A deep dive into the Oliver Wyman–TFWA report on the recovery, transformation, and future of travel retail across the Asia Pacific region.
Executive Summary
The Asia Pacific travel retail market is entering a pivotal year in 2026. According to the latest joint report by Oliver Wyman and the Tax Free World Association (TFWA), Asia Pacific Travel Retail Trends Insight 2026, the region is experiencing a multi-dimensional recovery fueled by rebounding Chinese consumer confidence, surging outbound travel, the emergence of India as a long-term growth engine, and a wave of AI-driven innovation reshaping the retail experience. However, significant structural challenges remain — including consumption repatriation to domestic channels, a shrinking conversion-rate gap at airports, and the urgent need for differentiated value propositions beyond price.
This article provides a complete, data-rich breakdown of the report’s findings, structured to stand alone as a reference for industry professionals, investors, and anyone tracking the evolution of Asia Pacific travel retail.
Part 1: The Macro Recovery — Chinese Consumer Confidence Rebuilds
1.1 Consumer Confidence Index: The Turnaround
After three consecutive years of decline from 2022 to 2025, the Oliver Wyman High-Income Consumer Confidence Index for China rebounded sharply in 2026.
Table 1: Oliver Wyman China High-Income Consumer Confidence Index, 2022–2026 (Household monthly income ≥ RMB 30,000; Base 100 in 2022)
| Year | Confidence Index | YoY Change |
|---|---|---|
| 2022 | 100 | — |
| 2024 | 75 | ↓ 25 |
| 2025 | 71 | ↓ 4 |
| 2026 | 115 | ↑ 44 (+62%) |
Source: Oliver Wyman China Tourist Survey (2022, 2024, 2025, 2026). Sample sizes: 4,000 (2022), 1,500 (2024), 2,000 (2025), 1,250 (2026).
The 2026 index of 115 marks the first time it has exceeded the 2022 baseline, driven by broad-based recovery across both short-term (current) and long-term (5-year) outlooks.
Table 2: Confidence Index Breakdown by Time Horizon, 2022–2026
| Year | Current Index | YoY Δ | 1-Year Index | YoY Δ | 5-Year Index | YoY Δ |
|---|---|---|---|---|---|---|
| 2022 | 81 | — | 109 | — | 101 | — |
| 2024 | 74 | -8 | 73 | -35 | 81 | -19 |
| 2025 | 69 | -4 | 70 | -3 | 74 | -7 |
| 2026 | 116 | +47 | 117 | +47 | 109 | +35 |
In 2026, sentiment proportions shifted dramatically toward optimism:
- Current outlook: Positive sentiment rose from 18% (2025) to 64% (2026), while negative sentiment fell from 22% to just 2%.
- 1-year outlook: Positive sentiment surged from 19% to 73%; negative dropped from 23% to 3%.
- 5-year outlook: Positive sentiment climbed from 26% to 75%; negative shrank from 22% to 1%.
1.2 Confidence Recovery Led by Older Generations
The rebound was not uniform across age groups. Baby Boomers showed the strongest recovery, while younger cohorts remained comparatively cautious about the long-term outlook.
Table 3: 2026 High-Income Consumer Confidence by Age Group
| Generation | Birth Years | Current | 1-Year | 5-Year | 2026 Overall | 2025 Overall | Change |
|---|---|---|---|---|---|---|---|
| Gen Z | After 1997 | 118 | 115 | 102 | 113 | 69 | +44 |
| Millennials | 1981–1996 | 110 | 114 | 105 | 111 | 73 | +38 |
| Gen X | 1965–1980 | 113 | 115 | 112 | 114 | 71 | +43 |
| Baby Boomers | 1946–1964 | 127 | 125 | 115 | 123 | 67 | +56 |
Source: Oliver Wyman China Tourist Survey (2025, 2026).
All generations registered increases of 38 to 56 points year-on-year, but Baby Boomers — with the highest overall confidence at 123 — were the standout group. Notably, Gen Z’s 5-year outlook (102) was the lowest across all groups, indicating persistent caution among young consumers about long-term economic prospects.
1.3 Macro Drivers of the Rebound
Four key macro factors underpin the confidence recovery:
- Stock market performance: The CSI 300 Index improved from 4,564 (2022) to 4,807 (2026), boosting wealth among asset-holding households — particularly older demographics.
- RMB appreciation: The RMB–USD exchange rate strengthened from 0.157 (2022) to approximately 0.146 (2026), enhancing purchasing power for imported goods and overseas travel.
