GLOBAL BIG DATA IN E-COMMERCE MARKET 2019-2028

ICT | Telecom and Internet

GLOBAL BIG DATA IN E-COMMERCE MARKET 2019-2028

Market By Deployment, Data Type, Solution, End-user And Geography | Forecast 2019-2028

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The global Big Data in e-commerce market was valued at $2.69 billion in 2019 and is expected to reach $8.25 billion by 2028, growing at a CAGR of 13.27% during the forecast period. While calculating the revenue estimations of the studied market, the impact of COVID-19 has been taken into account by Triton Market Research.

Big Data has been impacting every industry and e-commerce is one of them. Sales data, delivery information, inventory and payment data are some of the crucial types of information for the e-commerce business to operate effectively. With respect to the e-commerce industry, the main objective of the companies is to understand and analyze customer patterns, which ultimately results in a higher influx of traffic and sales. The application of Big Data serves the purpose of analyzing past trends and business performances with detailed data insights, which enable the companies to gain consumer satisfaction with better offerings. E-retailers nowadays are increasingly using Big Data to analyze customer behavior based on which they make decisions and reorganizes their businesses to drive up their sales.



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Triton Market Research’s report on the Big Data in e-commerce market provides an in-depth insight of the market. The detailed analysis of the market includes key insights, Porter’s five force analysis, market attractiveness index, vendor scorecard, parent market analysis, evolution & transition of Big Data and industry components.

Adoption of Big Data by online retailers to gain competitive advantage, for customer behavioral analysis & for personalized product recommendations, is the key growth enabler for the market. E-retailers are continuously monitoring customers’ shopping experience, answering their queries, keeping them informed about new offers and tracking their purchase patterns, so as to cater to their needs. Due to the need to effectively manage inventory, organize customers based on their shopping patterns, demographic details & time period and cut down on their excess stock, Big Data is expected to find increasing application among the e-commerce sellers. For instance, during festive seasons, high purchases occur, and hence, some online store owners change the pricing suggested by Big Data analytics to attract customers. Also, e-commerce giants such as Alibaba and Amazon are using Big Data with an aim to increase their sales.

Other than the market drivers, the growing inclination of consumers towards various online payment methods will be a great opportunity for the market. As per the consumer survey, about 50% of e-commerce sales are made through mobile platforms. Moreover, more than 80% of the consumers prefer online payments as they do not require any card or physical wallets, and involve hassle-free and time-saving benefits. The use of Big Data helps in identifying fraudulent activities and any other threats involved in the process. Big Data also integrates different payment options in one centralized platform, thereby making the process convenient for customers.

However, commercial sectors are facing it challenging to spot a suitable talent due to the crunch of accomplished qualified in the Big Data industry. According to a report by Accenture, 78% of the enterprises in India see data as something that is essential and about 53% of the enterprises feel there is a lack of professionals related to big data. Also, the privacy of Big Data is a huge concern due to the distinctive characteristics of its application in the e-commerce environment. High concentration and volume of data increase the possibilities of hacking activities. Additionally, the presence of a high volume of data increases the probability of data files and documents containing valuable and sensitive information, which can result in various fraudulent activities and cybercriminals.





Key geographies covered in global Big Data in e-commerce market are:

           North America: United States and Canada

           Europe: United Kingdom, France, Germany, Spain, Italy, Russia and Rest of Europe

           Asia-Pacific: China, Japan, India, Australia, South Korea, ASEAN Countries and Rest of Asia-Pacific

           Latin America: Brazil, Mexico and Rest of Latin America

           The Middle East and Africa: Saudi Arabia, Turkey, United Arab Emirates, South Africa and Rest of Middle East & Africa

The segmentation analysis of the Big Data in e-commerce market is as follows:

     Deployment is segmented into:

O    Cloud-based

O    On-premises

     Data Type is segmented into:

O    Structured

O    Unstructured

O    Semi-structured

     Solution is segmented into:

