According to PayNXT360, the quick commerce market in Germany is expected to grow by 8.9% annually, reaching US$4,613.4 million by 2025. The quick commerce market in the country has experienced robust...
According to PayNXT360, the quick commerce market in Germany is expected to grow by 8.9% annually, reaching US$4,613.4 million by 2025. The quick commerce market in the country has experienced robust growth during 2020-2024, achieving a CAGR of 8.3%. This upward trajectory is expected to continue, with the market forecast to grow at a CAGR of 8.6% from 2025 to 2029. By the end of 2029, the quick commerce market is projected to expand from its 2024 value of US$4,236.0 million to approximately US$6,422.8 million. Key Trends & Drivers 1. Market consolidates around a few profitability-focused operators • Germany’s ultra-fast grocery market has moved from rapid expansion to consolidation. Early players, such as Getir and its acquired brand Gorillas, have exited Germany entirely, shutting down their local operations and focusing on other geographies. Flink has emerged as the primary dedicated quick-commerce specialist, focusing on Germany and the Netherlands, and securing new funding in 2024 while exiting less profitable markets, such as France and Austria. • The funding environment for loss-making delivery models has tightened, pushing investors and management to prioritise unit economics over pure growth. Flink now emphasizes break-even performance in its core markets and targets full profitability within a defined timeline, signaling a shift away from the “growth at any cost” approach. • At the same time, Germany’s broader e-grocery market is still growing steadily rather than explosively, giving operators time to optimise networks instead of chasing hyper-growth. Strategy& expects online grocery to grow at a mid-single-digit to high-single-digit annual rate in Germany through the middle of the decade, reinforcing a focus on sustainable economics. • Quick commerce in Germany is likely to be led by a small number of scaled platforms: one or two specialists (e.g., Flink) plus multi-vertical players embedded in food-delivery apps and retailer ecosystems. Expansion will focus on dense urban catchments, where high-order density and short delivery distances support profitable operations; coverage in smaller cities and rural areas will remain selective. • Competitive intensity will shift from “who can open the most dark stores” to “who can run the most efficient network and secure the strongest partnerships”. 2. Retailers embed quick commerce through platform partnerships • Instead of building standalone ultra-fast capabilities everywhere, large German grocers are increasingly using third-party platforms to offer rapid delivery. REWE has launched an express delivery service in partnership with Lieferando (Eat Takeaway), with delivery promised within well under an hour in multiple German cities. • Czech online grocer Rohlik, operating as Knuspr.de in Germany, has partnered with Amazon to make its assortment available to Prime customers, initially in Berlin and with plans to expand to more cities. • Grocers such as REWE and Knuspr want to extend reach and speed without assuming the full cost of building rider fleets, routing systems, and consumer-facing marketplaces. Partnering with platforms allows them to plug into existing demand, logistics, and technology. • Platforms like Lieferando and Amazon seek to increase order frequency and maximise utilisation of their delivery networks by adding grocery and convenience missions alongside restaurant orders and general e-commerce. This aligns with broader retail shifts toward omnichannel fulfilment and rapid delivery windows. • Quick commerce will become less about pure-play startups and more about how supermarket brands are surfaced inside marketplace apps. REWE-style tie-ups are likely to be replicated by other chains for regional and specialty formats. • Negotiating power will shift toward large retailers that can offer scale assortments and strong private-label ranges on platforms. Smaller q-commerce-only operators will need to differentiate themselves on assortment, speed, or service model to avoid being commoditized. For consumers, “who delivers” will matter less than “which supermarket do I see in my chosen app,” making digital shelf placement and data-sharing agreements strategically important. 