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Big Data Analytics in Retail Market by Component (Software and Services), Deployment (On-premise and Cloud), Enterprise Size (Large Enterprises and Small & Medium-sized Enterprises), and Application (Sales & Marketing Analytics, Supply Chain Operations Management, Merchandising Analytics, Customer Analytics, and Others): Global Opportunity Analysis and Industry Forecast, 2020–2027

A02451
Pages: 274
Aug 2020 | 2979 Views
 
Author(s) : Vishwa Gaul
Tables: 133
Charts: 70
 

COVID-19

Pandemic disrupted the entire world and affected many industries.

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Big Data Analytics in Retail Market Statistics - 2027

Global big data analytics in retail market size was valued at $4.43 billion in 2019, and is projected to reach $17.85 billion by 2027, growing at a CAGR of 20.4% from 2020 to 2027. Big data describes a large volume of data that is used to reveal patterns, trends, and associations, especially related to human behavior and interactions. For the retail industry, big data is used for getting greater understanding of consumer shopping habits and how to attract new customers. Big data analytics in retail enables companies to create customer recommendations based on their purchase history, resulting in personalized shopping experiences. These big data analytics solutions also help in forecasting trends and making strategic decisions based on market analysis.

“Post COVID-19, big data analytics in retail software is expected to witness significant demand owing to the need to analyze business continuity scenarios, assess readiness to reopen the stores as per COVID-19 confirmed cases, and planning the sustainable strategies according to disruptive retail industry trends.”

Big-Data-Analytics-in-Retail-Market-2020-2027

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Increase in spending on big data analytics tools, rise in need to deliver personalized customer experience to increase sales, and increase in growth of the e-commerce sector are some of the major factors that are driving the growth of the global market. However, issues in collecting and collating the data from disparate systems and challenges in capturing customer data are anticipated to restrict the big data analytics in retail market growth. On the contrary, integration of new technologies such as IoT, AI and machine learning in big data analytics in retail, and rise in demand for predictive analytics in retail are anticipated to provide lucrative growth opportunities for the global big data analytics in retail market during the analysis period.

Big Data Analytics in Retail Market
By Component

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Big Data Analytics in Retail Software segment is projected as one of the most lucrative segments during the forecast period.

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On the basis of component, the software segment dominated the overall big data analytics in retail market size in 2019. This is attributed to the advantage of big data analytics in retail solution such as delivering business critical insights into predicting future trends based of historic data, customer behavior insights, pricing analysis, market basket analysis, supply chain management, and more.

Big Data Analytics in Retail Market
By Deployment Mode

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Cloud deployment mode segment is projected to witness highest growth rate during the forecast period.

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According to application, the supply chain operations management segment accounted for the highest big data analytics in retail market share in the global market in 2019. However, customer analytics segment is expected grow at the highest rate during the forecast period owing to increasing need to gain valuable insights regarding customer preferences, purchasing patterns and customer behavior.

Big Data Analytics in Retail Market
By Enterprise Size

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Large Enterprises accounted for the highest market share in 2019.

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In 2019, North America accounted for the highest big data analytics in retail market share, due to high spending on big data analytics tools and early adoption of modern technologies such as IoT, AI and more, in this region. In addition, large presence of key market vendors in North America is also propelling the growth of this segment. The need to analyze customer behavior forecast the budget requirements, formulate effective promotional and sales strategies by analyzing historic trends act as the key driving factors of the North America big data analytics in retail market.

Big Data Analytics in Retail Market
By Application

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Customer Analytics is projected to be one of the most significant segments during the forecast period.

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The emergence of COVID-19 is expected to have a trivial impact on the growth of big data analytics in retail market. The spending on big data analytics in retail industry is expected to be maintained as planned before this pandemic owing to multiple factors such as need of retailers to analyze the market trends, shift in customer preferences, and analyze customer data to offer personalized offerings and more. Due to COVID-19, many countries have enforced lockdown and it has affected the retail industry’s brick-and-mortar stores. The shift in buying patterns of consumers such as spike in sale of essential items and declining demand for non-essential items was observed during the COVID-19 pandemic. In addition, the trend of preference to buying from e-commerce platforms over physical stores is accelerating. Thus, with the emergence COVID-19, the use of big data analytics in retail will enable enterprises to analyze business continuity scenarios and formulate relevant business strategies as per the market trend during the pandemic period.