- Real estate stabilization: Policy easing in China’s property sector helped alleviate fears of continued home-price declines, especially in Tier-1 cities.
- US–China trade detente: After the escalation of trade tensions in 2025, the easing of bilateral frictions in 2026 boosted consumer confidence in economic growth.
Part 2: Chinese Outbound Travel — Growth and Shifting Patterns
2.1 Outbound Travel Volumes Approach Pre-Pandemic Peak
China’s outbound travel is set to reach — and potentially surpass — 2019 levels in 2026.
Table 4: China Outbound Travel Volumes by Year
| Year | Total Outbound Trips | High-Income Outbound Rate¹ |
|---|---|---|
| 2019 (Pre-COVID) | ~155 million | 32% |
| 2023 | ~8.8 million | 24% |
| 2024 | ~123 million | 26% |
| 2025 | ~140–150 million | 30% |
| 2026E | ~155–165 million | 32% |
¹ Share of households with monthly income ≥ RMB 30,000 that traveled abroad in the year.
Source: China Ministry of Culture and Tourism, Oliver Wyman China Tourist Survey (2023–2026).
The projected increase of approximately 15 million additional outbound trips in 2026 alone is equivalent to Singapore’s total annual visitor arrivals in 2025. The high-income outbound travel rate is expected to return to the 32% pre-pandemic level.
2.2 Holiday Travel: Strong International Growth
Public-holiday travel data from early 2026 confirms the momentum:
Table 5: 2026 Holiday Travel Growth (YoY)
| Holiday Period | Domestic¹ | International (incl. HK/Macau/Taiwan) |
|---|---|---|
| 2026 New Year | +5.2% | +39.1%² |
| 2026 Spring Festival | +5.7% | +10.2% |
| 2026 Qingming Festival | +6.8% | +4.4% |
¹ Daily visitor count basis. ² 3-day holiday in 2026 vs 1-day in 2025.
Source: China Ministry of Culture and Tourism, State Council, Ctrip Group, Oliver Wyman analysis.
International travel growth during the New Year period (+39.1%) was particularly striking, driven in part by a longer holiday window. Short-haul trips dominated, while long-haul and premium travel continued to gain traction according to Ctrip Group.
2.3 Short-Haul Destinations Surge in Popularity
Chinese high-income tourists are increasingly favoring short-haul destinations, with Korea, Singapore, and Thailand experiencing the most dramatic growth in preference.
Table 6: Chinese High-Income Tourist Destination Preferences, 2025 vs 2026 (% of respondents)
| Destination | 2025 | 2026 | Change (pp) |
|---|---|---|---|
| Short-Haul | |||
| Hong Kong | 44 | 46 | +2 |
| Korea | 14 | 39 | +25 |
| Singapore | 29 | 36 | +7 |
| Thailand | 22 | 29 | +7 |
| Macau | 32 | 29 | -3 |
| Japan | 27 | 28 | +1 |
| Malaysia | 19 | 24 | +5 |
| Taiwan | 15 | 16 | +2 |
| Vietnam | 5 | 9 | +3 |
| Long-Haul | |||
| Australia / New Zealand | 17 | 20 | +2 |
| United Kingdom | 10 | 19 | +9 |
| United States | 6 | 13 | +6 |
| Western Europe (excl. UK) | 6 | 10 | +4 |
| Canada | 6 | 9 | +3 |
Source: Oliver Wyman China Tourist Survey (2025, 2026).
South Korea registered the single largest increase — a 25-percentage-point surge from 14% to 39% — likely driven by improved diplomatic relations, geographic proximity, and competitive retail offerings. The United Kingdom (+10pp) led long-haul destinations. Meanwhile, Macau was the only destination to see a decline (-3pp).
Part 3: Luxury Spending — Category Dynamics and Generational Shifts
3.1 Overall Luxury Spending Intent Rebounds
In 2026, Chinese high-income consumers are significantly more willing to spend on personal luxury goods than in prior years, reversing a two-year decline.
Table 7: Personal Luxury Spending Intent, 2024–2026 (Share of respondents expecting to spend more vs less on personal luxury goods)
| Year | Significant Decrease | Decrease | Increase | Significant Increase | Net Change |
|---|---|---|---|---|---|
| 2024 | 2% | 20% | 19% | 2% | -2% |
| 2025 | 1% | 24% | 18% | 1% | -6% |
| 2026 | 4% | 13% | 38% | 10% | +31% |
Source: Oliver Wyman China Tourist Survey (2024, 2025, 2026).