3. Food-delivery platforms broaden into multi-vertical quick commerce • Food-delivery apps in Germany are evolving into multi-category commerce platforms that include groceries, household items, and other convenience products, offering rapid delivery promises. Lieferando explicitly markets grocery and convenience delivery alongside restaurant meals, including local supermarket partners in major cities such as Berlin. • Wolt positions itself as a local commerce platform delivering food and groceries in around half an hour, and has been expanding its non-restaurant offering in Germany as part of DoorDash’s broader European strategy. Uber Eats, while historically focused on restaurants, has been expanding its grocery and convenience partnerships in Europe and utilizing quick commerce tie-ups as a key part of its global growth narrative. • Restaurant delivery growth has slowed from pandemic highs, so platforms are seeking adjacent missions to keep riders busy throughout the day and improve route density. Groceries and convenience products offer recurring baskets and predictable peaks. • German consumers are increasingly expecting a single app to address multiple “need it now” use cases, such as dinner, forgotten ingredients, snacks, or small household items rather than managing separate apps for each category. Data from app analytics firms show that a handful of multi-vertical apps (Too Good To Go, Lieferando, Picnic, Uber Eats, Wolt) dominate the rankings in Germany, reinforcing the advantages of scale for discovery and engagement. • Quick commerce in Germany will increasingly be orchestrated through these multi-vertical “front doors”. Pure grocery players may rely on them for traffic or feel pressure to expand their own use cases. • Subscription programs, bundled delivery fees, and cross-category promotions will become increasingly important for retention, as platforms utilize grocery to deepen engagement with their existing food-delivery user base. For retailers and brands, the negotiation agenda will broaden from shelf space in physical stores to visibility in algorithmic search and promotional slots within these apps. 4. Operators tighten economics through labour and network optimisation • Q-commerce and food-delivery operators in Germany are restructuring their cost base and fulfilment models to achieve sustainable margins. Flink’s 2024 funding and communication explicitly highlight profitability by market, with investments channelled into densifying hubs and raising average order values rather than entering new countries. • Lieferando is reducing several thousand directly employed courier positions in Germany and shifting a portion of deliveries to external logistics partners, citing competitive pressure and the need for more flexible capacity. Getir’s decision to exit Germany underscores how quickly operators will now withdraw from markets that cannot reach sustainable scale or labour productivity. • Labour is a major cost driver in Germany’s last-mile delivery, and wage inflation, combined with regulatory scrutiny over platform work, is forcing companies to redesign their models. Outsourcing some routes to specialist logistics firms is seen as a way to variabilise costs and manage demand swings. • Dense urban networks, larger baskets, and better route planning are required to make 30–45 minute deliveries economically viable. This aligns with broader e-grocery trends where growth is steady but investors expect clear paths to profitability rather than persistent cash burn. • Service coverage is likely to become more varied, with central areas in major cities continuing to offer strong delivery performance, while smaller or less populated regions may experience longer delivery times, higher service fees, or a shift toward scheduled deliveries. • At the same time, labor frameworks are expected to evolve as EU-wide platform work regulations are implemented, pushing companies to balance flexibility for workers with