The report focuses on the growth prospects, restraints, and global big data analytics in retail market trends. Moreover, the study includes Porter’s five forces analysis of the industry to understand the impact of various factors such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers on the growth of the big data analytics in retail market.

Big Data Analytics in Retail Market
By Region

2027
North America 
Europe
Asia-pacific
Lamea

Asia-Pacific would exhibit the highest CAGR of 23.5% during 2020-2027.

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Segment review

The global big data analytics in retail market is segmented into component, deployment, enterprise size, industry vertical, and region. By component, it is divided into software, and services. Depending on deployment, it is categorized into on-premise and cloud. According to enterprise size, the big data analytics in retail market is segregated into large enterprises and small & medium enterprises. As per application, it is fragmented into sales & marketing analytics, supply chain operations management, merchandising analytics, customer analytics and others. Region wise, it is analyzed across North America, Europe, Asia-Pacific and LAMEA.

The key players operating in the global big data analytics in retail market analysis include Alteryx Inc., IBM, Microsoft, Microstrategy Inc., Oracle Corporation, Qlik Technologies Inc., RetailNext, SAP SE, SAS institute, and Teradata.

Top impacting factors

Increase in spending on big data analytics tools

Retailers across the world are increasingly adopting big data technologies to generate more value and data-driven decision making. Companies are leveraging data generated to improve customer facing experiences, employee productivity, operational improvement, product innovation and more. The retailers are mostly seeking to utilize these tools for forecasting, personalization, marketing, price optimization, merchandizing, and others. As per a study conducted by Forbes in 2015, customer analytics, operational analytics and fraud & compliance are some of the top use cases for big data in retail industry. It has emerged as the most important information system for CEOs, and they are now viewing data and analytics software as directly contributing to organizational profitability. Thus, retail companies are increasingly focusing on adopting big data analytics software and embedding them in the existing workflows of organizations.

Increasing growth of e-commerce sector

With big data analytics in retail software, retailers can improve the performance of their online stores to generate more revenue. Utilizing website analytics, clickstream data and heatmap studies, retailers can optimize product landing pages to ensure better engagement and conversion rates. Personalized product recommendations and offers based on historic web footprints of customers increases the chances of clickthroughs and sales. Items can be promoted by inspecting data points such as product browsing activity by region, user feedback and reviews, saved wishlists, or items in abandoned shopping carts. Further, today’s customers are more connected than ever before due to proliferation of smartphones. Thus, customers can access any information to consumer products using channels such as mobile, social media, e-commerce sites etc. Thus, for understanding customer’s buying decisions companies are utilizing customer journey analytics. This is further driving the growth of the big data analytics in retail market.

Growing demand of predictive analytics in retail

Predictive analytics in retail can enable extracting valuable information from the massive data which will be useful for retail companies in future. Analytical data helps retailers to offer precise insights, improve the existing process, future customer buying process, and more. It also helps in forming the retail sales strategy and increases the ROI of marketing activities. Predictive analytics for retail industry helps to optimize the supply chain and increase collaboration internally and across trading partners. The analytics report generated from using this software helps to guide new product development and launches. Further, it enables a curated relationship over a tailored conversation between retailers and suppliers. It also facilitates to improve conversion rate, lessening customer churn, and reducing customer acquisition costs. It also provides fast feedback on consumer tastes and preferences. Thus, owing to all these functionalities, the demand for predictive analytics in retail is on the rise, which is offering lucrative opportunities for the market.

Key Benefits For Stakeholders

  • This study includes the analytical depiction of the global big data analytics in retail market forecast and trends to determine the imminent investment pockets.
  • The report presents information related to key drivers, restraints, and big data analytics in retail market opportunity.
  • The current market size is quantitatively analyzed from 2019 to 2027 to highlight the financial competency of the big data analytics in retail industry.
  • Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.

