According to PayNXT360, the quick commerce market in Asia Pacific is expected to grow by 27.6% annually, reaching US$155.5 billion by 2025. The quick commerce market in the region has experienced rob...
According to PayNXT360, the quick commerce market in Asia Pacific is expected to grow by 27.6% annually, reaching US$155.5 billion by 2025. The quick commerce market in the region has experienced robust growth during 2020-2024, achieving a CAGR of 23.0%. This upward trajectory is expected to continue, with the market forecast to grow at a CAGR of 29.2% from 2025 to 2029. By the end of 2029, the quick commerce market is projected to expand from its 2024 value of US$121.9 billion to approximately US$433.7 billion. Key Trends and Drivers 1. Anchor quick commerce growth around super-apps and platform ecosystems • Quick commerce in the Asia Pacific is increasingly embedded within large platform ecosystems rather than operating independently. In China, instant retail has become a major battleground between platforms like Meituan and Alibaba (Taobao Shangou / Ele.me). China’s “instant retail” market reached approximately RMB 780 billion in 2024, accounting for roughly 6% of online retail of physical goods, and continues to grow as both players push for 30-minute delivery of groceries and general merchandise. • In India, quick commerce is led by Blinkit (within Zomato), Zepto, and Swiggy Instamart, which deliver groceries and daily essentials in 10–20 minutes from dense dark-store networks. Reuters reports that quick commerce already accounts for about two-thirds of India’s e-grocery orders and US$6–7 billion in GMV in 2024. In Southeast Asia, super-apps like Grab integrate grocery and convenience delivery services alongside mobility and payments. Grab’s on-demand verticals (including GrabMart) delivered 19% year-over-year growth in GMV in April–May 2025, underscoring how grocery/essentials are now part of a broader super-app usage habit. • The Asia Pacific accounts for more than half of global ecommerce revenue (approximately 57% in 2024), with China, South Korea, and rapidly growing India leading the penetration. Super-apps have a large, digitally native user base to cross-sell quick-commerce use cases. Strong mobile connectivity is foundational: the GSMA estimates that mobile technologies generated US$950 billion of economic value in the Asia Pacific in 2024 (5.6% of GDP), with continued 5G and network investment, making app-based instant retail ubiquitous in major cities. • Platforms are leveraging existing food-delivery and ride-hailing logistics fleets, merchant relationships, and wallets to add higher-frequency grocery missions with relatively low marginal cost. Platform-centric quick commerce is likely to intensify across China, India, and Southeast Asia, with more super-apps adding or scaling grocery/instant retail as a core vertical and expanding to second-tier cities where economics permit. • Competitive intensity will remain high. In China, regulators are already concerned about aggressive discounting and price wars among instant-commerce platforms and have warned of deflationary risks. This suggests the need for more oversight on pricing and promotional tactics. • Over the next 2–4 years, this trend is expected to result in a smaller set of huge ecosystem players dominating discovery, payments, and logistics for quick commerce in the region, while smaller standalone apps struggle to match their scale and cross-subsidize their operations. 2. Shift fulfilment into retailers’ and convenience chains’ own networks • Traditional grocery and convenience retailers are building or integrating rapid-delivery capabilities into their own store and warehouse networks, rather than leaving this space entirely to platforms. • In Australia, Woolworths has integrated the MILKRUN brand into its ecosystem; by late 2024, MILKRUN (now under Woolworths) had expanded to more than 2,500 suburbs and entered a licensing partnership with Endeavour Group’s Jimmy Brings, bringing its liquor assortment onto the same rapid-delivery platform. • In Japan, convenience chains such as Lawson and 7-Eleven are utilizing their extensive store networks to facilitate rapid delivery. Recent corporate communications highlight Lawson’s home-delivery services, which offer thousands of SKUs and delivery in as little as 15 minutes in select areas. In contrast, Seven & i’s 7NOW service links real-time store inventory to 30-minute delivery in thousands of outlets. • In Southeast Asia, Grab has been acquiring and partnering with supermarket chains such as Jaya Grocer in Malaysia and Everrise in East Malaysia to digitise their stores and offer on-demand grocery delivery through Grab’s app, blending retail and platform models. • Retailers view quick commerce as both a defensive and offensive response to e-commerce penetration. Online grocery accounts for a small share of total grocery sales in many APAC markets, but it is growing rapidly and could erode in-store trips if retailers do not participate. • Store-based fulfillment and dark stores give retailers direct control over assortment, pricing, and private-label promotion, and help them utilize existing real estate more efficiently (e.g., using off-peak store capacity for picking and delivery). Partnerships with platforms enable retailers to expand their digital reach without developing comprehensive logistics and consumer-facing apps from scratch, while still protecting their brands and supply chains. • Expect to see more hybrid models in markets such as Japan, Australia, Singapore, Malaysia, and Indonesia, where retailers continue to utilize both their own apps and third-party platforms for instant delivery. Retailers will tighten integration between physical stores, dark stores, and online front-ends, making “order from the nearest store and deliver in under 60 minutes” a standard urban service rather than a niche offering. • Over time, this will rebalance bargaining power away from pure platforms towards large chains, especially where grocery and convenience retailers control the majority of local supply and can negotiate preferred terms or exclusivities. 