regulatory compliance. While this could lead to higher operational costs, it may also promote greater standardization of labor practices across the sector. Overall, operational efficiency will be a key differentiator for platforms that can effectively align customer demand, courier availability, and store locations will hold a lasting competitive edge. Competitive Landscape Over the next two to four years, Germany’s quick commerce industry is likely to remain concentrated among a handful of major players embedded within broader retail and delivery ecosystems. Consolidation is expected to progress mainly through strategic partnerships rather than acquisitions, with operators prioritizing profitability, automation, and improved utilization of urban delivery networks. The market will stabilize as a sustainable, service-led segment of the broader e-grocery and delivery ecosystem. Current State of the Market • Germany’s quick commerce market has transitioned from a high-growth experimental phase to a consolidation-driven stage. After the rapid growth period of 2021–22, most operators have redirected their focus toward achieving profitability and enhancing operational efficiency. In 2024, Getir and its subsidiary Gorillas exited the German market, highlighting the difficulties created by duplicated networks and limited margins. • Flink continues to be the leading dedicated quick commerce provider, running a network of dark stores in major cities such as Berlin, Munich, and Hamburg. Traditional retailers, such as REWE and Edeka, have integrated express delivery into their omnichannel offerings through partnerships with delivery platforms, while delivery aggregators like Lieferando and Wolt are embedding grocery delivery within broader, multi-vertical ecosystems. Key Players and New Entrants • Flink and REWE now lead Germany’s urban quick commerce segment. Flink operates through an inventory-led model, while REWE leverages its wide retail footprint via platform partnerships. Meanwhile, Wolt (part of DoorDash) and Uber Eats are broadening their offerings beyond restaurant delivery to include grocery, convenience, and supermarket categories. • Knuspr.de, part of the Rohlik Group, has positioned itself as a premium online grocer focused on fresh produce and timed express deliveries. The market has seen limited new entrants, as increasing operational expenses and cautious investor sentiment have raised barriers to entry. Recent Launches, Mergers, and Acquisitions • A key development in 2024 was Getir’s complete withdrawal from the German market, including the closure of its Gorillas-branded operations. Flink secured new funding in mid-2024 to support operations and enhance its fulfillment technology, indicating investor emphasis on strengthening core markets. • REWE deepened its collaboration with Lieferando to expand rapid grocery delivery services, while Knuspr partnered with Amazon Prime to access a broader customer base. The market has seen limited merger and acquisition activity, reflecting a strategic shift toward partnerships and operational alliances rather than consolidation through M&A. This report provides a detailed data-centric analysis of the quick commerce industry in Germany 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’s research methodology is based on industry best practices. It's unbiased analysis leverages a proprietary analytics platform to offer a detailed view of emerging business and investment market opportunities.
This report provides a detailed data-driven analysis of the quick commerce market in Germany, 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: • Germany Quick Commerce Market Size and Growth Dynamics -- Gross Merchandise Value -- Gross Merchandise Volume -- Average Order Value -- Order Frequency per Year • Germany 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 • Germany Quick Commerce Market Segmentation by Payment Mode -- Instant Bank Transfer -- Wallets and Digital Payments -- Credit and Debit Cards -- Cash on Delivery • Germany Quick Commerce Market Segmentation by Age Group -- Gen Z (15–25) -- Millennials (26–39) -- Gen X (40–55) -- Baby Boomers (Above 55) • Germany Quick Commerce