Key Market Segments

By Component    

  • Software
  • Services  

By Deployment     

  • On-premise
  • Cloud    

By Enterprise Size    

  • Large Enterprises 
  • Small & Medium Enterprises (SMEs)

By Application

  • Sales and marketing analytics
  • Supply chain operations management
  • Merchandising analytics
  • Customer analytics
  • Others

By Region

  • North America
    • U.S.
    • Canada
  • Europe 
    • UK
    • Germany
    • France
    • Rest of Europe
  • Asia-Pacific 
    • China
    • India
    • Japan
    • Australia
    • Rest of Asia-Pacific
  • LAMEA
    • Latin America
    • Middle East
    • Africa

Key Market Players

  • Alteryx Inc.
  • IBM
  • Microsoft
  • Microstrategy Inc.
  • Oracle Corporation
  • Qlik Technologies Inc.
  • RetailNext
  • SAP SE
  • SAS institute
  • Teradata
 

CHAPTER 1:INTRODUCTION

1.1.REPORT DESCRIPTION
1.2.KEY BENEFITS FOR STAKEHOLDERS
1.3.KEY MARKET SEGMENTS
1.4.RESEARCH METHODOLOGY

1.4.1.Secondary research
1.4.2.Primary research
1.4.3.Analyst tools & models

CHAPTER 2:EXECUTIVE SUMMARY

2.1.KEY FINDINGS

2.1.1.Top impacting factors
2.1.2.Top investment pockets

2.2.CXO PERSPECTIVE

CHAPTER 3:MARKET OVERVIEW

3.1.MARKET DEFINITION AND SCOPE
3.2.PORTER’S FIVE FORCES ANALYSIS
3.3.KEY PLAYER POSITIONING
3.4.CASE STUDIES

3.4.1.Case Study 01
3.4.2.Case Study 02

3.5.MARKET DYNAMICS

3.5.1.Drivers

3.5.1.1.Increase in spending on big data analytics tools
3.5.1.2.Rise in need to deliver personalized customer experience to increase sales
3.5.1.3.Increasing growth of e-commerce sector

3.5.2.Restraints

3.5.2.1.Collecting and collating the data from disparate systems
3.5.2.2.To capture customer data

3.5.3.Opportunity

3.5.3.1.Integration of new technologies such as IoT, AI and machine learning in big data analytics in retail
3.5.3.2.Growing demand of predictive analytics in retail

3.6.IMPACT ANALYSIS: COVID-19 ON BIG DATA IN RETAIL ANALYTICS MARKET

3.6.1.Impact on market size
3.6.2.Consumer trends, preferences, and budget impact
3.6.3.Regulatory framework
3.6.4.Economic impact
3.6.5.Key player strategies to tackle negative impact
3.6.6.Opportunity window (due to COVID outbreak)

CHAPTER 4:BIG DATA ANALYTICS IN RETAIL MARKET, BY COMPONENT

4.1.OVERVIEW
4.2.SOFTWARE

4.2.1.Key market trends, growth factors, and opportunities
4.2.2.Market size and forecast, by region
4.2.3.Market analysis, by region

4.3.SERVICE

4.3.1.Key market trends, growth factors, and opportunities
4.3.2.Market size and forecast, by region
4.3.3.Market analysis, by region

CHAPTER 5:BIG DATA ANALYTICS IN RETAIL MARKET, BY DEPLOYMENT

5.1.OVERVIEW
5.2.ON PREMISE

5.2.1.Key market trends, growth factors, and opportunities
5.2.2.Market size and forecast, by region
5.2.3.Market analysis, by region

5.3.CLOUD

5.3.1.Key market trends, growth factors, and opportunities
5.3.2.Market size and forecast, by region
5.3.3.Market analysis, by region

CHAPTER 6:BIG DATA ANALYTICS IN RETAIL MARKET, BY ORGANIZATION SIZE

6.1.OVERVIEW
6.2.LARGE ENTERPRISES

6.2.1.Key market trends, growth factors, and opportunities
6.2.2.Market size and forecast, by region
6.2.3.Market analysis, by region