After a net decline of 6 percentage points in 2025, the 2026 net spending-intent figure jumped to +31% — a year-on-year improvement of 37 percentage points. This is the strongest luxury spending intent since the survey began.
3.2 Category-Level Spending Expectations
Not all categories benefit equally. Premium beauty and luxury apparel/footwear lead, while watches and leather goods lag.
Table 8: 2026 Personal Luxury Spending Intent by Category (Net % of respondents expecting to spend more vs less, vs 2025)
| Category | Significant Decrease | Decrease | Increase | Significant Increase | Net |
|---|---|---|---|---|---|
| Premium Beauty | 10% | 2% | 40% | 8% | +37% |
| Luxury Apparel & Footwear | 12% | 3% | 37% | 8% | +30% |
| Jewelry | 14% | 5% | 34% | 9% | +24% |
| Watches | 9% | 17% | 25% | 6% | +6% |
| Leather Goods | 5% | 15% | 21% | 3% | +4% |
Source: Oliver Wyman China Tourist Survey (2025, 2026).
3.3 Generational Preferences Across Categories
Generational differences in luxury spending are pronounced, with important implications for brand and category strategies.
Table 9: 2026 Personal Luxury Net Spending Intent by Generation and Category
| Category | Gen Z (post-1997) | Millennials (1981–1996) | Gen X (1965–1980) | Baby Boomers (1946–1964) |
|---|---|---|---|---|
| Leather Goods | +5% | +8% | +12% | +21% |
| Luxury Apparel & Footwear | +32% | +31% | +34% | +50% |
| Watches | +17% | -5% | +14% | +31% |
| Jewelry | +35% | +12% | +41% | +45% |
| Premium Beauty | +45% | +57% | +45% | +39% |
Source: Oliver Wyman China Tourist Survey (2025, 2026).
Key observations:
- Premium beauty and luxury apparel show the strongest momentum across all age groups, positioning them as the categories with the greatest near-term growth potential in travel retail.
- Gen Z and Millennials prefer lower-ticket, higher-frequency items, favoring instant-gratification products that offer aspirational value without the commitment of high price points.
- Leather goods and watches remain relatively soft across all generations. Millennials even show a net-negative intent (-5%) for watches.
- Baby Boomers exhibit the most dramatic rebound, with net positive intent above +30% across all five categories, and +50% for luxury apparel and footwear.
Part 4: China’s Consumption Repatriation — A Structural Headwind
4.1 The Shift to Domestic Channels
One of the most significant structural trends reshaping Asia Pacific travel retail is the repatriation of Chinese luxury consumption from offshore to onshore channels. In 2019, overseas purchases accounted for 55% of total Chinese luxury spending. By 2026, that share is expected to fall to just 25%.
Table 10: Offshore Share of Total China Luxury Consumption
| Year | Offshore Share |
|---|---|
| 2019 | 55% |
| 2025 | 24% |
| 2026E | 25% |
Table 11: 2026 China Luxury Spend by Channel
| Channel | Share of Total |
|---|---|
| Domestic duty-paid | 50% |
| Daigou (domestic)² | 15% |
| Hainan & other domestic duty-free | 10% |
| Offshore duty-free | 17% |
| Offshore duty-paid | 8% |
² Daigou spend treated as domestic consumption based on end-consumer’s purchase location.
Source: Oliver Wyman China Tourist Survey (2025, 2026).
Five structural factors are driving this repatriation:
- Travel-purpose shift: Culture, cuisine, and experiences have become the primary focus of outbound travel. Fewer than 15% of Chinese outbound tourists now cite shopping as their main purpose.
- Stronger domestic clienteling: Over 75% of luxury consumers maintain regular contact with their sales advisors in China. Higher service standards are pulling customers back to domestic stores.
- Hainan’s resurgence: Government policy support and subsidies are positioning Hainan as a premier duty-free shopping destination.
- Global price harmonization: Narrowing price gaps between domestic and overseas channels have reduced the incentive to shop abroad.
- Domestic store expansion: China accounted for roughly 40% of new luxury store openings globally in 2024, with year-on-year growth of approximately 10%.
4.2 Hainan Offshore Duty-Free: The Recovery Narrative
After contracting for two consecutive years, Hainan’s offshore duty-free sales returned to growth in late 2025 and accelerated sharply into 2026.