O    Content Analytics

O    Customer Analytics

O    Fraud Detection

O    Risk Management

•     End-user is segmented into:

O    Online Classified

O    Online Education

O    Online Financial

O    Online Retail

O    Online Travel and Leisure

O    Other End-users

Promising companies that are operating in the Big Data in e-commerce market are Hitachi Ltd, SAP SE, Hewlett Packard Enterprise, Splunk Inc, Data USA, SAS Institute Inc, Dell Technologies, Amazon Web Services Inc, Teradata, Cloudera Inc, Microsoft Corporation, Oracle, Palantir Technologies, International Business Machines Corporation and Guavus Inc.

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Table of Content

1.    GLOBAL BIG DATA IN E-COMMERCE MARKET - SUMMARY

2.    INDUSTRY OUTLOOK

2.1. MARKET DEFINITION

2.2. PARENT MARKET ANALYSIS: BIG DATA MARKET

2.3. EVOLUTION & TRANSITION OF BIG DATA

2.4. KEY INSIGHTS

2.4.1. UNSTRUCTURED DATA OFFERS LUCRATIVE GROWTH OPPORTUNITIES

2.4.2. CLOUD IS THE MOST PREFERRED DEPLOYMENT MODE

2.4.3. CONTEXTUAL & PROGRAMMATIC ADVERTISING – KEY TREND

2.4.4. RISE IN SUBSCRIPTION-BASED BUSINESS MODELS

2.5. PORTER’S FIVE FORCE ANALYSIS

2.5.1. THREAT OF NEW ENTRANTS

2.5.2. THREAT OF SUBSTITUTE

2.5.3. BARGAINING POWER OF BUYERS

2.5.4. BARGAINING POWER OF SUPPLIERS

2.5.5. THREAT OF COMPETITIVE RIVALRY

2.6. MARKET ATTRACTIVENESS INDEX

2.7. VENDOR SCORECARD

2.8. INDUSTRY COMPONENTS

2.9. MARKET DRIVERS

2.9.1. ADOPTION OF BIG DATA BY ONLINE RETAILERS TO GAIN COMPETITIVE ADVANTAGE

2.9.2. E-RETAILERS USING BIG DATA FOR CUSTOMER BEHAVIORAL ANALYSIS & PERSONALIZED RECOMMENDATIONS

2.10.  MARKET RESTRAINTS

2.10.1. LACK OF BIG DATA PROFESSIONALS

2.11. MARKET OPPORTUNITIES

2.11.1. GROWING PREFERENCE OF CONSUMERS TOWARDS ONLINE PAYMENT METHODS

2.11.2. MASSIVE GROWTH IN THE DATA GENERATION

2.12. MARKET CHALLENGES

2.12.1. PRIVACY OF BIG DATA – MAJOR CHALLENGE

3.    GLOBAL BIG DATA IN E-COMMERCE MARKET OUTLOOK - BY DEPLOYMENT

3.1. CLOUD-BASED

3.2. ON-PREMISES

4.    GLOBAL BIG DATA IN E-COMMERCE MARKET OUTLOOK - BY DATA TYPE

4.1. STRUCTURED

4.2. UNSTRUCTURED

4.3. SEMI-STRUCTURED

5.    GLOBAL BIG DATA IN E-COMMERCE MARKET OUTLOOK - BY SOLUTION

5.1. CONTENT ANALYTICS

5.2. CUSTOMER ANALYTICS

5.3. FRAUD DETECTION

5.4. RISK MANAGEMENT

6.    GLOBAL BIG DATA IN E-COMMERCE MARKET OUTLOOK - BY END-USER

6.1. ONLINE CLASSIFIED

6.2. ONLINE EDUCATION

6.3. ONLINE FINANCIAL

6.4. ONLINE RETAIL

