programs and B2B distribution. On the B2C side, Expedia is reducing its reliance on smaller brands and consolidating its main brands under One Key; on the B2B side, it is increasing the share of its business that provides travel content to other sales channels. These moves are intended both to open new sources of growth and to address rising price transparency, stronger supplier capabilities, and regulatory scrutiny. The industry's historical tailwinds are weakening. During the global financial crisis, online penetration increased by approximately 250 basis points per year from a level of only about 25%; penetration now exceeds 60%, with an annual increase of approximately 150 basis points. There is also increasingly little new platform supply available for OTAs to add, so supply expansion no longer generates substantial incremental growth as naturally as it did in the early years. Tools such as Google Hotels are better suited than traditional OTAs for comparing prices across platforms, making it easier for direct channels and smaller OTAs to reach consumers. Booking and Expedia have therefore increased discounts, while challengers such as TCOM also compete on price. Following the EU's elimination of price-parity clauses, the likelihood that direct channels for midscale and luxury hotels offer lower average prices than OTAs has increased significantly, putting pressure on OTAs. Google and the EU's Digital Markets Act (DMA) have created two-way effects. Google previously expanded direct-booking and smaller-OTA options in hotel search, intensifying competition for prices and sponsored placements. However, after adjusting its hotel product in response to the DMA, organic traffic from Google declined and metasearch shares also shifted. The report believes this has instead given large OTAs more opportunities to acquire customers directly on search results pages, partially reversing the previous Google headwind. The ultimate impact depends on the traffic mix, ad-placement design, and whether OTAs can maintain conversion efficiency. Generative AI is the next competitive battleground, but changes may occur gradually. Consumers are already using AI for inspiration, research, and trip planning, while booking functions are also beginning to be embedded in AI platforms. However, travel prices and inventory are extensive and change rapidly. AI agents cannot rely solely on scraped data and must still connect with inventory and transaction systems, so intermediaries will not simply disappear. The risk is that AI improves cross-platform price comparison and could force OTAs to increase promotions. If sponsored placements decline, AI platforms control the end-customer relationship, or OTAs must share commissions with AI agents, both take rates and customer acquisition economics could suffer. On the other hand, large OTAs' real-time inventory connections, payment capabilities, technology infrastructure, and service systems could also make them critical infrastructure in the AI era. The report emphasizes that the ultimate allocation of value will depend largely on whether AI platforms adopt advertising, transaction commissions, or other revenue models. Airbnb follows a different logic from traditional OTAs. It created a new category through peer-to-peer lodging rather than merely consolidating existing hotel distribution channels, so its growth opportunities derive more from expanding the vacation rental category, meeting lodging demand that is growing faster than hotel supply, entering adjacent businesses, and improving monetization. Most listings on Airbnb's platform are exclusive, and more than 90% of traffic comes directly to the platform, indicating that its brand dependence and reliance on upstream traffic channels are markedly lower than those of traditional OTAs. The report also notes that Airbnb has an industry-leading contribution margin and is driving growth in underpenetrated Europe and other international markets, while its short-term rental room-night growth has begun to outpace that of some peers. AI could still change how travelers discover and book accommodations, but differentiated supply, a strong brand, and technological capabilities provide important defenses. Industry demand ultimately remains affected by macroeconomic conditions and consumer confidence. The report observes a strong correlation between hotel room-night demand and real GDP growth globally and in the US, although demand can temporarily deviate from the trend implied by GDP, with such deviations generally associated with changes in consumer confidence. In a recession scenario, current OTAs lack the high penetration growth, abundant new supply, and clear price-comparison advantages of the previous cycle, so their ability to cushion the downturn may be weaker than in the past. Regarding valuation, the report believes growth and cash conversion are the primary drivers of valuation multiples; Booking has achieved multiple expansion by improving margins and cash conversion.