3. Reset quick commerce models around sustainable economics and policy constraints • The region is shifting from “growth at any cost” and 10-minute delivery promises towards more economically disciplined models, focusing on 20–30-minute delivery, higher average order values, and a clearer path to profitability. • In India, a Bain/Flipkart analysis cited by Reuters shows that quick commerce already accounts for one-tenth of e-retail spending, but still faces questions over profitability, particularly beyond major metropolitan areas. Zomato’s Eternal has reported strong revenue growth driven by Blinkit, but net profit volatility underscores the investment burden of rapid store ramp-ups. • In China, the collapse of pandemic-era community group-buying models and the pivot to instant retail demonstrate how unprofitable formats are being phased out while capital is redeployed into more scalable models. Wired reports that many group-buying platforms have shut operations as consumers switch to 30-minute delivery services. • Governments and regulators are increasingly alert to pricing and labour practices. Chinese authorities have flagged that deep discounting and subsidies in instant retail can contribute to deflation and distort competition. • Higher interest rates and tighter funding conditions have reduced appetite for sustained cash burn. New capital rounds, such as Zepto’s recent US$450 million fundraise at a US$7 billion valuation, are now explicitly tied to demonstrating clearer unit economics rather than pure GMV growth. As e-commerce penetration in APAC rises, online growth is shifting from new user acquisition to frequency and basket expansion. This makes profitability and operational efficiency central to investor expectations. • Labour and urban planning concerns such as rider safety, gig worker conditions, dark store zoning, and traffic congestion are prompting more scrutiny from city governments, particularly in dense Asian metropolitan areas. • Consolidation is likely to accelerate in markets such as India, China, Australia, and Japan, with weaker operators exiting or being acquired by larger platforms or retailers that can absorb fixed costs and negotiate better terms with suppliers. Service promises are likely to stabilize around 20–30 minute delivery or 1-hour windows, with ultra-fast 10-minute delivery reserved for dense catchments and high-value customer segments where economics support it. • Profitability metrics, including contribution margin per order, dark-store productivity, and rider utilization, will become key focus areas for management and investors, shaping decisions on geographic expansion, category mix, and fee structures. 4. Turn quick commerce into multi-category, retail-media, and data-driven ecosystems • Quick commerce platforms across the APAC region are expanding beyond groceries into electronics, beauty, home care, and small appliances, while simultaneously building advertising and retail-media businesses on top of their high-frequency traffic. In India, Reuters notes that Zepto now offers more than 45,000 products, including electronics and apparel, while Blinkit is increasingly used for non-grocery missions such as small devices and accessories. • Media and industry coverage indicate that Zepto’s in-house ad engine and Blinkit’s advertising business are each tracking towards roughly ₹1,000 crore in annual ad revenues, with platforms like Blinkit, Zepto, and Instamart collectively estimated to generate ₹3,000–3,500 crore of ad revenue as brands shift their budgets into quick-commerce retail media. In China, Meituan’s instant retail business has scaled to around 120 million daily delivery orders across food and non-food services, giving it a large data and ad-product surface for merchants. • Platforms and super-apps like Grab are also emphasizing data-driven merchant tools and AI assistants that help small merchants manage catalogs, pricing, and campaigns, turning quick commerce into an SME enablement layer as well as a consumer channel. • Groceries and daily essentials generate high-frequency usage and rich first-party transaction data, making them ideal inputs for performance-based advertising. Media reports from India highlight that FMCG and D2C brands are allocating 15–20% of their digital ad budgets to retail-media and quick-commerce channels, drawn by stronger conversion rates and closed-loop measurement. As competition compresses product-level margins, platforms are seeking to diversify their revenue streams into higher-margin areas, such as ads, sponsored listings, subscription programs, and financial services. • Broader ecommerce in APAC is maturing towards ecosystem plays, in which payments, logistics, media, and financial services are tightly integrated, and quick commerce is a natural high-frequency anchor within that ecosystem. Quick commerce in India, China, Southeast Asia, and developed APAC markets, such as Japan and Australia, is likely to evolve into a multi-category “instant retail” layer, where groceries remain the foundation. Still, higher-margin categories (electronics, accessories, beauty, OTC pharma, and premium beverages) grow their share of GMV. • Advertising and retail-media revenue will become a core profit driver, with platforms acting as gatekeepers for brand visibility at the digital shelf and using granular data to sell targeted placements. This shift will deepen the interdependence between brands and quick-commerce platforms, potentially prompting scrutiny from regulators and competition authorities regarding data use and platform power. Competitive Landscape: Over the next 2–4 years, the competitive landscape is likely to evolve into fewer, stronger players rather than many small ones. In markets like India, consolidation will continue as weaker players exit or are absorbed, and the focus shifts from pure growth to unit economics, profitability, and retention. In Southeast Asia, given an earlier stage, we may see platforms expand beyond top metros into tier-2/3 cities, and investment will tilt towards operational efficiency, lower delivery promise ceilings (e.g., 20–30 minutes rather than 10 minutes everywhere), and new revenue streams (advertising, subscriptions). Competitive intensity will remain high, but the battle will shift from just speed to cost, differentiation, category breadth, and platform leverage. Further, regulatory and labour-cost pressures may force the exit of heavily subsidized players. Current State of the Market • In the Asia-Pacific region, quick commerce (q-commerce) has transitioned from early experimentation to intense competitive deployment in major metropolitan areas. In India, for example, q-commerce is now described as “no longer an experiment but a core layer of consumer infrastructure”. • Established players are scaling dark-store networks, optimising fulfilment, and expanding into new categories beyond basic groceries. Meanwhile, in Southeast Asia, the model is less advanced than in India but is gaining traction through ride-hailing / super-app platforms. The market is marked by multiple players racing to build urban fulfilment density, while dealing with cost and regulatory headwinds. Key Players and New Entrants • In India, the competitive front-runners include Blinkit (now part of Eternal Limited), which is estimated to hold approximately 44% of the q-commerce market in FY25. Zepto, with roughly 30%, and Swiggy Instamart, with about 23%. In Southeast Asia, super-apps are key players; for example, Grab’s GrabMart is reported to have a share of over 35% in quick-commerce in some key locales. • New entrants and adjacent incumbents are also entering the market. Global e-commerce giants like Amazon are conducting ultra-fast grocery pilots in India and elsewhere. Thus, the competitive set is broad, including dark-store pureplays, food-delivery platforms moving into q-commerce, building retailers, and general e-commerce players experimenting. Recent Launches, Mergers, and Acquisitions • Significant transactions and launches are shaping the landscape. In India, Blinkit’s acquisition by Zomato (now Eternal) is a foundational consolidation. In India’s q-commerce space, acquisition-led scale is one route. At the same time, some large retailers (such as