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Global Shopping Application Market to reach USD 2477.19 million by the end of 2029

Global Shopping Application Market Size study & Forecast, by Marketplace (Google Play Store, Apple iOS Store, Others) and Regional Analysis, 2022-2029

Product Code: OIRHG-51638579
Publish Date: 16-11-2022
Page: 200

Global Shopping Application Market is valued at approximately USD 868.4 million in 2021 and is anticipated to grow with a healthy growth rate of more than 14% over the forecast period 2022-2029. The market expansion might be attributed to the region’s expanding desire for handmade eco-friendly goods. Before making a purchase, customers can browse products and services using shopping applications in the comfort of their homes. The market is expanding as a result of the rising demand for AI-based shopping applications. Additionally, it is projected that the convenience of transportation and the affordable aftermarket services offered globally would boost market growth. The market is expanding as a result of a rise in the use of internet portals in Europe and a rise in the demand for high-end desired goods. However, the market’s expansion is being hampered by expensive but inferior goods. Key players are currently concentrating on adopting shopping applications with varied access capabilities. Consequently, it is anticipated that the market for shopping applications would expand significantly throughout the course of the projected period.

In comparison to other large nations, the UK has the highest prevalence of online purchasing. With over USD 3 billion spent each week in the UK internet retail industry, consumer eCommerce currently represents over 36% of the country’s overall retail market (up from 20% in 2019), according to International Trade Administration. Along with this, Sales of retail e-commerce are expected to increase quickly in the United States during the next few years, from around 470 billion dollars in 2021 to more than 560 billion dollars in 2025, according to Statista. Along with this, accruing to Statista, growth for e-commerce sales is rising around the globe, which is driving the growth of the market. For instance, in 2020, the sales of e-commerce were USD 4,938 billion which is predicted to increase to USD 6,767 billion in 2023. However, rising number of competitors over the forecast period is limiting the market growth for the market.

The key regions considered for the Global Shopping Application Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. Due to the increasing demand for electronic devices from customers in China and India, Asia Pacific had the greatest revenue share over the projection period of 2022–2029. The adoption of technologically sophisticated applications in Japan that include features like layered security and automated site backup is fueling the market’s expansion. The growing need for breadcrumb navigation to quickly navigate across product categories is what is driving the market in China. The fastest CAGR is anticipated for Central and South America from 2022 to 2028. This is a result of customers in Brazil and Argentina having a higher demand for online portal apps. One important growing reason is the recent tendency in Brazil to use machine learning chat assistance to run e-commerce apps. Over the course of the projection period, it is expected that Argentina’s rising consumer product demand would accelerate market expansion.

Major market players included in this report are:
LimeRoad
Lazada
Tvisha Technologies
ZALORA
eBay
Gearbest
Tata Cliq
Etsy
Koovs
AJIO

Recent Developments in the Market:
 In September 2022, Poq, a global provider of mobile app platforms, announced ECO. The Australian-based wellness company Modern Essentials, which specialises in 100% pure essential oils and mixes, has released native iOS and Android applications utilising Shopify Feedless SDK and poq’s composable commerce mobile app stack.
 In 2021, Ralph Lauren unveiled Ralph Lauren x ZEPETO, a new partnership for the popular global social networking and avatar simulation software, where users can interact with one another and immerse themselves in a fully articulated virtual environment with a customised 3D avatar.
 In 2018, ZARA, a brand of ready-to-wear clothes that is renowned for being among the first to adopt emerging trends, introduced an augmented reality line. Use this cutting-edge technology to discover the new collection on ZARA’s website, in delivery boxes, and in storefront windows.
Global Shopping Application Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Marketplace, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Marketplace offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Marketplace:
Google Play Store
Apple iOS Store
Others

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Million)
1.2.1. Shopping Application Market, by Region, 2019-2029 (USD Million)
1.2.2. Shopping Application Market, by Marketplace, 2019-2029 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Shopping Application Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Shopping Application Market Dynamics
3.1. Shopping Application Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing retail industry
3.1.1.2. Growing e-commerce market
3.1.2. Market Challenges
3.1.2.1. Number of competitors
3.1.3. Market Opportunities
3.1.3.1. Advancements in AI integration in shopping application
Chapter 4. Global Shopping Application Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Investment Adoption Model
4.5. Analyst Recommendation & Conclusion
4.6. Top investment opportunity
4.7. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Shopping Application Market, by Marketplace
6.1. Market Snapshot
6.2. Global Shopping Application Market by Marketplace, Performance – Potential Analysis
6.3. Global Shopping Application Market Estimates & Forecasts by Marketplace, 2019-2029 (USD Million)
6.4. Shopping Application Market, Sub Segment Analysis
6.4.1. Google Play Store
6.4.2. Apple iOS Store
6.4.3. Others
Chapter 7. Global Shopping Application Market, Regional Analysis
7.1. Shopping Application Market, Regional Market Snapshot
7.2. North America Shopping Application Market
7.2.1. U.S. Shopping Application Market
7.2.1.1. Marketplace breakdown estimates & forecasts, 2019-2029
7.2.2. Canada Shopping Application Market
7.3. Europe Shopping Application Market Snapshot
7.3.1. U.K. Shopping Application Market
7.3.2. Germany Shopping Application Market
7.3.3. France Shopping Application Market
7.3.4. Spain Shopping Application Market
7.3.5. Italy Shopping Application Market
7.3.6. Rest of Europe Shopping Application Market
7.4. Asia-Pacific Shopping Application Market Snapshot
7.4.1. China Shopping Application Market
7.4.2. India Shopping Application Market
7.4.3. Japan Shopping Application Market
7.4.4. Australia Shopping Application Market
7.4.5. South Korea Shopping Application Market
7.4.6. Rest of Asia Pacific Shopping Application Market
7.5. Latin America Shopping Application Market Snapshot
7.5.1. Brazil Shopping Application Market
7.5.2. Mexico Shopping Application Market
7.6. Rest of The World Shopping Application Market

Chapter 8. Competitive Intelligence
8.1. Top Market Strategies
8.2. Company Profiles
8.2.1. LimeRoad
8.2.1.1. Key Information
8.2.1.2. Overview
8.2.1.3. Financial (Subject to Data Availability)
8.2.1.4. Product Summary
8.2.1.5. Recent Developments
8.2.2. Lazada
8.2.3. Tvisha Technologies
8.2.4. ZALORA
8.2.5. eBay
8.2.6. Gearbest
8.2.7. Tata Cliq
8.2.8. Etsy
8.2.9. Koovs
8.2.10. AJIO
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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