Market Segmentation by Location Tier -- Tier 1 Cities -- Tier 2 Cities -- Tier 3 Cities • Germany Quick Commerce Market Segmentation by Business Model -- Inventory-led Model -- Hyper-local Model -- Multi-vendor Platform Model -- Others • Germany Quick Commerce Market Segmentation by Delivery Time -- Delivery in 30 Minutes -- Delivery 30–60 Minutes -- Delivery in 3 Hours • Germany Quick Commerce Consumer Behavior and Demographics -- Average Subscription Uptake by Age Group -- Average Subscription Uptake by Location Tier -- Average Subscription Uptake -- Average Delivery Time • Germany Quick Commerce Revenue Structure and Composition -- Advertising Revenue -- Delivery Fee Revenue -- Subscription Revenue • Germany 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 • Germany 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 • Germany 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 • Germany 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 • Germany 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 • Germany 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.
1. About this Report 1.1 Summary 1.2 Methodology 1.3 Definitions 1.4 Disclaimer 2. Germany Quick Commerce Industry Attractiveness 2.1 Germany Quick Commerce – Gross Merchandise Value Trend Analysis, 2020-2029 2.2 Germany Quick Commerce – Gross Merchandise Volume Trend Analysis, 2020-2029 2.3 Germany Quick Commerce – Average Order Value Trend Analysis, 2020-2029 2.4 Germany Quick Commerce – Order Frequency Trend Analysis, 2020-2029 2.5 Germany Quick Commerce – Market Share Analysis by Key Players, 2024 3. Germany Quick Commerce Operational KPIs 3.1 Germany Quick Commerce Revenue and Growth Trend, 2020-2029 3.2 Germany 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. Germany Quick Commerce Analysis by Product Type 4.1 Germany Quick Commerce Segment Share by Product Type, 2024 4.2 Germany 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 Germany 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 Germany 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 Germany 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 Germany 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 Germany 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 Germany 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 Germany 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 Germany 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. Germany Quick Commerce Analysis by Payment Method 5.1 Germany Quick Commerce Segment Share by Payment Method, 2020-2029 5.2 Germany 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 Germany 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 Germany 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 Germany 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. Germany Quick Commerce Analysis by Age Group 6.1 Germany Quick Commerce Segment Share by Age Group, 2024 6.2 Germany 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 Germany 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 Germany 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 Germany 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. Germany Quick Commerce Analysis by Location 7.1 Germany Quick Commerce Segment Share by Location, 2020-2029 7.2 Germany 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 Germany 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 Germany 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. Germany Quick Commerce Analysis by Business Model 8.1 Germany Quick Commerce Segment Share by Business Model, 2024 8.2 Germany 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 Germany 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 Germany 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 Germany 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. Germany Quick Commerce Analysis by Delivery Time 9.1 Germany Quick Commerce Segment Share by Delivery Time, 2020-2029 9.2 Germany 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 Germany 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 Germany 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. Germany Quick Commerce Consumer Behaviour and Adoption 10.1 Germany Quick Commerce- Average Subscription Uptake, 2024 10.2 Germany Quick Commerce- Average Subscription Uptake by Age Group, 2024 10.3 Germany Quick Commerce- Average Subscription Uptake by Location, 2024 10.4 Germany Quick Commerce- Average Delivery Time, 2024 11. Further Reading 11.1 About PayNXT360 11.2 Related Research