Reliance Retail) have chosen organic dark-store roll-outs rather than acquiring existing players. • In Southeast Asia, key launches include GrabMart’s expanded fresh product campaign in Thailand and an increase in the scale of merchant partners. These moves reflect both consolidation among major players and the increasing expansion of fulfillment and merchant ecosystems. This report provides a detailed data-centric analysis of the quick commerce industry in Asia Pacific offering comprehensive coverage of both overall and quick commerce markets. It includes more than 100+ KPIs, covering gross merchandise value, gross merchandise volume, average order value, and order frequency. The report offers an in-depth analysis of quick commerce, including product type, payment mode, age group, location tier, business model, and delivery time. It further categorizes the market by revenue streams (advertising, delivery fee, and subscription-based models). In addition, the analysis captures consumer demographics by age and location alongside behavioral indicators such as subscription uptake and average delivery time. Collectively, these datasets provide a comprehensive view of market size, consumer behavior, and operational efficiency within the quick commerce ecosystem. PayNXT360 research methodology is based on industry best practices. Its unbiased analysis leverages a proprietary analytics platform to deliver a detailed view of market performance, structural trends, and growth dynamics across the quick commerce ecosystem, with a primary focus on both overall and instant delivery markets. This title from PayNXT360 is a bundled offering, combining the following 14 reports, covering 1,450+ tables and 1,600+ figures: 1. Asia Pacific Overall and Quick Commerce Market Business and Investment Opportunities Databook 2. Australia Overall and Quick Commerce Market Business and Investment Opportunities Databook 3. Bangladesh Overall and Quick Commerce Market Business and Investment Opportunities Databook 4. China Overall and Quick Commerce Market Business and Investment Opportunities Databook 5. India Overall and Quick Commerce Market Business and Investment Opportunities Databook 6. Indonesia Overall and Quick Commerce Market Business and Investment Opportunities Databook 7. Japan Overall and Quick Commerce Market Business and Investment Opportunities Databook 8. Malaysia Overall and Quick Commerce Market Business and Investment Opportunities Databook 9. Philippines Overall and Quick Commerce Market Business and Investment Opportunities Databook 10. Singapore Overall and Quick Commerce Market Business and Investment Opportunities Databook 11. South Korea Overall and Quick Commerce Market Business and Investment Opportunities Databook 12. Taiwan Overall and Quick Commerce Market Business and Investment Opportunities Databook 13. Thailand Overall and Quick Commerce Market Business and Investment Opportunities Databook 14. Vietnam Overall and Quick Commerce Market Business and Investment Opportunities Databook
This report provides a detailed data-driven analysis of the quick commerce market focusing on the rapid delivery ecosystem and its growth trajectory. It examines key market segments, operational models, and consumer behavior shaping the evolution of instant delivery services: • Quick Commerce Market Size and Growth Dynamics -- Gross Merchandise Value -- Gross Merchandise Volume -- Average Order Value -- Order Frequency per Year • Quick Commerce Market Segmentation by Product Type -- Groceries and Staples -- Fruits and Vegetables -- Snacks and Beverages -- Personal Care and Hygiene -- Pharmaceuticals and Health Products -- Home Décor -- Clothing and Accessories -- Electronics -- Others • Quick Commerce Market Segmentation by Payment Mode -- Instant Bank Transfer -- Wallets and Digital Payments -- Credit and Debit Cards -- Cash on Delivery • Quick Commerce Market Segmentation by Age Group -- Gen Z (15–25) -- Millennials (26–39) -- Gen X (40–55) -- Baby Boomers (Above 55) • Quick Commerce Market Segmentation by Location Tier -- Tier 1 Cities -- Tier 2 Cities -- Tier 3 Cities • Quick Commerce Market Segmentation by Business Model -- Inventory-led Model -- Hyper-local Model -- Multi-vendor Platform Model -- Others • Quick Commerce Market Segmentation by Delivery Time -- Delivery in 30 Minutes -- Delivery 30–60 Minutes -- Delivery in 3 Hours • Quick Commerce Consumer Behavior and Demographics -- Average Subscription Uptake by Age Group -- Average Subscription Uptake by Location Tier -- Average Subscription Uptake -- Average Delivery Time • Quick Commerce Revenue Structure and Composition -- Advertising Revenue -- Delivery Fee Revenue -- Subscription Revenue • Quick Commerce Operational Metrics by Product Type -- Gross Merchandise Value by Product Type -- Gross Merchandise Volume by Product Type -- Average Order Value by Product Type -- Order Frequency by Product Type • Quick Commerce Operational Metrics by Payment Mode -- Gross Merchandise Value by Payment Mode -- Gross Merchandise Volume by Payment Mode -- Average Order Value by Payment Mode • Quick Commerce Operational Metrics by Age Group -- Gross Merchandise Value by Age Group -- Gross Merchandise Volume by Age Group -- Average Order Value by Age Group • Quick Commerce Operational Metrics by Location Tier -- Gross Merchandise Value by Location Tier -- Gross Merchandise Volume by Location Tier -- Average Order Value by Location Tier -- Order Frequency by Location Tier • Quick Commerce Operational Metrics by Business Model -- Gross Merchandise Value by Business Model -- Gross Merchandise Volume by Business Model -- Average Order Value by Business Model • Quick Commerce Operational Metrics by Delivery Time -- Gross Merchandise Value by Delivery Time -- Gross Merchandise Volume by Delivery Time -- Average Order Value by Delivery Time -- Order Frequency by Delivery Time
• Comprehensive Market Intelligence: Gain a holistic understanding of the overall quick commerce with detailed operational metrics such as gross merchandise value, gross merchandise volume, average order value, and order frequency across key product categories. • Granular Segmentation and Cross-Analysis: Explore the fast-growing quick commerce ecosystem through detailed segmentation by product type, payment mode, age group, location tier, business model, and delivery time, providing data into evolving consumer behavior and purchasing dynamics. • Consumer Behavior and Ecosystem Readiness: Understand how demographics and payment method adoption are shaping consumer preferences and driving the expansion of instant delivery services in both urban and semi-urban markets. • Data-Driven Forecasts and KPI Tracking: Access a comprehensive dataset of 100+ key performance indicators (KPIs) with historical and forecast data through 2029, offering visibility into growth drivers, market trends, and investment opportunities across the quick commerce sector. • Decision-Ready Databook Format: Presented in a structured, data-centric format compatible with analytical and financial modeling, the Databook enables quick commerce companies, retailers, investors, and logistics partners to make informed, evidence-based strategic decisions.