6.3.SMES

6.3.1.Key market trends, growth factors, and opportunities
6.3.2.Market size and forecast, by region
6.3.3.Market analysis, by region

CHAPTER 7:BIG DATA ANALYTICS IN RETAIL MARKET, BY APPLICATION

7.1.OVERVIEW
7.2.SALES AND MARKETING ANALYTICS

7.2.1.Key market trends, growth factors, and opportunities
7.2.2.Market size and forecast, by region
7.2.3.Market analysis, by region

7.3.SUPPLY CHAIN OPERATIONS MANAGEMENT

7.3.1.Key market trends, growth factors, and opportunities
7.3.2.Market size and forecast, by region
7.3.3.Market analysis, by region

7.4.MERCHANDISING ANALYTICS

7.4.1.Key market trends, growth factors, and opportunities
7.4.2.Market size and forecast, by region
7.4.3.Market analysis, by region

7.5.CUSTOMER ANALYTICS

7.5.1.Key market trends, growth factors, and opportunities
7.5.2.Market size and forecast, by region
7.5.3.Market analysis, by region

7.6.OTHERS

7.6.1.Key market trends, growth factors, and opportunities
7.6.2.Market size and forecast, by region
7.6.3.Market analysis, by region

CHAPTER 8:BIG DATA ANALYTICS IN RETAIL MARKET, BY REGION

8.1.OVERVIEW
8.2.NORTH AMERICA

8.2.1.Key market trends, growth factors and opportunities
8.2.2.Market size and forecast, by component
8.2.3.Market size and forecast, by deployment
8.2.4.Market size and forecast, by organization size
8.2.5.Market size and forecast, by application
8.2.6.Market analysis by country

8.2.6.1.U.S.

8.2.6.1.1.Market size and forecast, by component
8.2.6.1.2.Market size and forecast, by deployment
8.2.6.1.3.Market size and forecast, by organization size
8.2.6.1.4.Market size and forecast, by application

8.2.6.2.Canada

8.2.6.2.1.Market size and forecast, by component
8.2.6.2.2.Market size and forecast, by deployment
8.2.6.2.3.Market size and forecast, by organization size
8.2.6.2.4.Market size and forecast, by application

8.3.EUROPE

8.3.1.Key market trends, growth factors and opportunities
8.3.2.Market size and forecast, by component
8.3.3.Market size and forecast, by deployment
8.3.4.Market size and forecast, by organization size
8.3.5.Market size and forecast, by application
8.3.6.Market analysis by country

8.3.6.1.UK

8.3.6.1.1.Market size and forecast, by component
8.3.6.1.2.Market size and forecast, by deployment
8.3.6.1.3.Market size and forecast, by organization size
8.3.6.1.4.Market size and forecast, by application

8.3.6.2.Germany

8.3.6.2.1.Market size and forecast, by component
8.3.6.2.2.Market size and forecast, by deployment
8.3.6.2.3.Market size and forecast, by organization size
8.3.6.2.4.Market size and forecast, by application

8.3.6.3.France

8.3.6.3.1.Market size and forecast, by component
8.3.6.3.2.Market size and forecast, by deployment
8.3.6.3.3.Market size and forecast, by organization size
8.3.6.3.4.Market size and forecast, by application

8.3.6.4.Rest of Europe

8.3.6.4.1.Market size and forecast, by component
8.3.6.4.2.Market size and forecast, by deployment
8.3.6.4.3.Market size and forecast, by organization size
8.3.6.4.4.Market size and forecast, by application

8.4.ASIA-PACIFIC

8.4.1.Key market trends, growth factors and opportunities
8.4.2.Market size and forecast, by component
8.4.3.Market size and forecast, by deployment
8.4.4.Market size and forecast, by organization size
8.4.5.Market size and forecast, by application
8.4.6.Market analysis by country

8.4.6.1.China

8.4.6.1.1.Market size and forecast, by component
8.4.6.1.2.Market size and forecast, by deployment
8.4.6.1.3.Market size and forecast, by organization size
8.4.6.1.4.Market size and forecast, by application