Table 1: Germany Quick Commerce – Gross Merchandise Value (US$ Million), 2020–2029 Table 2: Germany Quick Commerce – Gross Merchandise Volume (Millions), 2020-2029 Table 3: Germany Quick Commerce – Average Order Value (US$), 2020-2029 Table 4: Germany Quick Commerce – Order Frequency (Orders per Year), 2020-2029 Table 5: Germany Quick Commerce Revenue and Growth Trend (US$ Million), 2020-2029 Table 6: Advertising Revenue (US$ Million), 2020-2029 Table 7: Delivery Fee Revenue (US$ Million), 2020-2029 Table 8: Subscription Revenue (US$ Million), 2020-2029 Table 9: Groceries & Staples- Gross Merchandise Value (US$ Million), 2020-2029 Table 10: Groceries & Staples- Gross Merchandise Volume (Millions), 2020-2029 Table 11: Groceries & Staples- Average Order Value (US$), 2020-2029 Table 12: Groceries & Staples- Order Frequency (Orders per Year), 2020-2029 Table 13: Fruits & Vegetables- Gross Merchandise Value (US$ Million), 2020-2029 Table 14: Fruits & Vegetables- Gross Merchandise Volume (Millions), 2020-2029 Table 15: Fruits & Vegetables- Average Order Value (US$), 2020-2029 Table 16: Fruits & Vegetables- Order Frequency (Orders per Year), 2020-2029 Table 17: Snacks & Beverages- Gross Merchandise Value (US$ Million), 2020-2029 Table 18: Snacks & Beverages- Gross Merchandise Volume (Millions), 2020-2029 Table 19: Snacks & Beverages- Average Order Value (US$), 2020-2029 Table 20: Snacks & Beverages- Order Frequency (Orders per Year), 2020-2029 Table 21: Personal Care & Hygiene- Gross Merchandise Value (US$ Million), 2020-2029 Table 22: Personal Care & Hygiene- Gross Merchandise Volume (Millions), 2020-2029 Table 23: Personal Care & Hygiene- Average Order Value (US$), 2020-2029 Table 24: Personal Care & Hygiene- Order Frequency (Orders per Year), 2020-2029 Table 25: Pharmaceuticals & Health Products- Gross Merchandise Value (US$ Million), 2020-2029 Table 26: Pharmaceuticals & Health Products- Gross Merchandise Volume (Millions), 2020-2029 Table 27: Pharmaceuticals & Health Products- Average Order Value (US$), 2020-2029 Table 28: Pharmaceuticals & Health Products- Order Frequency (Orders per Year), 2020-2029 Table 29: Home Décor- Gross Merchandise Value (US$ Million), 2020-2029 Table 30: Home Décor- Gross Merchandise Volume (Millions), 2020-2029 Table 31: Home Décor- Average Order Value (US$), 2020-2029 Table 32: Home Décor- Order Frequency (Orders per Year), 2020-2029 Table 33: Clothing & Accessories- Gross Merchandise Value (US$ Million), 2020-2029 Table 34: Clothing & Accessories- Gross Merchandise Volume (Millions), 2020-2029 Table 35: Clothing & Accessories- Average Order Value (US$), 2020-2029 Table 36: Clothing & Accessories- Order Frequency (Orders per Year), 2020-2029 Table 37: Electronics- Gross Merchandise Value (US$ Million), 2020-2029 Table 38: Electronics- Gross Merchandise Volume (Millions), 2020-2029 Table 39: Electronics- Average Order Value (US$), 2020-2029 Table 40: Electronics- Order Frequency (Orders per Year), 2020-2029 Table 41: Others- Gross Merchandise Value (US$ Million), 2020-2029 Table 42: Others- Gross Merchandise Volume (Millions), 2020-2029 Table 43: Others- Average Order Value (US$), 2020-2029 Table 44: Others- Order Frequency (Orders per Year), 2020-2029 Table 45: Instant Bank Transfer- Gross Merchandise Value (US$ Million), 2020-2029 Table 46: Instant Bank Transfer- Gross Merchandise Volume (Millions), 2020-2029 Table 47: Instant Bank Transfer- Average Order Value (US$), 2020-2029 Table 48: Wallets & Digital Payments- Gross Merchandise Value (US$ Million), 2020-2029 Table 49: Wallets & Digital Payments- Gross Merchandise Volume (Millions), 2020-2029 Table 50: Wallets & Digital Payments- Average Order Value (US$), 2020-2029 Table 51: Credit & Debit Card- Gross Merchandise Value (US$ Million), 2020-2029 Table 52: Credit & Debit Card- Gross Merchandise Volume (Millions), 