This title from PayNXT360 is a bundled offering, combining the following 14 reports, covering 1450+ tables and 1,600+ figures: 1. Asia Pacific Overall and Quick Commerce Market Business and Investment Opportunities Databook 2. Australia Overall and Quick Commerce Market Business and Investment Opportunities Databook 3. Bangladesh Overall and Quick Commerce Market Business and Investment Opportunities Databook 4. China Overall and Quick Commerce Market Business and Investment Opportunities Databook 5. India Overall and Quick Commerce Market Business and Investment Opportunities Databook 6. Indonesia Overall and Quick Commerce Market Business and Investment Opportunities Databook 7. Japan Overall and Quick Commerce Market Business and Investment Opportunities Databook 8. Malaysia Overall and Quick Commerce Market Business and Investment Opportunities Databook 9. Philippines Overall and Quick Commerce Market Business and Investment Opportunities Databook 10. Singapore Overall and Quick Commerce Market Business and Investment Opportunities Databook 11. South Korea Overall and Quick Commerce Market Business and Investment Opportunities Databook 12. Taiwan Overall and Quick Commerce Market Business and Investment Opportunities Databook 13. Thailand Overall and Quick Commerce Market Business and Investment Opportunities Databook 14. Vietnam Overall and Quick Commerce Market Business and Investment Opportunities Databook All global, regional, and country reports mentioned above will have the following tables of contents: 1. About this Report 1.1 Summary 1.2 Methodology 1.3 Definitions 1.4 Disclaimer 2. Quick Commerce Industry Attractiveness 2.1 Quick Commerce – Gross Merchandise Value Trend Analysis, 2020-2029 2.2 Quick Commerce – Gross Merchandise Volume Trend Analysis, 2020-2029 2.3 Quick Commerce – Average Order Value Trend Analysis, 2020-2029 2.4 Quick Commerce – Order Frequency Trend Analysis, 2020-2029 2.5 Quick Commerce – Market Share Analysis by Key Players, 2024 3. Quick Commerce Operational KPIs 3.1 Quick Commerce Revenue and Growth Trend, 2020-2029 3.2 Quick Commerce Revenue Structure, Composition, and Growth Analysis by Segment, 2024 3.2.1 Advertising Revenue, 2020-2029 3.2.2 Delivery Fee Revenue, 2020-2029 3.2.3 Subscription Revenue, 2020-2029 4. Quick Commerce Analysis by Product Type 4.1 Quick Commerce Segment Share by Product Type, 2024 4.2 Quick Commerce Analysis by Groceries & Staples: Market Size and Forecast, 2020-2029 4.2.1 Groceries & Staples- Gross Merchandise Value Trend Analysis, 2020-2029 4.2.2 Groceries & Staples- Gross Merchandise Volume Trend Analysis, 2020-2029 4.2.3 Groceries & Staples- Average Order Value Trend Analysis, 2020-2029 4.2.4 Groceries & Staples- Order Frequency Trend Analysis, 2020-2029 4.3 Quick Commerce Analysis by Fruits & Vegetables: Market Size and Forecast, 2020-2029 4.3.1 Fruits & Vegetables- Gross Merchandise Value Trend Analysis, 2020-2029 4.3.2 Fruits & Vegetables- Gross Merchandise Volume Trend Analysis, 2020-2029 4.3.3 Fruits & Vegetables- Average Order Value Trend Analysis, 2020-2029 4.3.4 Fruits & Vegetables- Order Frequency Trend Analysis, 2020-2029 4.4 Quick Commerce Analysis by Snacks & Beverages: Market Size and Forecast, 2020-2029 4.4.1 Snacks & Beverages- Gross Merchandise Value Trend Analysis, 2020-2029 4.4.2 Snacks & Beverages- Gross Merchandise Volume Trend Analysis, 2020-2029 4.4.3 Snacks & Beverages- Average Order Value Trend Analysis, 2020-2029 4.4.4 Snacks & Beverages- Order Frequency Trend Analysis, 2020-2029 4.5 Quick Commerce Analysis by Personal Care & Hygiene: Market Size and Forecast, 2020-2029 4.5.1 Personal Care & Hygiene- Gross Merchandise Value Trend Analysis, 2020-2029 4.5.2 Personal Care & Hygiene- Gross Merchandise Volume Trend Analysis, 2020-2029 4.5.3 Personal Care & Hygiene- Average Order Value Trend Analysis, 2020-2029 4.5.4 Personal Care & Hygiene- Order Frequency Trend Analysis, 2020-2029 4.6 Quick Commerce Analysis by Pharmaceuticals & Health Products: Market Size and Forecast, 2020-2029 4.6.1 Pharmaceuticals & Health Products- Gross Merchandise Value Trend Analysis, 2020-2029 4.6.2 Pharmaceuticals & Health Products- Gross Merchandise Volume Trend Analysis, 2020-2029 4.6.3 Pharmaceuticals & Health Products- Average Order Value Trend Analysis, 2020-2029 4.6.4 Pharmaceuticals & Health Products- Order Frequency Trend Analysis, 2020-2029 4.7 Quick Commerce Analysis by Home Décor: Market Size and Forecast, 2020-2029 4.7.1 Home Décor- Gross Merchandise Value Trend Analysis, 2020-2029 4.7.2 Home Décor- Gross Merchandise Volume Trend Analysis, 2020-2029 4.7.3 Home Décor- Average Order Value Trend Analysis, 2020-2029 4.7.4 Home Décor- Order Frequency Trend Analysis, 2020-2029 4.8 Quick Commerce Analysis by Clothing & Accessories: Market Size and Forecast, 2020-2029 4.8.1 Clothing & Accessories- Gross Merchandise Value Trend Analysis, 2020-2029 4.8.2 Clothing & Accessories- Gross Merchandise Volume Trend Analysis, 2020-2029 4.8.3 Clothing & Accessories- Average Order Value Trend Analysis, 2020-2029 4.8.4 Clothing & Accessories- Order Frequency Trend Analysis, 2020-2029 4.9 Quick Commerce Analysis by Electronics: Market Size and Forecast, 2020-2029 4.9.1 Electronics- Gross Merchandise Value Trend Analysis, 2020-2029 4.9.2 Electronics- Gross Merchandise Volume Trend Analysis, 2020-2029 4.9.3 Electronics- Average Order Value Trend Analysis, 2020-2029 4.9.4 Electronics- Order Frequency Trend Analysis, 2020-2029 4.10 Quick Commerce Analysis by Other Product Category: Market Size and Forecast, 2020-2029 4.10.1 Other Product Category- Gross Merchandise Value Trend Analysis, 2020-2029 4.10.2 Other Product Category- Gross Merchandise Volume Trend Analysis, 2020-2029 4.10.3 Other Product Category- Average Order Value Trend Analysis, 2020-2029 4.10.4 Other Product Category- Order Frequency Trend Analysis, 2020-2029 5. Quick Commerce