8.4.6.2.India

8.4.6.2.1.Market size and forecast, by component
8.4.6.2.2.Market size and forecast, by deployment
8.4.6.2.3.Market size and forecast, by organization size
8.4.6.2.4.Market size and forecast, by application

8.4.6.3.Japan

8.4.6.3.1.Market size and forecast, by component
8.4.6.3.2.Market size and forecast, by deployment
8.4.6.3.3.Market size and forecast, by organization size
8.4.6.3.4.Market size and forecast, by application

8.4.6.4.Australia

8.4.6.4.1.Market size and forecast, by component
8.4.6.4.2.Market size and forecast, by deployment
8.4.6.4.3.Market size and forecast, by organization size
8.4.6.4.4.Market size and forecast, by application

8.4.6.5.Rest of Asia-Pacific

8.4.6.5.1.Market size and forecast, by component
8.4.6.5.2.Market size and forecast, by deployment
8.4.6.5.3.Market size and forecast, by organization size
8.4.6.5.4.Market size and forecast, by application

8.5.LAMEA

8.5.1.Key market trends, growth factors and opportunities
8.5.2.Market size and forecast, by component
8.5.3.Market size and forecast, by deployment
8.5.4.Market size and forecast, by organization size
8.5.5.Market size and forecast, by application
8.5.6.Market analysis by country

8.5.6.1.Latin America

8.5.6.1.1.Market size and forecast, by component
8.5.6.1.2.Market size and forecast, by deployment
8.5.6.1.3.Market size and forecast, by organization size
8.5.6.1.4.Market size and forecast, by application

8.5.6.2.Middle East

8.5.6.2.1.Market size and forecast, by component
8.5.6.2.2.Market size and forecast, by deployment
8.5.6.2.3.Market size and forecast, by organization size
8.5.6.2.4.Market size and forecast, by application

8.5.6.3.Africa

8.5.6.3.1.Market size and forecast, by component
8.5.6.3.2.Market size and forecast, by deployment
8.5.6.3.3.Market size and forecast, by organization size
8.5.6.3.4.Market size and forecast, by application

CHAPTER 9:COMPETITIVE LANDSCAPE

9.1.COMPETITIVE DASHBOARD
9.2.TOP WINNING STRATEGIES
9.3.KEY DEVELOPMENTS

9.3.1.New product launches
9.3.2.Partnership
9.3.3.Acquisition
9.3.4.Product development
9.3.5.Business expansion
9.3.6.Collaboration
9.3.7.Agreement

CHAPTER 10:COMPANY PROFILE

10.1.ADOBE INC.

10.1.1.Company overview
10.1.2.Key Executives
10.1.3.Company snapshot
10.1.4.Operating business segments
10.1.5.Product portfolio
10.1.6.R&D Expenditure
10.1.7.Business performance
10.1.8.Key strategic moves and developments

10.2.CISCO SYSTEMS, INC.

10.2.1.Company overview
10.2.2.Key Executives
10.2.3.Company snapshot
10.2.4.Product portfolio
10.2.5.R&D Expenditure
10.2.6.Business performance
10.2.7.Key strategic moves and developments

10.3.INTERNATIONAL BUSINESS MACHINES CORPORATION

10.3.1.Company overview
10.3.2.Key Executives
10.3.3.Company snapshot
10.3.4.Operating business segments
10.3.5.Product portfolio
10.3.6.R&D Expenditure
10.3.7.Business performance
10.3.8.Key strategic moves and developments

10.4.ORACLE CORPORATION

10.4.1.Company overview
10.4.2.Key executives
10.4.3.Company snapshot
10.4.4.Operating business segments
10.4.5.Product portfolio
10.4.6.R&D expenditure
10.4.7.Business performance
10.4.8.Key strategic moves and developments

10.5.SAP SE

10.5.1.Company overview
10.5.2.Key Executives
10.5.3.Company snapshot
10.5.4.Operating business segments
10.5.5.Product portfolio
10.5.6.R&D Expenditure
10.5.7.Business performance
10.5.8.Key strategic moves and developments

10.6.SAS INSTITUTE INC.