Table 12: Hainan Offshore Duty-Free Monthly YoY Sales Growth, 2024–2026
| Month | YoY Growth |
|---|---|
| Sep 2024 | -38% |
| Oct 2024 | -35% |
| Nov 2024 | -22% |
| Dec 2024 | -6% |
| Jan 2025 | -13% |
| Feb 2025 | -13% |
| Mar 2025 | -5% |
| Apr 2025 | -7% |
| May 2025 | -1% |
| Jun 2025 | -5% |
| Jul 2025 | -7% |
| Aug 2025 | -4% |
| Sep 2025 | +3% |
| Oct 2025 | +13% |
| Nov 2025 | +27% |
| Dec 2025 | +17% |
| Jan 2026 | +45% |
| Feb 2026 | +15% |
Source: BofA Global Research, Hainan Customs, social media sentiment analysis, Oliver Wyman analysis.
Three catalysts drove the Hainan turnaround:
- Government and retailer subsidies (from Oct 2025): Coupons and deep discounts effectively lowered real purchase prices.
- AI-powered price comparison and social amplification (from Nov 2025): Social media buzz around Hainan duty-free value increased 40% month-on-month.
- CDF Hainan e-commerce upgrade (from Nov 2025): Expanded digital reach, broader category selection, and the addition of “order online, pick up in store” services.
Part 5: India — The Next Growth Engine
5.1 A More Diversified Asian Traveler Base
For the next decade, Asia Pacific travel retail growth will be driven by a substantially more diverse mix of traveler nationalities than in the past. More than 80% of surveyed industry executives believe future Asian travel growth will come from a broader, more diversified traveler base.
Table 13: Contribution to Asia Pacific Travel Retail Growth¹ by Tourist Nationality
| Tourist Nationality | 2015–2019 | 2025–2035 (Forecast) |
|---|---|---|
| Chinese | ~65% | ~40% |
| Indian | ~5% | ~20% |
| South Korean | ~9% | ~10% |
| Other nationalities | ~25% | ~30% |
¹ Excluding daigou-related growth.
Source: Generation Research, government statistics, UN Tourism, Oliver Wyman–Travel Retail Executive Survey (2026).
While Chinese tourists will remain the single largest contributor, their relative share is expected to shrink from 65% to 40%. India is the biggest story in the reshuffling, projected to quadruple its contribution from 5% to 20%.
5.2 India’s ~4× Travel Retail Growth Trajectory (2025–2035)
Oliver Wyman projects that Indian tourist travel retail spending in Asia Pacific will grow approximately fourfold between 2025 and 2035, driven by three compounding factors:
Table 14: Drivers of Indian Travel Retail Spending Growth, 2025–2035
| Driver | Multiplier | Rationale |
|---|---|---|
| Middle-class & affluent population growth | 2.8× | Economic expansion will enlarge the emerging middle, middle, and affluent segments |
| International trips per capita | 1.1× | Affluent Indians travel internationally 1.8× more frequently than middle-income Indians |
| Travel retail spend per trip | 1.3× | Affluent consumer average travel retail spend is 2.3× that of middle-income groups, with further upside potential mirroring early Chinese trajectory |
Combined: ~4× (2025–2035)
Source: India Ministry of Tourism, World Bank, Oliver Wyman India Tourist Survey (2026).
5.3 India vs. China: Fundamentally Different Consumer Profiles
Indian high-income tourists are not simply “the next Chinese luxury consumer.” Their behaviors, preferences, and motivations are structurally different, requiring distinct commercial approaches.
Table 15: China vs India — High-Income Tourist Profiles
| Dimension | India | China |
|---|---|---|
| Dominant demographic | Gen Z / Millennials | Millennials and older |
| Preferred destinations | Middle East (15M visits vs 8M to APAC) | Hong Kong, Korea, Singapore |
| Value proposition | Price matters; 2.2× average spend gap makes “value-for-price” conversion critical | Must be recognizably luxury; clear brand visibility and premium perception essential |
| Key triggers | High-touch service, strong brand endorsement, social currency | Exclusive access, pre-sale, airport QR-code ordering, home delivery |
Table 16: Duty-Free Behavior — India vs China
| Metric | India | China |
|---|---|---|
| Gifting as % of duty-free purchases | 41% | 17% |
| Pre-planned purchase before entering store | >33% | 25% |
| Wine & spirits as #1 purchase category | 58% | 5% |
| Arrival duty-free shopping share | 70–80% | 25–50% |
Source: India Ministry of Tourism, TFWA, Oliver Wyman China and India Tourist Surveys (2026).
For Indian consumers, duty-free shopping is a more purpose-driven, value-oriented, and arrival-centric behavior. Gifting accounts for over 40% of purchases — more than double the Chinese share. Wine and spirits dominate at 58%, compared to just 5% among Chinese tourists.