Analysis by Payment Method 5.1 Quick Commerce Segment Share by Payment Method, 2020-2029 5.2 Quick Commerce Analysis by Instant Bank Transfer: Market Size and Forecast, 2020-2029 5.2.1 Instant Bank Transfer- Gross Merchandise Value Trend Analysis, 2020-2029 5.2.2 Instant Bank Transfer- Gross Merchandise Volume Trend Analysis, 2020-2029 5.2.3 Instant Bank Transfer- Average Order Value Trend Analysis, 2020-2029 5.3 Quick Commerce Analysis by Wallets & Digital Payments: Market Size and Forecast, 2020-2029 5.3.1 Wallets & Digital Payments- Gross Merchandise Value Trend Analysis, 2020-2029 5.3.2 Wallets & Digital Payments- Gross Merchandise Volume Trend Analysis, 2020-2029 5.3.3 Wallets & Digital Payments- Average Order Value Trend Analysis, 2020-2029 5.4 Quick Commerce Analysis by Credit & Debit Cards: Market Size and Forecast, 2020-2029 5.4.1 Credit & Debit Cards- Gross Merchandise Value Trend Analysis, 2020-2029 5.4.2 Credit & Debit Cards- Gross Merchandise Volume Trend Analysis, 2020-2029 5.4.3 Credit & Debit Cards- Average Order Value Trend Analysis, 2020-2029 5.5 Quick Commerce Analysis by Cash on Delivery: Market Size and Forecast, 2020-2029 5.5.1 Cash on Delivery- Gross Merchandise Value Trend Analysis, 2020-2029 5.5.2 Cash on Delivery- Gross Merchandise Volume Trend Analysis, 2020-2029 5.5.3 Cash on Delivery- Average Order Value Trend Analysis, 2020-2029 6. Quick Commerce Analysis by Age Group 6.1 Quick Commerce Segment Share by Age Group, 2024 6.2 Quick Commerce Analysis by Gen Z (15–25) Age Group: Market Size and Forecast, 2020-2029 6.2.1 Gen Z (15–25) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.2.2 Gen Z (15–25) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.2.3 Gen Z (15–25) Age Group- Average Order Value Trend Analysis, 2020-2029 6.3 Quick Commerce Analysis by Millennials (26–39) Age Group: Market Size and Forecast, 2020-2029 6.3.1 Millennials (26–39) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.3.2 Millennials (26–39) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.3.3 Millennials (26–39) Age Group- Average Order Value Trend Analysis, 2020-2029 6.4 Quick Commerce Analysis by Gen X (40–55) Age Group: Market Size and Forecast, 2020-2029 6.4.1 Gen X (40–55) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.4.2 Gen X (40–55) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.4.3 Gen X (40–55) Age Group- Average Order Value Trend Analysis, 2020-2029 6.5 Quick Commerce Analysis by Baby Boomers (Above 55+) Age Group: Market Size and Forecast, 2020-2029 6.5.1 Baby Boomers (Above 55+) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.5.2 Baby Boomers (Above 55+) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.5.3 Baby Boomers (Above 55+) Age Group- Average Order Value Trend Analysis, 2020-2029 7. Quick Commerce Analysis by Location 7.1 Quick Commerce Segment Share by Location, 2020-2029 7.2 Quick Commerce Analysis by Tier 1 Cities: Market Size and Forecast, 2020-2029 7.2.1 Tier 1 Cities- Gross Merchandise Value Trend Analysis, 2020-2029 7.2.2 Tier 1 Cities- Gross Merchandise Volume Trend Analysis, 2020-2029 7.2.3 Tier 1 Cities- Average Order Value Trend Analysis, 2020-2029 7.2.4 Tier 1 Cities- Order Frequency Trend Analysis, 2020-2029 7.3 Quick Commerce Analysis by Tier 2 Cities: Market Size and Forecast, 2020-2029 7.3.1 Tier 2 Cities- Gross Merchandise Value Trend Analysis, 2020-2029 7.3.2 Tier 2 Cities- Gross Merchandise Volume Trend Analysis, 2020-2029 7.3.3 Tier 2 Cities- Average Order Value Trend Analysis, 2020-2029 7.3.4 Tier 2 Cities- Order Frequency Trend Analysis, 2020-2029 7.4 Quick Commerce Analysis by Tier 3 Cities: Market Size and Forecast, 2020-2029 7.4.1 Tier 3 Cities- Gross Merchandise Value Trend Analysis, 2020-2029 7.4.2 Tier 3 Cities- Gross Merchandise Volume Trend Analysis, 2020-2029 7.4.3 Tier 3 Cities- Average Order Value Trend Analysis, 2020-2029 7.4.4 Tier 3 Cities- Order Frequency Trend Analysis, 2020-2029 8. Quick Commerce Analysis by Business Model 8.1 Quick Commerce Segment Share by Business Model, 2024 8.2 Quick Commerce Analysis by Inventory Model: Market Size and Forecast, 2020-2029 8.2.1 Inventory Model- Gross Merchandise Value Trend Analysis, 2020-2029 8.2.2 Inventory Model- Gross Merchandise Volume Trend Analysis, 2020-2029 8.2.3 Inventory Model- Average Order Value Trend Analysis, 2020-2029 8.3 Quick Commerce Analysis by Hyperlocal Model: Market Size and Forecast, 2020-2029 8.3.1 Hyperlocal Model- Gross Merchandise Value Trend Analysis, 2020-2029 8.3.2 Hyperlocal Model- Gross Merchandise Volume Trend Analysis, 2020-2029 8.3.3 Hyperlocal Model- Average Order Value Trend Analysis, 2020-2029 8.4 Quick Commerce Analysis by Multi-vendor Platform Model: Market Size and Forecast, 2020-2029 8.4.1 Multi-vendor Platform Model- Gross Merchandise Value Trend Analysis, 2020-2029 8.4.2 Multi-vendor Platform Model- Gross Merchandise Volume Trend Analysis, 2020-2029 8.4.3 Multi-vendor Platform Model- Average Order Value Trend Analysis, 2020-2029 8.5 Quick Commerce Analysis by Other Business Models: Market Size and Forecast, 2020-2029 8.5.1 Other Business Models- Gross Merchandise Value Trend Analysis, 2020-2029 8.5.2 Other Business Models- Gross Merchandise Volume Trend Analysis, 2020-2029 8.5.3 Other Business Models- Average Order Value Trend Analysis, 2020-2029 9. Quick Commerce Analysis by Delivery Time 9.1 Quick Commerce Segment Share by Delivery Time, 2020-2029 9.2 Quick Commerce Analysis by Delivery Time In 30 Minutes: Market Size and Forecast, 2020-2029 9.2.1 Delivery Time In 30 Minutes- Gross Merchandise Value Trend Analysis, 2020-2029 9.2.2 Delivery Time In 30 Minutes- Gross Merchandise Volume Trend Analysis, 2020-2029 9.2.3 Delivery Time In 30 Minutes- Average Order Value Trend Analysis, 2020-2029 9.2.4 Delivery Time In 30 Minutes- Order Frequency Trend Analysis, 2020-2029 9.3 Quick Commerce Analysis by Delivery Time 30–60 Minutes: Market Size and Forecast, 2020-2029 9.3.1 Delivery Time 30–60 Minutes- Gross Merchandise Value Trend Analysis, 2020-2029 9.3.2 Delivery Time 30–60 Minutes- Gross Merchandise Volume Trend Analysis, 2020-2029 9.3.3 Delivery Time 30–60 Minutes- Average Order Value Trend Analysis, 2020-2029 9.3.4 Delivery Time 30–60 Minutes- Order Frequency Trend Analysis, 2020-2029 9.4 Quick Commerce Analysis by Delivery Time In 3 Hours: Market Size and Forecast, 2020-2029 9.4.1 Delivery Time In 3 Hours- Gross Merchandise Value Trend Analysis, 2020-2029 9.4.2 Delivery Time In 3 Hours- Gross Merchandise Volume Trend Analysis, 2020-2029 9.4.3 Delivery Time In 3 Hours- Average Order Value Trend Analysis, 2020-2029 9.4.4 Delivery Time In 3 Hours- Order Frequency Trend Analysis, 2020-2029 10. Quick Commerce Consumer Behaviour and Adoption 10.1 Quick Commerce- Average Subscription Uptake, 2024 10.2 Quick Commerce- Average Subscription Uptake by Age Group, 2024 10.3 Quick Commerce- Average Subscription Uptake by Location, 2024 10.4 Quick Commerce- Average Delivery Time, 2024 11. Further Reading 11.1 About PayNXT360 11.2 Related Research
Table 1: Quick Commerce – Gross Merchandise Value (US$ Million), 2020–2029 Table 2: Quick Commerce – Gross Merchandise Volume (US$ Million), 2020 – 2029 Table 3: Quick Commerce – Average Order Value (US$ Million), 2020-2029 Table 4: Quick Commerce – Order Frequency (Orders per Year), 2020-2029 Table 5: Quick Commerce Revenue and Growth Trend (US$ Million), 2020-2029 Table 7: Advertising Revenue (US$ Million), 2020-2029 Table 8: Delivery Fee Revenue (US$ Million), 2020-2029 Table 9: Subscription Revenue (US$ Million), 2020-2029 Table 10: Groceries & Staples- Gross Merchandise Value (US$ Million), 2020-2029 Table 11: Groceries & Staples- Gross Merchandise Volume (US$ Million), 2020-2029 Table 12: Groceries & Staples- Average Order Value (US$ Million), 2020-2029 Table 13: Groceries & Staples- Order Frequency (Orders per Year), 2020-2029 Table 14: Fruits & Vegetables- Gross Merchandise Value (US$ Million), 2020-2029 Table 15: Fruits & Vegetables- Gross Merchandise Volume (US$ Million), 2020-2029 Table 16: Fruits & Vegetables- Average Order Value (US$ Million), 2020-2029 Table 17: Fruits & Vegetables- Order Frequency (Orders per Year), 2020-2029 Table 18: Snacks & Beverages- Gross Merchandise Value (US$ Million), 2020-2029 Table 19: Snacks & Beverages- Gross Merchandise Volume (US$ Million), 2020-2029 Table 20: Snacks & Beverages- Average Order Value (US$ Million), 2020-2029 Table 21: Snacks & Beverages- Order Frequency (Orders per Year), 2020-2029 Table 22: Personal Care & Hygiene- Gross Merchandise Value (US$ Million), 2020-2029 Table 23: Personal Care & Hygiene- Gross Merchandise Volume (US$ Million), 2020-2029 Table 24: Personal Care & Hygiene- Average Order Value (US$ Million), 2020-2029 Table 25: Personal Care & Hygiene- Order Frequency (Orders per Year), 2020-2029 Table 26: Pharmaceuticals & Health Products- Gross Merchandise Value (US$ Million), 2020-2029 Table 27: Pharmaceuticals & Health Products- Gross Merchandise Volume (US$ Million), 2020-2029 Table 28: Pharmaceuticals & Health Products- Average Order Value (US$ Million), 2020-2029 Table 29: Pharmaceuticals & Health Products- Order Frequency (Orders per Year), 2020-2029 Table 30: Home Décor- Gross Merchandise Value (US$ Million), 2020-2029 Table 31: Home Décor- Gross Merchandise Volume (US$ Million), 2020-2029 Table 32: Home Décor- Average Order Value (US$ Million), 2020-2029 Table 33: Home Décor- Order Frequency (Orders per Year), 2020-2029 Table 34: Clothing & Accessories- Gross Merchandise Value (US$ Million), 2020-2029 Table 35: Clothing & Accessories- Gross Merchandise Volume (US$ Million), 2020-2029 Table 36: Clothing & Accessories- Average Order Value (US$ Million), 2020-2029 Table 37: Clothing & Accessories- Order Frequency (Orders per Year), 2020-2029 Table 38: Electronics- Gross Merchandise Value (US$ Million), 2020-2029 Table 39: Electronics- Gross Merchandise Volume (US$ Million), 2020-2029 Table 40: Electronics- Average Order Value (US$ Million), 2020-2029 Table 41: Electronics- Order Frequency (Orders per Year), 2020-2029 Table 42: Others- Gross Merchandise Value (US$ Million), 2020-2029 Table 43: Others- Gross Merchandise Volume (US$ Million), 2020-2029 Table 44: Others- Average Order Value (US$ Million), 2020-2029 Table 45: Others- Order Frequency (Orders per Year), 2020-2029 Table 46: Instant Bank Transfer- Gross Merchandise Value (US$ Million), 2020-2029 Table 47: Instant Bank Transfer- Gross Merchandise Volume (US$ Million), 2020-2029 Table 48: Instant Bank Transfer- Average Order Value (US$ Million), 2020-2029 Table 49: Wallets & Digital Payments- Gross Merchandise Value (US$ Million), 2020-2029 Table 50: Wallets & Digital Payments- Gross Merchandise Volume (US$ Million), 2020-2029 Table 51: Wallets & Digital Payments- Average Order Value (US$ Million), 2020-2029 Table 52: Credit & Debit Card- Gross Merchandise Value (US$ Million), 2020-2029 Table 53: Credit & Debit Card- Gross Merchandise Volume (US$ Million), 2020-2029 Table 54: Credit & Debit Card- Average Order Value (US$ Million), 2020-2029 Table 55: Cash on Delivery- Gross Merchandise Value (US$ Million), 2020-2029 Table 56: Cash on Delivery- Gross Merchandise Volume (US$ Million), 2020-2029 Table 57: Cash on Delivery- Average Order Value (US$ Million), 2020-2029 Table 58: Gen Z (15–25) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 59: Gen Z (15–25) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Table 60: Gen Z (15–25) Age Group- Average Order Value (US$ Million), 2020-2029 Table 61: Millennials (26–39) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 62: Millennials (26–39) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Table 63: Millennials (26–39) Age Group- Average Order Value (US$ Million), 2020-2029 Table 64. Gen X (40–55) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 65: Gen X (40–55) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Table 66: Gen X (40–55) Age Group- Average Order Value (US$ Million), 2020-2029 Table 67: Baby Boomers (Above 55) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 68: Baby Boomers (Above 55) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Table 69: Baby Boomers (Above 55) Age Group- Average Order Value (US$ Million), 2020-2029 Table 70: Tier 1 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Table 71: Tier 1 Cities- Gross Merchandise Volume (US$ Million), 2020-2029 Table 72: Tier 1 Cities- Average Order Value (US$ Million), 2020-2029 Table 73: Tier 1 Cities- Order Frequency (Orders per Year), 2020-2029 Table 74: Tier 2 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Table 75: Tier 2 Cities- Gross Merchandise Volume (US$ Million), 2020-2029 Table 76: Tier 2 Cities- Average Order Value (US$ Million), 2020-2029 Table 77: Tier 2 Cities- Order Frequency (Orders per Year), 2020-2029 Table 78: Tier 3 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Table 79: Tier 3 Cities- Gross Merchandise Volume (US$ Million), 2020-2029 Table 80: Tier 3 Cities- Average Order Value (US$ Million), 2020-2029 Table 81: Tier 3 Cities- Order Frequency (Orders per Year), 2020-2029 Table 82: Inventory Model- Gross Merchandise Value (US$ Million), 2020-2029 Table 83: Inventory Model- Gross Merchandise Volume (US$ Million), 2020-2029 Table 84: Inventory Model- Average Order Value (US$ Million), 2020-2029 Table 85: Hyper-local Model- Gross Merchandise Value (US$ Million), 2020-2029 Table 86: Hyper-local Model- Gross Merchandise Volume (US$ Million), 2020-2029 Table 87: Hyper-local Model- Average Order Value (US$ Million), 2020-2029 Table 88: Multi-vendor Platform Model- Gross Merchandise Value (US$ Million), 2020-2029 Table 89: Multi-vendor Platform Model- Gross Merchandise Volume (US$ Million), 2020-2029 Table 90: Multi-vendor Platform Model- Average Order Value (US$ Million), 2020-2029 Table 91: Others- Gross Merchandise Value (US$ Million), 2020-2029 Table 92: Others- Gross Merchandise Volume (US$ Million), 2020-2029 Table 93: Others- Average Order Value (US$ Million), 2020-2029 Table 94: Delivery Time In 30 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Table 95: Delivery Time In 30 Minutes- Gross Merchandise Volume (US$ Million), 2020-2029 Table 96: Delivery Time In 30 Minutes- Average Order Value (US$ Million), 2020-2029 Table 97: Delivery Time In 30 Minutes- Order Frequency (Orders per Year), 2020-2029 Table 98: Delivery Time 30–60 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Table 99: Delivery Time 30–60 Minutes- Gross Merchandise Volume (US$ Million), 2020-2029 Table 100: Delivery Time 30–60 Minutes- Average Order Value (US$ Million), 2020-2029 Table 101: Delivery Time 30–60 Minutes- Order Frequency (Orders per Year), 2020-2029 Table 102: Delivery Time In 3 Hours- Gross Merchandise Value (US$ Million), 2020-2029 Table 103: Delivery Time In 3 Hours- Gross Merchandise Volume (US$ Million), 2020-2029 Table 104: Delivery Time In 3 Hours- Average Order Value (US$ Million), 2020-2029 Table 105: Delivery Time In 3 Hours- Order Frequency (Orders per Year), 2020-2029
Figure 1: PayNXT360’s Methodology Framework Figure 2: Quick Commerce – Gross Merchandise Value (US$ Million), 2020–2029 Figure 3: Quick Commerce – Gross Merchandise Volume (US$ Million), 2020 – 2029 Figure 4: Quick Commerce – Average Order Value (US$ Million), 2020-2029 Figure 5: Quick Commerce – Order Frequency (Orders per Year), 2020-2029 Figure 6: Quick Commerce – Market Share Analysis by Key Players (%), 2024 Figure 7: Quick Commerce Revenue and Growth Trend (US$ Million), 2020-2029 Figure 8: Revenue Structure, Composition, and Growth Analysis by Segment (US$ Million), 2024 Figure 9: Advertising Revenue (US$ Million), 2020-2029 Figure 10: Delivery Fee Revenue (US$ Million), 2020-2029 Figure 11: Subscription Revenue (US$ Million), 2020-2029 Figure 12: Groceries & Staples- Gross Merchandise Value (US$ Million), 2020-2029 Figure 13: Groceries & Staples- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 14: Groceries & Staples- Average Order Value (US$ Million), 2020-2029 Figure 15: Groceries & Staples- Order Frequency (Orders per Year), 2020-2029 Figure 16: Fruits & Vegetables- Gross Merchandise Value (US$ Million), 2020-2029 Figure 17: Fruits & Vegetables- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 18: Fruits & Vegetables- Average Order Value (US$ Million), 2020-2029 Figure 19: Fruits & Vegetables- Order Frequency (Orders per Year), 2020-2029 Figure 20: Snacks & Beverages- Gross Merchandise Value (US$ Million), 2020-2029 Figure 21: Snacks & Beverages- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 22: Snacks & Beverages- Average Order Value (US$ Million), 2020-2029 Figure 23: Snacks & Beverages- Order Frequency (Orders per Year), 2020-2029 Figure 24: Personal Care & Hygiene- Gross Merchandise Value (US$ Million), 2020-2029 Figure 25: Personal Care & Hygiene- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 26: Personal Care & Hygiene- Average Order Value (US$ Million), 2020-2029 Figure 27: Personal Care & Hygiene- Order Frequency (Orders per Year), 2020-2029 Figure 28: Pharmaceuticals & Health Products- Gross Merchandise Value (US$ Million), 2020-2029 Figure 29: Pharmaceuticals & Health Products- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 30: Pharmaceuticals & Health Products- Average Order Value (US$ Million), 2020-2029 Figure 31: Pharmaceuticals & Health Products- Order Frequency (Orders per Year), 2020-2029 Figure 32: Home Décor- Gross Merchandise Value (US$ Million), 2020-2029 Figure 33: Home Décor- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 34: Home Décor- Average Order Value (US$ Million), 2020-2029 Figure 35: Home Décor- Order Frequency (Orders per Year), 2020-2029 Figure 