Analysis framework

The report is structured around industry history and competitive stages. It first explains the agency and merchant business models, then reconstructs the OTA scale flywheel using supply growth, room nights, search traffic, pricing samples, and platform shares. It subsequently compares the business adjustments and competitive advantages of Booking, Expedia, and Airbnb, and assesses the transmission mechanisms of price-parity regulation, changes to Google's products, the DMA, and AI. Finally, the report combines macroeconomic demand, consumer confidence, online penetration, cash conversion, and valuation multiples to derive differentiated company ratings.

Methodology notes

• Competitive and strategic frameworkValue chain analysis

  Analysis of the travel distribution value chain and intermediary roles

  The report follows the chain linking hotels and other travel suppliers, technology and distribution intermediaries, traffic platforms, and consumers to analyze how inventory, customers, payments, and commissions flow, and to determine the value that different intermediaries can capture.

• Industry/sector analysis frameworkSupply-demand framework

  Matching lodging demand with hotel and vacation rental supply

  The report compares growth in lodging demand with hotel and vacation rental supply. It argues that when hotel supply is insufficient, more flexible vacation rental supply must expand to meet demand, forming the basis of Airbnb's category growth thesis.

• Industry/sector analysis frameworkPenetration S-curve

  Changes in the base and growth rate of online travel penetration

  The report compares online penetration of approximately 25% during the financial crisis and annual increases of approximately 250 basis points with current penetration above 60% and annual increases of approximately 150 basis points, illustrating how the digitalization tailwind is weakening as the base expands.

• Event games and behavioral financeEvent-driven analysis

  Distribution changes resulting from the elimination of price-parity clauses and the DMA

  The report analyzes price competition, Google's organic traffic, and customer acquisition opportunities on search pages before and after regulatory changes to assess how these events alter value allocation among OTAs, hotel direct channels, and search platforms.

• Cycle and business conditions frameworkBusiness-cycle inflection analysis

  Analysis of GDP, consumer confidence, and hotel room-night demand

  The report uses the correlation between room-night demand and real GDP to measure the underlying business-cycle trend, then uses consumer confidence to explain periods when demand deviates from that trend, thereby discussing industry sensitivity in a recession scenario.

• Valuation methodology

  Consensus valuation framework driven by growth and cash conversion

  The report does not provide specific valuation multiples or target prices. Instead, it treats growth, margins, and cash conversion as the primary drivers of valuation multiples and uses them to explain Booking's valuation improvement.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Booking（BKNG）

  A major core beneficiary among OTAs, relying on supply, traffic, and conversion rates to form a self-reinforcing flywheel, while transitioning toward the merchant model, Connected Trip, and B2B distribution.

  Strengths

  Scaled supply, strong price competitiveness, a good user experience, data capabilities, expertise in managing Google traffic, and improving margins and cash conversion.

  Weaknesses

  Weakening tailwinds from online penetration and incremental supply, with increasing reliance on traffic acquisition, discounts, and investment in the merchant model.

  Comparison

  Room nights have grown at a 22% CAGR since 2008; its brands are, on average, more price-competitive than Expedia's brands.

  Risks

  Google traffic rules, price-parity regulation, AI-driven traffic diversion, commission sharing, and price transparency could weaken customer acquisition and commission economics.

• Expedia（EXPE）

  Consolidating its B2C brands under One Key while expanding its B2B business that provides travel content to third-party sales channels.

  Strengths

  Possesses a large travel content and distribution base, while B2B has become a more important source of growth.

  Weaknesses

  The report shows that its brands are, on average, less price-competitive than Booking's, and its B2C operations need to improve execution through brand consolidation and loyalty programs.

  Comparison

  Along with Booking, it is one of the world's leading OTAs, but it relatively lags in supply growth and price competitiveness.

  Risks

  Discount competition, changes in Google traffic, AI intermediation, and shifts in customer ownership could affect margins and commission levels.

• Airbnb

  Created a new category through peer-to-peer lodging, with growth relying more on vacation rental category expansion, international penetration, and improved monetization than simply taking share from traditional OTAs.

  Strengths

  Most listings are exclusive, more than 90% of traffic comes directly to the platform, and it possesses a strong brand, technological capabilities, and an industry-leading contribution margin.