5.4 Indian Millennials: The Core Travel Cohort
India’s Millennial generation shows the strongest international travel intent and is the fastest-growing high-income segment.
Table 17: Indian High-Income Consumer Net Travel Intent by Generation (April 2026) (Household monthly income ≥ INR 300,000)
| Generation | Net International Travel Intent |
|---|---|
| Gen Z | +42% |
| Millennials | +50% |
| Gen X | +40% |
| Baby Boomers | -19% |
Source: Oliver Wyman India Tourist Survey (2026).
Three structural advantages underpin Millennial travel growth in India:
- Rising affluence: The high-income share (annual income ≥ USD 32,000) rose from 18% (2024) to 23% (2025), a +5pp increase, with Millennials as the fastest-growing cohort.
- Lower travel barriers: The share of Millennials adopting low-cost travel modes (e.g., budget airlines) has doubled in recent years.
- Lower dependency burden: India’s old-age dependency ratio is only 12%, roughly half of China’s level, and is projected to continue declining.
5.5 Indian Destination Preferences: Short-Haul Rising
Table 18: Indian High-Income Tourist Destination Preferences, 2025 vs 2026
| Destination | 2025 | 2026 | Change (pp) |
|---|---|---|---|
| Asia Pacific | |||
| Singapore | 43 | 46 | +3 |
| Japan | 25 | 33 | +9 |
| Thailand | 27 | 31 | +4 |
| Australia / New Zealand | 20 | 28 | +8 |
| Malaysia | 18 | 26 | +8 |
| Hong Kong | 14 | 22 | +8 |
| Korea | 9 | 17 | +8 |
| Vietnam | 10 | 17 | +7 |
| Mainland China | 16 | 16 | +1 |
| Middle East | |||
| UAE | 26 | 25 | -1 |
| Saudi Arabia | 24 | 21 | -3 |
| Qatar | 14 | 17 | +3 |
| Europe / Americas | |||
| United Kingdom | 20 | 25 | +5 |
| United States | 19 | 23 | +3 |
| Canada | 11 | 18 | +6 |
Source: Oliver Wyman India Tourist Survey (2026).
APAC destinations saw broad-based growth in Indian traveler preference, with Japan (+9pp) leading. Meanwhile, Middle East preferences softened slightly, potentially due to geopolitical considerations.
5.6 India Duty-Free Category Rankings
Table 19: India Tourist Duty-Free Purchase Intent by Category
| Rank | Category | Net Intent¹ |
|---|---|---|
| #1 | Confectionery & Food | +46% |
| #2 | Wine & Spirits | +42% |
| #3 | Gold | +41% |
| #4 | Luxury Apparel & Footwear | +39% |
| #5 | Electronics | +39% |
| #6 | Jewelry | +38% |
| #7 | Premium Beauty | +37% |
¹ Net intent = % expecting to buy more in next 2 years minus % expecting to buy less.
Source: Oliver Wyman India Tourist Survey (2026).
Part 6: The Airport Retail Performance Gap
6.1 Post-Pandemic Travel Retail Lags Visitor Recovery
Despite passenger volumes recovering close to 2019 levels, travel retail sales (excluding daigou) remain significantly behind.
Table 20: Asia Pacific Travel Indicators, 2025 vs 2019
| Indicator | Change (2025 vs 2019) |
|---|---|
| Tourism expenditure | +6% |
| International visitor arrivals¹ | -6% |
| Travel retail sales² (excl. daigou) | -18% |
¹ Including domestic traffic and domestic duty-free in Jeju (Korea), Okinawa (Japan), and Hainan (China). ² Estimated based on 2019 conversion rates and spend per customer.
Source: Generation Research, government statistics, UN Tourism, Oliver Wyman analysis.
Oliver Wyman estimates that closing this gap represents a ~USD 5 billion (approximately 20%) revenue opportunity for the Asia Pacific travel retail industry.
6.2 Airport Conversion Rates: A Wide Performance Gap
A comparison of airport duty-free conversion rates and average spend per passenger reveals substantial variation — and significant room for improvement at many Asian hub airports.