2020-2029 Table 53: Credit & Debit Card- Average Order Value (US$), 2020-2029 Table 54: Cash on Delivery- Gross Merchandise Value (US$ Million), 2020-2029 Table 55: Cash on Delivery- Gross Merchandise Volume (Millions), 2020-2029 Table 56: Cash on Delivery- Average Order Value (US$), 2020-2029 Table 57: Gen Z (15–25) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 58: Gen Z (15–25) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Table 59: Gen Z (15–25) Age Group- Average Order Value (US$), 2020-2029 Table 60: Millennials (26–39) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 61: Millennials (26–39) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Table 62: Millennials (26–39) Age Group- Average Order Value (US$), 2020-2029 Table 63. Gen X (40–55) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 64: Gen X (40–55) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Table 65: Gen X (40–55) Age Group- Average Order Value (US$), 2020-2029 Table 66: Baby Boomers (Above 55+) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Table 67: Baby Boomers (Above 55+) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Table 68: Baby Boomers (Above 55+) Age Group- Average Order Value (US$), 2020-2029 Table 69: Tier 1 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Table 70: Tier 1 Cities- Gross Merchandise Volume (Millions), 2020-2029 Table 71: Tier 1 Cities- Average Order Value (US$), 2020-2029 Table 72: Tier 1 Cities- Order Frequency (Orders per Year), 2020-2029 Table 73: Tier 2 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Table 74: Tier 2 Cities- Gross Merchandise Volume (Millions), 2020-2029 Table 75: Tier 2 Cities- Average Order Value (US$), 2020-2029 Table 76: Tier 2 Cities- Order Frequency (Orders per Year), 2020-2029 Table 77: Tier 3 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Table 78: Tier 3 Cities- Gross Merchandise Volume (Millions), 2020-2029 Table 79: Tier 3 Cities- Average Order Value (US$), 2020-2029 Table 80: Tier 3 Cities- Order Frequency (Orders per Year), 2020-2029 Table 81: Inventory Model- Gross Merchandise Value (US$ Million), 2020-2029 Table 82: Inventory Model- Gross Merchandise Volume (Millions), 2020-2029 Table 83: Inventory Model- Average Order Value (US$), 2020-2029 Table 84: Hyperlocal Model- Gross Merchandise Value (US$ Million), 2020-2029 Table 85: Hyperlocal Model- Gross Merchandise Volume (Millions), 2020-2029 Table 86: Hyperlocal Model- Average Order Value (US$), 2020-2029 Table 87: Multi-vendor Platform Model- Gross Merchandise Value (US$ Million), 2020-2029 Table 88: Multi-vendor Platform Model- Gross Merchandise Volume (Millions), 2020-2029 Table 89: Multi-vendor Platform Model- Average Order Value (US$), 2020-2029 Table 90: Others- Gross Merchandise Value (US$ Million), 2020-2029 Table 91: Others- Gross Merchandise Volume (Millions), 2020-2029 Table 92: Others- Average Order Value (US$), 2020-2029 Table 93: Delivery Time In 30 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Table 94: Delivery Time In 30 Minutes- Gross Merchandise Volume (Millions), 2020-2029 Table 95: Delivery Time In 30 Minutes- Average Order Value (US$), 2020-2029 Table 96: Delivery Time In 30 Minutes- Order Frequency (Orders per Year), 2020-2029 Table 97: Delivery Time 30–60 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Table 98: Delivery Time 30–60 Minutes- Gross Merchandise Volume (Millions), 2020-2029 Table 99: Delivery Time 30–60 Minutes- Average Order Value (US$), 2020-2029 Table 100: Delivery Time 30–60 Minutes- Order Frequency (Orders per Year), 2020-2029 Table 101: Delivery Time In 3 Hours- Gross Merchandise Value (US$ Million), 2020-2029 Table 102: Delivery Time In 3 Hours- Gross Merchandise Volume (Millions), 2020-2029 Table 103: Delivery Time In 3 Hours- Average Order Value (US$), 2020-2029 Table 104: Delivery Time In 3 Hours- Order Frequency (Orders per Year), 2020-2029