  Weaknesses

  Penetration remains relatively low in Europe and certain international markets, requiring continued expansion of supply and use cases.

  Comparison

  Compared with Booking and Expedia, Airbnb is less dependent on search and metasearch traffic, while its short-term rental room-night growth has begun to outpace that of some peers.

  Risks

  AI could change how travelers discover and book accommodations, while lodging demand or supply expansion falling short of expectations could also affect category growth.

• Tripadvisor

  The report rates it Outperform and places it within the competitive landscape of online travel and metasearch.

  Comparison

  The report gives Tripadvisor the same Outperform rating as Airbnb, above the Market-Perform ratings for Booking and Expedia.

  Risks

  AI, adjustments to Google's products, and changes in travel traffic gateways could affect metasearch platforms.

Key data

• Booking room-night CAGR22%Since 2008, approximately 5 times the industry growth rate and 3 times Marriott's room growth rate
• Booking and Expedia share of global room nightsapproximately 12%The report uses this to conclude that OTAs still have room for further penetration
• Booking hotel supply growth in 20195%Room nights grew 11% over the same period, showing that growth no longer depends solely on incremental supply
• Booking room-night growth in 201911%Higher than the 5% hotel supply growth over the same period
• Share of hotel searches beginning on Googleat least 55%The report's estimate for 2018
• Price comparison sampleN=355 hotelsUsed to compare the frequency with which different global channels display the lowest room prices
• Booking Connected Trip share of transactionslow-double-digit percentageAs of the second quarter of 2025, up 30% year over year
• Airbnb direct traffic sharemore than 90%Indicating relatively low reliance on referral channels such as metasearch
• Increase in online penetration during the financial crisisapproximately 250 basis points/yearOnline penetration was approximately 25% at the time
• Current increase in online penetrationapproximately 150 basis points/yearCurrent penetration has exceeded 60%
• Expected OTA room-night growthmid-single-digitThe report's directional expectation for future growth

Impact & implications

The report believes OTAs can continue growing through their relatively low share of global room nights, scaled supply, and transaction capabilities, but industry drivers will shift from simple online penetration and incremental supply toward loyalty, the merchant model, Connected Trip, B2B distribution, and AI connectivity. Traditional OTAs must balance higher conversion rates against increased discounts, while Airbnb relies more heavily on exclusive supply, direct traffic, category expansion, and international penetration. AI will not necessarily eliminate intermediaries, but it could redefine which layer of intermediation controls the customer and captures commissions.

Risks

• AI could divert OTAs' upstream traffic, control end-customer relationships, and demand a share of commissions, thereby weakening OTA commission economics.
• As AI enables easier cross-platform price comparison, OTAs may be forced to increase promotions and discounts.
• The EU's elimination of price-parity clauses has increased the likelihood that hotel direct channels offer lower average prices than OTAs.
• Adjustments to Google's hotel search and advertising products could change organic traffic, sponsored placements, and customer acquisition costs.
• The slowdown in online penetration growth and limited incremental supply are weakening traditional OTAs' structural growth tailwinds.
• Slower economic growth or declining consumer confidence could reduce hotel room-night demand.
• Booking and Expedia face price competition from platforms such as TCOM.

What to watch

• The pace of generative AI adoption in travel inspiration, research, planning, and direct booking, as well as its revenue model.
• Whether OTAs can achieve the report's expected mid-single-digit room-night growth and continue increasing their current approximately 12% share of global room nights.
• Booking Connected Trip's share of transactions, growth rate, and effectiveness in reducing customer acquisition costs.
• Returns on Booking's and Expedia's investments in loyalty programs, the merchant model, and B2B distribution.
• Changes in Google's organic traffic, metasearch share, and OTA customer acquisition opportunities on search pages following implementation of the DMA.
• Price competitiveness among hotel direct channels, Booking, Expedia, and smaller OTAs.
• Airbnb's penetration in Europe and other international markets, expansion of exclusive listings, and direct traffic performance.
• The impact of changes in GDP and consumer confidence on global and US hotel room-night demand.