Table 21: Airport Duty-Free Conversion Rate and Spend Per Passenger, 2025 (Selected Hubs)
| Airport (Code) | Region | Conversion Rate | Spend per PAX (USD) |
|---|---|---|---|
| Beijing Capital (PEK) | APAC | ~7% | ~70 |
| San Francisco (SFO) | Americas | ~7% | ~100 |
| London Heathrow (LHR) | Europe | ~10% | ~150 |
| Madrid (MAD) | Europe | ~11% | ~90 |
| Singapore Changi (SIN) | APAC | ~12% | ~100 |
| Seoul Incheon (ICN) | APAC | ~14% | ~85 |
| Dubai (DXB) | Middle East | ~15% | ~185 |
| Paris CDG | Europe | ~15% | ~155 |
| Hong Kong (HKG) | APAC | ~16% | ~120 |
| Doha (DOH) | Middle East | ~19% | ~90 |
| Bahrain (BAH) | Middle East | ~21% | ~90 |
| Rome Fiumicino (FCO) | Europe | ~23% | ~75 |
| Istanbul (IST) | Europe | ~26% | ~40 |
Source: Expert interviews, Oliver Wyman analysis.
The data reveals that APAC airports cluster in the lower-left quadrant, with conversion rates below 16% and spend per passenger generally below USD 120. Dubai (DXB) stands out in the region with an industry-leading combination of 15% conversion and USD 185 per passenger.
Part 7: Three Strategic Levers to Close the Gap
Oliver Wyman identifies three key levers for brands and travel retailers to reclaim growth:
Lever 1: Extend Dwell Time in Airport Retail
Time spent shopping in airport duty-free is declining. Chinese tourists’ average shopping time dropped 19% from 32 minutes (2024) to 26 minutes (2026). Indian tourists saw an 8% decline from 25 to 23 minutes.
Table 22: Average Airport Duty-Free Shopping Time
| Tourist Group | 2024 | 2026 | Change |
|---|---|---|---|
| Chinese | 32 min | 26 min | -19% |
| Indian | 25 min | 23 min | -8% |
Table 23: Average Airport Dwell Time by City
| City / Airport | Dwell Time |
|---|---|
| Singapore (Changi) | 29 min |
| Seoul (Incheon) | 27 min |
| Bangkok (Suvarnabhumi) | 26 min |
| Tokyo (Haneda) | 26 min |
| Hong Kong | 24 min |
| Doha | 20 min |
| Mumbai | 15 min |
| Delhi | 13 min |
Source: Oliver Wyman China and India Tourist Surveys (2026).
Singapore’s 29-minute average is 2.2× Delhi’s 13 minutes, highlighting the potential for airport-experience investments to unlock substantially more shopping time.
“People are indeed spending more time in airports, but they aren’t spending it shopping — they’re in lounges, restaurants, or on their phones.” — Global Channel Head, Luxury Group
Best practice: Converting time into engagement
Brands and retailers are transforming travel retail from passive shelf displays into pre-bookable, shareable, pre-flight experiences:
- Pre-trip outreach: CRM and media activation turn travel retail into a planned destination within the traveler’s journey.
- Magnetic attractions: Spaces worth visiting during long layovers — lounges, cafes, beauty salons, spas.
- Conversion and remarketing: Exclusive launches, pre-orders, and membership programs that sustain engagement post-travel.
- Hyper-personalized experiences: AI, diagnostics, art installations, and bespoke services that deepen emotional connection.
Case study: Copenhagen Airport — Prada Beauty
- Multi-million reach
- 7 minutes average engagement time
- Conversion rate 9 percentage points above industry average
Additional examples:
- Louis Vuitton Café — London Heathrow
- La Prairie Spa — Sydney Airport
- Shilla Duty-Free Beauty Loft — Singapore Changi
- Dior Beauty Lounge — Doha Hamad International
Lever 2: Deliver a Differentiated Value Proposition Beyond Price
Price remains important, but in an era of unprecedented price transparency — driven by social media price-comparison content and AI-generated cross-channel pricing analysis — travel retail can no longer win on price alone.
Social media platforms are filled with consumer-generated price-comparison tables contrasting duty-free prices against domestic retail, Tmall, JD.com, and other channels. AI tools like DeepSeek can now generate comprehensive cross-channel price comparisons in seconds, making it nearly impossible to sustain a meaningful price advantage.
The implication: brands and retailers must build value propositions rooted in exclusivity, experience, and immediacy — not discounting.
Lever 3: Build Flexibility for a More Diverse Traveler Mix
As the traveler base becomes more diverse — with Indian tourists projected to contribute 20% of regional growth by 2035 — airports must dynamically adapt products, pricing, promotions, and services to match evolving passenger profiles. A one-size-fits-all global playbook no longer works.