6.5. ONLINE TRAVEL AND LEISURE

6.6. OTHER END-USERS

7.    GLOBAL BIG DATA IN E-COMMERCE MARKET – REGIONAL OUTLOOK

7.1. NORTH AMERICA

7.1.1. MARKET BY DEPLOYMENT

7.1.2. MARKET BY DATA TYPE

7.1.3. MARKET BY SOLUTION

7.1.4. MARKET BY END-USER

7.1.5. COUNTRY ANALYSIS

7.1.5.1.      UNITED STATES

7.1.5.2.      CANADA

7.2. EUROPE

7.2.1. MARKET BY DEPLOYMENT

7.2.2. MARKET BY DATA TYPE

7.2.3. MARKET BY SOLUTION

7.2.4. MARKET BY END-USER

7.2.5. COUNTRY ANALYSIS

7.2.5.1.      UNITED KINGDOM

7.2.5.2.      GERMANY

7.2.5.3.      FRANCE

7.2.5.4.      SPAIN

7.2.5.5.      ITALY

7.2.5.6.      RUSSIA

7.2.5.7.      REST OF EUROPE

7.3. ASIA-PACIFIC

7.3.1. MARKET BY DEPLOYMENT

7.3.2. MARKET BY DATA TYPE

7.3.3. MARKET BY SOLUTION

7.3.4. MARKET BY END-USER

7.3.5. COUNTRY ANALYSIS

7.3.5.1.      CHINA

7.3.5.2.      JAPAN

7.3.5.3.      INDIA

7.3.5.4.      SOUTH KOREA

7.3.5.5.      ASEAN COUNTRIES

7.3.5.6.      AUSTRALIA & NEW ZEALAND

7.3.5.7.      REST OF ASIA-PACIFIC

7.4. LATIN AMERICA

7.4.1. MARKET BY DEPLOYMENT

7.4.2. MARKET BY DATA TYPE

7.4.3. MARKET BY SOLUTION

7.4.4. MARKET BY END-USER

7.4.5. COUNTRY ANALYSIS

7.4.5.1.      BRAZIL

7.4.5.2.      MEXICO

7.4.5.3.      REST OF LATIN AMERICA

7.5. MIDDLE EAST AND AFRICA

7.5.1. MARKET BY DEPLOYMENT

7.5.2. MARKET BY DATA TYPE

7.5.3. MARKET BY SOLUTION

7.5.4. MARKET BY END-USER

7.5.5. COUNTRY ANALYSIS

7.5.5.1.      UNITED ARAB EMIRATES

7.5.5.2.      SAUDI ARABIA

7.5.5.3.      TURKEY

7.5.5.4.      SOUTH AFRICA

7.5.5.5.      REST OF MIDDLE EAST & AFRICA

8.    COMPETITIVE LANDSCAPE

8.1. MICROSOFT CORPORATION

8.2. IBM CORPORATION

8.3. ORACLE

8.4. AMAZON WEB SERVICES INC

8.5. SAP SE

8.6. HEWLETT PACKARD ENTERPRISE

8.7. DATA USA

8.8. CLOUDERA INC

8.9. SAS INSTITUTE INC

8.10. TERADATA CORPORATION

8.11. GUAVUS INC

8.12.  PALANTIR TECHNOLOGIES

8.13. HITACHI LTD

8.14. DELL TECHNOLOGIES

8.15. SPLUNK INC

9.    RESEARCH METHODOLOGY & SCOPE

9.1. RESEARCH SCOPE & DELIVERABLES

9.2. SOURCES OF DATA

9.3. RESEARCH METHODOLOGY

List of table

TABLE 1: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY GEOGRAPHY, 2019-2028 (IN $ MILLION)      

TABLE 2: EVOLUTION & TRANSITION OF BIG DATA          

TABLE 3: VENDOR SCORECARD        

TABLE 4: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY DEPLOYMENT, 2019-2028 (IN $ MILLION)      

TABLE 5: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY DATA TYPE, 2019-2028 (IN $ MILLION)      