36: Clothing & Accessories- Gross Merchandise Value (US$ Million), 2020-2029 Figure 37: Clothing & Accessories- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 38: Clothing & Accessories- Average Order Value (US$ Million), 2020-2029 Figure 39: Clothing & Accessories- Order Frequency (Orders per Year), 2020-2029 Figure 40: Electronics- Gross Merchandise Value (US$ Million), 2020-2029 Figure 41: Electronics- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 42: Electronics- Average Order Value (US$ Million), 2020-2029 Figure 43: Electronics- Order Frequency (Orders per Year), 2020-2029 Figure 44: Others- Gross Merchandise Value (US$ Million), 2020-2029 Figure 45: Others- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 46: Others- Average Order Value (US$ Million), 2020-2029 Figure 47: Others- Order Frequency (Orders per Year), 2020-2029 Figure 48: Instant Bank Transfer- Gross Merchandise Value (US$ Million), 2020-2029 Figure 49: Instant Bank Transfer- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 50: Instant Bank Transfer- Average Order Value (US$ Million), 2020-2029 Figure 51: Wallets & Digital Payments- Gross Merchandise Value (US$ Million), 2020-2029 Figure 52: Wallets & Digital Payments- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 53: Wallets & Digital Payments- Average Order Value (US$ Million), 2020-2029 Figure 54: Credit & Debit Card- Gross Merchandise Value (US$ Million), 2020-2029 Figure 55: Credit & Debit Card- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 56: Credit & Debit Card- Average Order Value (US$ Million), 2020-2029 Figure 57: Cash on Delivery- Gross Merchandise Value (US$ Million), 2020-2029 Figure 58: Cash on Delivery- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 59: Cash on Delivery- Average Order Value (US$ Million), 2020-2029 Figure 60: Gen Z (15–25) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 61: Gen Z (15–25) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 62: Gen Z (15–25) Age Group- Average Order Value (US$ Million), 2020-2029 Figure 63: Millennials (26–39) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 64: Millennials (26–39) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 65: Millennials (26–39) Age Group- Average Order Value (US$ Million), 2020-2029 Figure 66: Gen X (40–55) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 67: Gen X (40–55) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 68: Gen X (40–55) Age Group- Average Order Value (US$ Million), 2020-2029 Figure 69: Baby Boomers (Above 55) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 70: Baby Boomers (Above 55) Age Group- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 71: Baby Boomers (Above 55) Age Group- Average Order Value (US$ Million), 2020-2029 Figure 72: Tier 1 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Figure 73: Tier 1 Cities- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 74: Tier 1 Cities- Average Order Value (US$ Million), 2020-2029 Figure 75: Tier 1 Cities- Order Frequency (Orders per Year), 2020-2029 Figure 76: Tier 2 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Figure 77: Tier 2 Cities- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 78: Tier 2 Cities- Average Order Value (US$ Million), 2020-2029 Figure 79: Tier 2 Cities- Order Frequency (Orders per Year), 2020-2029 Figure 80: Tier 3 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Figure 81: Tier 3 Cities- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 82: Tier 3 Cities- Average Order Value (US$ Million), 2020-2029 Figure 83: Tier 3 Cities- Order Frequency (Orders per Year), 2020-2029 Figure 84: Inventory Model- Gross Merchandise Value (US$ Million), 2020-2029 Figure 85: Inventory Model- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 86: Inventory Model- Average Order Value (US$ Million), 2020-2029 Figure 87: Hyper-local Model- Gross Merchandise Value (US$ Million), 2020-2029 Figure 88: Hyper-local Model- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 89: Hyper-local Model- Average Order Value (US$ Million), 2020-2029 Figure 90: Multi-vendor Platform Model- Gross Merchandise Value (US$ Million), 2020-2029 Figure 91: Multi-vendor Platform Model- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 92: Multi-vendor Platform Model- Average Order Value (US$ Million), 2020-2029 Figure 93: Others- Gross Merchandise Value (US$ Million), 2020-2029 Figure 94: Others- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 95: Others- Average Order Value (US$ Million), 2020-2029 Figure 96: Delivery Time In 30 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Figure 97: Delivery Time In 30 Minutes- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 98: Delivery Time In 30 Minutes- Average Order Value (US$ Million), 2020-2029 Figure 99: Delivery Time In 30 Minutes- Order Frequency (Orders per Year), 2020-2029 Figure 100: Delivery Time 30–60 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Figure 101: Delivery Time 30–60 Minutes- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 102: Delivery Time 30–60 Minutes- Average Order Value (US$ Million), 2020-2029 Figure 103: Delivery Time 30–60 Minutes- Order Frequency (Orders per Year), 2020-2029 Figure 104: Delivery Time In 3 Hours- Gross Merchandise Value (US$ Million), 2020-2029 Figure 105: Delivery Time In 3 Hours- Gross Merchandise Volume (US$ Million), 2020-2029 Figure 106: Delivery Time In 3 Hours- Average Order Value (US$ Million), 2020-2029 Figure 107: Delivery Time In 3 Hours- Order Frequency (Orders per Year), 2020-2029 Figure 108: Quick Commerce – Market Share Analysis by Key Players (%), 2024 Figure 109: Quick Commerce- Age Group Average Subscription Uptake (%), 2024 Figure 110: Quick Commerce- Location Average Subscription Uptake (%), 2024 Figure 111: Tier 3 Cities- Average Subscription Uptake (%), 2025
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