Table 24: Airport Duty-Free Perception Gap — Chinese vs Indian Tourist Rankings (Top 10 Airports)
| Airport | Dimension | Chinese Rank | Indian Rank |
|---|---|---|---|
| Tokyo | Service quality | #1 | #10 |
| Tokyo | Checkout speed | #3 | #10 |
| Hong Kong | Store layout & zoning | #4 | #9 |
| Hong Kong | Brand & product selection | #5 | #9 |
| Singapore | Pricing | #5 | #1 |
| Singapore | Store layout & zoning | #10 | #2 |
Source: Oliver Wyman China and India Tourist Surveys (2026).
The perception gap is stark. Chinese tourists rate Tokyo’s service quality #1; Indian tourists rate it last. Singapore’s pricing ranks #5 for Chinese visitors but #1 for Indians — while its store layout ranks #10 for Chinese but #2 for Indians.
Key drivers of these differences:
- Chinese tourists value Chinese-language signage, Mandarin-speaking sales staff, digital payment options, and a more curated, goal-oriented shopping path.
- Indian tourists prefer the compact layouts and spirits-centric “destination retail” approach seen at airports like Dubai, Doha, and Changi, with more browsing-oriented journeys.
Best practices in flexibility:
- Localized exclusives: F1 × KitKat co-branded activation during the São Paulo Grand Prix — blending city culture with event themes, featuring airport-exclusive and race-limited products.
- Airport membership programs: Integrating browse/purchase, terminal pickup, and cross-category benefits (duty-free, convenience stores, F&B, lounges, local travel) — unlocking 3× spend uplift.
- Data-sharing ecosystems: Leveraging cross-channel data (e.g., cruise spending) to understand nationality-specific preferences, enabling 5–15% revenue uplift through hyper-personalization, demand forecasting, and inventory optimization.
Part 8: AI and Innovation — The Next Frontier
8.1 The Innovation Imperative
76% of surveyed executives believe innovation is critical for sustained growth in Asia Pacific travel retail. However, only 40% say their organizations treat innovation as a top investment priority — signaling a significant execution gap.
“AI is an important enabler for understanding customers better, but the product itself, customer relationships, and human touch remain the core of value creation.” — Luxury Brand Executive
8.2 Current and Planned AI Deployment
AI adoption in travel retail remains nascent on the customer-facing side, but deployment plans are aggressive for the next 12 months.
Table 25: AI Solution Deployment in Asia Pacific Travel Retail (% of surveyed executives)
| AI Application Area | Deployed | Planned (12 months) | No Plan / Unsure |
|---|---|---|---|
| Internal & external reporting | 40% | 47% | 13% |
| Demand forecasting & supply chain optimization | 20% | 33% | 47% |
| Visual merchandising / Planogram / In-store automation | 20% | 47% | 33% |
| Customer service | 20% | 33% | 47% |
| Dynamic pricing & promotion optimization | 13% | 40% | 47% |
| Brand protection / Fraud / Daigou detection | 13% | 33% | 53% |
| Staff management (scheduling, etc.) | 13% | 40% | 47% |
| Store operations (checkout, etc.) | 7% | 33% | 60% |
| Personalization / CRM / Targeted offers | 7% | 53% | 40% |
Source: Oliver Wyman Travel Retail Executive Survey (2026).
Personalization and CRM stand out as the area with the single largest planned deployment increase — jumping from just 7% deployed to 53% planning deployment within 12 months. Only 20% of firms have deployed any customer-facing AI, but 65% plan to deploy within 12 months.
8.3 AI in Action: Customer-Facing Applications
Three real-world AI deployments illustrate the emerging playbook:
- Scenario-based product recommendation: Pernod Ricard / Lotte Duty-Free at Changi T1 deployed an AI-powered boutique that provides personalized tasting recommendations via a robotic bartender, tailored to shopper preferences.
- Personalized promotions: Ospree Duty-Free / Voiceback Analytics at Mumbai T2 allows customers to scan a QR code and provide personal data for instant customized discounts. Voiceback’s dynamic promotion engine tailors offers based on shopping preferences and history.
- AI/AR-assisted shopping: Avolta / Perfect Corp at Heathrow, Stansted, Manchester, and Barcelona airports introduced AI/AR virtual try-on features that let travelers test beauty products before purchase.
8.4 The Pre-Planning Opportunity
Younger travelers are substantially more likely to plan duty-free purchases in advance — creating a clear opening for AI-powered pre-trip engagement.
Table 26: Tourists Who Pre-Plan Duty-Free Shopping (%)
| Segment | China | India |
|---|---|---|
| Gen Z | 87% | 92% |
| Millennials | 71% | 87% |
| Gen X & Baby Boomers | 73% | 86% |
| Total | 75% | 88% |
Source: Oliver Wyman China and India Tourist Surveys (2026).