TABLE 6: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY SOLUTION, 2019-2028 (IN $ MILLION)      

TABLE 7: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY END-USER, 2019-2028 (IN $ MILLION)      

TABLE 8: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY GEOGRAPHY, 2019-2028 (IN $ MILLION)      

TABLE 9: NORTH AMERICA BIG DATA IN E-COMMERCE MARKET, BY COUNTRY, 2019-2028 (IN $ MILLION)        

TABLE 10: NORTH AMERICA BIG DATA IN E-COMMERCE MARKET, BY DEPLOYMENT, 2019-2028 (IN $ MILLION)          

TABLE 11: NORTH AMERICA BIG DATA IN E-COMMERCE MARKET, BY DATA TYPE, 2019-2028 (IN $ MILLION)          

TABLE 12: NORTH AMERICA BIG DATA IN E-COMMERCE MARKET, BY SOLUTION, 2019-2028 (IN $ MILLION)        

TABLE 13: NORTH AMERICA BIG DATA IN E-COMMERCE MARKET, BY END-USER, 2019-2028 (IN $ MILLION)        

TABLE 14: EUROPE BIG DATA IN E-COMMERCE MARKET, BY COUNTRY, 2019-2028 (IN $ MILLION)      

TABLE 15: EUROPE BIG DATA IN E-COMMERCE MARKET, BY DEPLOYMENT, 2019-2028 (IN $ MILLION)      

TABLE 16: EUROPE BIG DATA IN E-COMMERCE MARKET, BY DATA TYPE, 2019-2028 (IN $ MILLION)      

TABLE 17: EUROPE BIG DATA IN E-COMMERCE MARKET, BY SOLUTION, 2019-2028 (IN $ MILLION)      

TABLE 18: EUROPE BIG DATA IN E-COMMERCE MARKET, BY END-USER, 2019-2028 (IN $ MILLION)      

TABLE 19: ASIA-PACIFIC BIG DATA IN E-COMMERCE MARKET, BY COUNTRY, 2019-2028 (IN $ MILLION)   

TABLE 20: ASIA-PACIFIC BIG DATA IN E-COMMERCE MARKET, BY DEPLOYMENT, 2019-2028 (IN $ MILLION)        

TABLE 21: ASIA-PACIFIC BIG DATA IN E-COMMERCE MARKET, BY DATA TYPE, 2019-2028 (IN $ MILLION)        

TABLE 22: ASIA-PACIFIC BIG DATA IN E-COMMERCE MARKET, BY SOLUTION, 2019-2028 (IN $ MILLION)   

TABLE 23: ASIA-PACIFIC BIG DATA IN E-COMMERCE MARKET, BY END-USER, 2019-2028 (IN $ MILLION)   

TABLE 24: LATIN AMERICA BIG DATA IN E-COMMERCE MARKET, BY COUNTRY, 2019-2028 (IN $ MILLION)        

TABLE 25: LATIN AMERICA BIG DATA IN E-COMMERCE MARKET, BY DEPLOYMENT, 2019-2028 (IN $ MILLION)          

TABLE 26: LATIN AMERICA BIG DATA IN E-COMMERCE MARKET, BY DATA TYPE, 2019-2028 (IN $ MILLION)        

TABLE 27: LATIN AMERICA BIG DATA IN E-COMMERCE MARKET, BY SOLUTION, 2019-2028 (IN $ MILLION)        

TABLE 28: LATIN AMERICA BIG DATA IN E-COMMERCE MARKET, BY END-USER, 2019-2028 (IN $ MILLION)        

TABLE 29: MIDDLE EAST AND AFRICA BIG DATA IN E-COMMERCE MARKET, BY COUNTRY, 2019-2028 (IN $ MILLION)

TABLE 30: MIDDLE EAST AND AFRICA BIG DATA IN E-COMMERCE MARKET, BY DEPLOYMENT, 2019-2028 (IN $ MILLION)      