Figure 1: PayNXT360’s Methodology Framework Figure 2: Germany Quick Commerce – Gross Merchandise Value (US$ Million), 2020–2029 Figure 3: Germany Quick Commerce – Gross Merchandise Volume (Millions), 2020-2029 Figure 4: Germany Quick Commerce – Average Order Value (US$), 2020-2029 Figure 5: Germany Quick Commerce – Order Frequency (Orders per Year), 2020-2029 Figure 6: Germany Quick Commerce – Market Share Analysis by Key Players (%), 2024 Figure 7: Germany Quick Commerce Revenue and Growth Trend (US$ Million), 2020-2029 Figure 8: Germany Quick Commerce 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 (Millions), 2020-2029 Figure 14: Groceries & Staples- Average Order Value (US$), 2020-2029 Figure 15: Groceries & Staples- Order Frequency (Orders per Year), 2020-2029 Figure 16: Fruits & Vegetables- Gross Merchandise Value (US$ Million), 2020-2029 Figure 17: Fruits & Vegetables- Gross Merchandise Volume (Millions), 2020-2029 Figure 18: Fruits & Vegetables- Average Order Value (US$), 2020-2029 Figure 19: Fruits & Vegetables- Order Frequency (Orders per Year), 2020-2029 Figure 20: Snacks & Beverages- Gross Merchandise Value (US$ Million), 2020-2029 Figure 21: Snacks & Beverages- Gross Merchandise Volume (Millions), 2020-2029 Figure 22: Snacks & Beverages- Average Order Value (US$), 2020-2029 Figure 23: Snacks & Beverages- Order Frequency (Orders per Year), 2020-2029 Figure 24: Personal Care & Hygiene- Gross Merchandise Value (US$ Million), 2020-2029 Figure 25: Personal Care & Hygiene- Gross Merchandise Volume (Millions), 2020-2029 Figure 26: Personal Care & Hygiene- Average Order Value (US$), 2020-2029 Figure 27: Personal Care & Hygiene- Order Frequency (Orders per Year), 2020-2029 Figure 28: Pharmaceuticals & Health Products- Gross Merchandise Value (US$ Million), 2020-2029 Figure 29: Pharmaceuticals & Health Products- Gross Merchandise Volume (Millions), 2020-2029 Figure 30: Pharmaceuticals & Health Products- Average Order Value (US$), 2020-2029 Figure 31: Pharmaceuticals & Health Products- Order Frequency (Orders per Year), 2020-2029 Figure 32: Home Décor- Gross Merchandise Value (US$ Million), 2020-2029 Figure 33: Home Décor- Gross Merchandise Volume (Millions), 2020-2029 Figure 34: Home Décor- Average Order Value (US$), 2020-2029 Figure 35: Home Décor- Order Frequency (Orders per Year), 2020-2029 Figure 36: Clothing & Accessories- Gross Merchandise Value (US$ Million), 2020-2029 Figure 37: Clothing & Accessories- Gross Merchandise Volume (Millions), 2020-2029 Figure 38: Clothing & Accessories- Average Order Value (US$), 2020-2029 Figure 39: Clothing & Accessories- Order Frequency (Orders per Year), 2020-2029 Figure 40: Electronics- Gross Merchandise Value (US$ Million), 2020-2029 Figure 41: Electronics- Gross Merchandise Volume (Millions), 2020-2029 Figure 42: Electronics- Average Order Value (US$), 2020-2029 Figure 43: Electronics- Order Frequency (Orders per Year), 2020-2029 Figure 44: Other Product Category- Gross Merchandise Value (US$ Million), 2020-2029 Figure 45: Other Product Category- Gross Merchandise Volume (Millions), 2020-2029 Figure 46: Other Product Category- Average Order Value (US$), 2020-2029 Figure 47: Other Product Category- Order Frequency (Orders per Year), 2020-2029 Figure 48: Instant Bank Transfer- Gross Merchandise Value (US$ Million), 2020-2029 Figure 49: Instant Bank Transfer- Gross Merchandise Volume (Millions), 2020-2029 Figure 50: Instant Bank Transfer- Average Order Value (US$), 2020-2029 Figure 51: Wallets & Digital Payments- Gross Merchandise Value (US$ Million), 2020-2029 Figure 52: Wallets & Digital Payments- Gross Merchandise Volume (Millions), 2020-2029 Figure 53: Wallets & Digital Payments- Average Order Value (US$), 2020-2029 Figure 54: Credit & Debit Cards- Gross Merchandise Value (US$ Million), 2020-2029 Figure 55: Credit & Debit Cards- Gross Merchandise Volume (Millions), 2020-2029 Figure 56: Credit & Debit Cards- Average Order Value (US$), 2020-2029 Figure 57: Cash on Delivery- Gross Merchandise Value (US$ Million), 2020-2029 Figure 58: Cash on Delivery- Gross Merchandise Volume (Millions), 2020-2029 Figure 59: Cash on Delivery- Average Order Value (US$), 2020-2029 Figure 60: Gen Z (15–25) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 61: Gen Z (15–25) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Figure 62: Gen Z (15–25) Age Group- Average Order Value (US$), 2020-2029 Figure 63: Millennials (26–39) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 64: Millennials (26–39) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Figure 65: Millennials (26–39) Age Group- Average Order Value (US$), 2020-2029 Figure 66: Gen X (40–55) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 67: Gen X (40–55) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Figure 68: Gen X (40–55) Age Group- Average Order Value (US$), 2020-2029 Figure 69: Baby Boomers (Above 55+) Age Group- Gross Merchandise Value (US$ Million), 2020-2029 Figure 70: Baby Boomers (Above 55+) Age Group- Gross Merchandise Volume (Millions), 2020-2029 Figure 71: Baby Boomers (Above 55+) Age Group- Average Order Value (US$), 2020-2029 Figure 72: Tier 1 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Figure 73: Tier 1 Cities- Gross Merchandise Volume (Millions), 2020-2029 Figure 74: Tier 1 Cities- Average Order Value (US$), 2020-2029 Figure 75: Tier 1 Cities- Order Frequency (Orders per Year), 2020-2029 Figure 76: Tier 2 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Figure 77: Tier 2 Cities- Gross Merchandise Volume (Millions), 2020-2029 Figure 78: Tier 2 Cities- Average Order Value (US$), 2020-2029 Figure 79: Tier 2 Cities- Order Frequency (Orders per Year), 2020-2029 Figure 80: Tier 3 Cities- Gross Merchandise Value (US$ Million), 2020-2029 Figure 81: Tier 3 Cities- Gross Merchandise Volume (Millions), 2020-2029 Figure 82: Tier 3 Cities- Average Order Value (US$), 2020-2029 Figure 83: Tier 3 Cities- Order Frequency (Orders per Year), 2020-2029 Figure 84: Inventory Model- Gross Merchandise Value (US$ Million), 2020-2029 Figure 85: Inventory Model- Gross Merchandise Volume (Millions), 2020-2029 Figure 86: Inventory Model- Average Order Value (US$), 2020-2029 Figure 87: Hyperlocal Model- Gross Merchandise Value (US$ Million), 2020-2029 Figure 88: Hyperlocal Model- Gross Merchandise Volume (Millions), 2020-2029 Figure 89: Hyperlocal Model- Average Order Value (US$), 2020-2029 Figure 90: Multi-vendor Platform Model- Gross Merchandise Value (US$ Million), 2020-2029 Figure 91: Multi-vendor Platform Model- Gross Merchandise Volume (Millions), 2020-2029 Figure 92: Multi-vendor Platform Model- Average Order Value (US$), 2020-2029 Figure 93: Other Business Models- Gross Merchandise Value (US$ Million), 2020-2029 Figure 94: Other Business Models- Gross Merchandise Volume (Millions), 2020-2029 Figure 95: Other Business Models- Average Order Value (US$), 2020-2029 Figure 96: Delivery Time In 30 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Figure 97: Delivery Time In 30 Minutes- Gross Merchandise Volume (Millions), 2020-2029 Figure 98: Delivery Time In 30 Minutes- Average Order Value (US$), 2020-2029 Figure 99: Delivery Time In 30 Minutes- Order Frequency (Orders per Year), 2020-2029 Figure 100: Delivery Time 30–60 Minutes- Gross Merchandise Value (US$ Million), 2020-2029 Figure 101: Delivery Time 30–60 Minutes- Gross Merchandise Volume (Millions), 2020-2029 Figure 102: Delivery Time 30–60 Minutes- Average Order Value (US$), 2020-2029 Figure 103: Delivery Time 30–60 Minutes- Order Frequency (Orders per Year), 2020-2029 Figure 104: Delivery Time In 3 Hours- Gross Merchandise Value (US$ Million), 2020-2029 Figure 105: Delivery Time In 3 Hours- Gross Merchandise Volume (Millions), 2020-2029 Figure 106: Delivery Time In 3 Hours- Average Order Value (US$), 2020-2029 Figure 107: Delivery Time In 3 Hours- Order Frequency (Orders per Year), 2020-2029 Figure 108: Germany Quick Commerce – Average Subscription Uptake, 2024 Figure 109: Germany Quick Commerce- Average Subscription Uptake by Age Group, 2024 Figure 110: Germany Quick Commerce- Average Subscription Uptake by Location, 2024 Figure 111: Germany Quich Commerce- Average Delivery Time, 2024 Figure 112: Germany Quick Commerce Segment Share by Product Type, 2024 Figure 113: Germany Quick Commerce Segment Share by Payment Method, 2020-2029 Figure 114: Germany Quick Commerce Segment Share by Age Group, 2024 Figure 115: Germany Quick Commerce Segment Share by Location, 2020-2029 Figure 116: Germany Quick Commerce Segment Share by Business Model, 2024 Figure 117: Germany Quick Commerce Segment Share by Delivery Time, 2020-2029
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