With 75% of Chinese and 88% of Indian high-income tourists pre-planning duty-free purchases, the opportunity for AI-driven demand creation is enormous — from generating purchase intent during trip planning to guiding shoppers to the right store at the right time.
8.5 AI in the Travel Planning and Shopping Journey
Oliver Wyman envisions AI large language models (LLMs) embedded at every stage of the travel retail journey:
| Journey Stage | AI Application |
|---|---|
| Create demand | AI suggests relevant shopping opportunities during trip planning — e.g., “Your flight is delayed 2 hours; here’s what you can do at the airport.” |
| Create purchase intent | AI mines personal signals (occasions, budget, preferences) to suggest specific shopping goals — e.g., “Your husband’s birthday is coming up; here are curated gift ideas available at the terminal.” |
| Link brands/products to intent | AI maps purchase intent to specific brands and SKUs with product information — e.g., whisky recommendations with tasting notes, price, and availability. |
| Facilitate the shopping journey | AI guides travelers to the right store and gate, with real-time inventory and navigation — e.g., “You’re at Gate 67; the nearest store with this product is Duty Zero by cdf, closing at midnight.” |
Source: Gemini AI, Oliver Wyman analysis.
To capture this opportunity, travel retailers and brands must focus on three dimensions:
- Shopping purpose and rationale: Create AI-readable purchase reasons (e.g., “post-flight skincare repair,” “gifts under $50”) with structured data including price, reviews, packaging size, and pickup location.
- Structured taxonomy: Sync product attributes comprehensively across Google, retailer apps, airline apps, airport shopping platforms, and AI search summaries — categorized by travel purpose, destination, climate, traveler profile, price range, gifting attributes, and packaging convenience.
- Real-time retail: Provide real-time terminal-level inventory, order-and-pick-up functionality, lounge delivery, and loyalty-point payment options at the SKU level.
Part 9: Strategic Imperatives for 2026 and Beyond
The report concludes with a framework of three strategic imperatives for travel retail stakeholders:
1. Reinvent the Value Proposition
- What are the emerging needs of existing and new customer segments? What value propositions will attract them?
- How to evolve from price-driven attraction to “give travelers a real reason to shop at duty-free”?
2. Reimagine Products and Services
- How to design product and service offerings that deliver “money-can’t-buy” value and experiences?
- How can AI and data enable product personalization and improve conversion?
3. Optimize the Operating Model
- How to optimize the full traveler journey — pre-arrival, in-airport, and post-travel?
- What capabilities, partnerships, and ways of working are needed to test fast, learn continuously, and unlock the full potential of AI and innovation?
Key Takeaways: Data at a Glance
| Metric | Value |
|---|---|
| China high-income consumer confidence index (2026) | 115 (vs 71 in 2025, +62%) |
| Chinese outbound trips (2026E) | 155–165 million (vs ~140–150M in 2025) |
| China luxury spending net intent (2026) | +31% (vs -6% in 2025) |
| Top luxury spending category | Premium beauty: +37% net intent |
| China offshore luxury consumption share (2026E) | 25% (vs 55% in 2019) |
| Hainan duty-free YoY growth (Jan 2026) | +45% |
| India travel retail spending growth (2025–2035) | ~4× |
| India projected share of APAC travel retail growth (2025–2035) | 20% (vs 5% in 2015–2019) |
| Indian tourists pre-planning duty-free purchases | 88% |
| APAC travel retail sales gap vs 2019 | -18% (vs tourist arrivals -6%) |
| Revenue opportunity from closing the gap | ~USD 5 billion |
| Executives prioritizing innovation investment | 40% (vs 76% who see it as critical) |
| Firms planning customer-facing AI within 12 months | 65% (vs 20% deployed) |
| Personalization/CRM AI: planned vs deployed | 53% planned vs 7% deployed |
About the Report
Asia Pacific Travel Retail Trends Insight 2026 was jointly published by Oliver Wyman and the Tax Free World Association (TFWA). The report draws on quantitative surveys of Chinese and Indian high-income tourists (2022–2026), executive interviews with travel retail stakeholders, and proprietary Oliver Wyman analysis. Contributing authors include Jacky Lui, Waldemar Jap, Pedro Yip, Vincent Barbat, Christophe Chaix, and Kenneth Chow.
This article is a comprehensive independent analysis based on the Oliver Wyman–TFWA report. All data points and tables are sourced from the original report unless otherwise noted.