TABLE 31: MIDDLE EAST AND AFRICA BIG DATA IN E-COMMERCE MARKET, BY DATA TYPE, 2019-2028 (IN $ MILLION)

TABLE 32: MIDDLE EAST AND AFRICA BIG DATA IN E-COMMERCE MARKET, BY SOLUTION, 2019-2028 (IN $ MILLION)

TABLE 33: MIDDLE EAST AND AFRICA BIG DATA IN E-COMMERCE MARKET, BY END-USER, 2019-2028 (IN $ MILLION)

List of Figures

FIGURE 1: MARKET ATTRACTIVENESS INDEX       

FIGURE 2: INDUSTRY COMPONENTS

FIGURE 3: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY CLOUD-BASED, 2019-2028 (IN $ MILLION)   

FIGURE 4: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY ON-PREMISES, 2019-2028 (IN $ MILLION)      

FIGURE 5: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY STRUCTURED, 2019-2028 (IN $ MILLION)      

FIGURE 6: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY UNSTRUCTURED, 2019-2028 (IN $ MILLION)        

FIGURE 7: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY SEMI-STRUCTURED, 2019-2028 (IN $ MILLION)          

FIGURE 8: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY CONTENT ANALYTICS, 2019-2028 (IN $ MILLION)          

FIGURE 9: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY CUSTOMER ANALYTICS, 2019-2028 (IN $ MILLION)          

FIGURE 10: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY FRAUD DETECTION, 2019-2028 (IN $ MILLION)          

FIGURE 11: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY RISK MANAGEMENT, 2019-2028 (IN $ MILLION)          

FIGURE 12: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY ONLINE CLASSIFIED, 2019-2028 (IN $ MILLION)          

FIGURE 13: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY ONLINE EDUCATION, 2019-2028 (IN $ MILLION)          

FIGURE 14: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY ONLINE FINANCIAL, 2019-2028 (IN $ MILLION)          

FIGURE 15: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY ONLINE RETAIL, 2019-2028 (IN $ MILLION)        

FIGURE 16: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY ONLINE TRAVEL AND LEISURE, 2019-2028 (IN $ MILLION)     

FIGURE 17: GLOBAL BIG DATA IN E-COMMERCE MARKET, BY OTHER END-USERS, 2019-2028 (IN $ MILLION)          

FIGURE 18: GLOBAL BIG DATA IN E-COMMERCE MARKET, REGIONAL OUTLOOK, 2019 & 2028 (IN %)  

FIGURE 19: UNITED STATES BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)           

FIGURE 20: CANADA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)       

FIGURE 21: UNITED KINGDOM BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)      

FIGURE 22: GERMANY BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)   

FIGURE 23: FRANCE BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)       

FIGURE 24: SPAIN BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)           

FIGURE 25: ITALY BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)

FIGURE 26: RUSSIA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)        

FIGURE 27: REST OF EUROPE BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)      

FIGURE 28: CHINA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)           

FIGURE 29: JAPAN BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)          

FIGURE 30: INDIA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION) 

FIGURE 31: SOUTH KOREA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)           

FIGURE 32: ASEAN COUNTRIES BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)      

FIGURE 33: AUSTRALIA & NEW ZEALAND BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)        

FIGURE 34: REST OF ASIA-PACIFIC BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)      

FIGURE 35: BRAZIL BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)         

FIGURE 36: MEXICO BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)       

FIGURE 37: REST OF LATIN AMERICA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)      

FIGURE 38: UNITED ARAB EMIRATES BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)      

FIGURE 39: SAUDI ARABIA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)           

FIGURE 40: TURKEY BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)       

FIGURE 41: SOUTH AFRICA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)           

FIGURE 42: REST OF MIDDLE EAST & AFRICA BIG DATA IN E-COMMERCE MARKET, 2019-2028 (IN $ MILLION)          

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