10.6.1.Company overview
10.6.2.Key Executives
10.6.3.Company snapshot
10.6.4.Product portfolio
10.6.5.Business performance
10.6.6.Key strategic moves and developments

10.7.SISENSE INC.

10.7.1.Company overview
10.7.2.Key Executives
10.7.3.Company snapshot
10.7.4.Product portfolio
10.7.5.Key strategic moves and developments

10.8.TERADATA CORPORATION

10.8.1.Company overview
10.8.2.Key Executives
10.8.3.Company snapshot
10.8.4.Product portfolio
10.8.5.Key strategic moves and developments

10.9.TIBCO SOFTWARE INC.

10.9.1.Company overview
10.9.2.Key Executives
10.9.3.Company snapshot
10.9.4.Product portfolio
10.9.5.Key strategic moves and developments

10.10.TABLEAU SOFTWARE

10.10.1.Company overview
10.10.2.Key Executives
10.10.3.Company snapshot
10.10.4.Product portfolio
10.10.5.R&D Expenditure
10.10.6.Business performance
10.10.7.Key strategic moves and developments

LIST OF TABLES

TABLE 01.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT, 2019–2027 ($MILLION)
TABLE 02.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR SOFTWARE, BY REGION, 2019–2027 ($MILLION)
TABLE 03.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR SERVICE, BY REGION , 2019–2027 ($MILLION)
TABLE 04.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT 2019–2027 ($MILLION)
TABLE 05.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR ON PREMISE, BY REGION, 2019–2027 ($MILLION)
TABLE 06.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR CLOUD, BY REGION, 2019–2027 ($MILLION)
TABLE 07.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE 2019–2027 ($MILLION)
TABLE 08.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR LARGE ENTERPRISES, BY REGION, 2019–2027 ($MILLION)
TABLE 09.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR SMES, BY REGION, 2019–2027 ($MILLION)
TABLE 10.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019–2027 ($MILLION)
TABLE 11.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR SALES AND MARKETING ANALYTICS, BY REGION, 2019–2027 ($MILLION)
TABLE 12.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR SUPPLY CHAIN OPERATIONS MANAGEMENT, BY REGION, 2019–2027 ($MILLION)
TABLE 13.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR MERCHANDISING ANALYTICS, BY REGION, 2019–2027 ($MILLION)
TABLE 14.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR RISK AND CUSTOMER ANALYTICS, BY REGION, 2019–2027 ($MILLION)
TABLE 15.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE FOR OTHERS, BY REGION, 2019–2027 ($MILLION)
TABLE 16.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY REGION, 2019–2027 ($MILLION)
TABLE 17.NORTH AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 18.NORTH AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 19.NORTH AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE 2019-2027 ($MILLION)
TABLE 20.NORTH AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 21.NORTH AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COUNTRY, 2019-2027 ($MILLION)
TABLE 22.U.S. BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 23.U.S. BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 24.U.S. BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 25.U.S. BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 26.CANADA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 27.CANADA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 28.CANADA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 29.CANADA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 30.EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 31.EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 32.EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE 2019-2027 ($MILLION)
TABLE 33.EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 34.EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COUNTRY, 2019-2027 ($MILLION)
TABLE 35.UK BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 36.UK BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 37.UK BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 38.UK BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 39.GERMANY BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 40.GERMANY BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 41.GERMANY BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 42.GERMANY BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 43.FRANCE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 44.FRANCE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 45.FRANCE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 46.FRANCE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 47.REST OF EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 48.REST OF EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 49.REST OF EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 50.REST OF EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 51.ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 52.ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 53.ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE 2019-2027 ($MILLION)
TABLE 54.ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 55.ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COUNTRY, 2019-2027 ($MILLION)
TABLE 56.CHINA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 57.CHINA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 58.CHINA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 59.CHINA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 60.INDIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 61.INDIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 62.INDIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 63.INDIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 64.JAPAN BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 65.JAPAN BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 66.JAPAN BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 67.JAPAN BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 68.AUSTRALIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 69.AUSTRALIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 70.AUSTRALIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 71.AUSTRALIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 72.REST OF ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 73.REST OF ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 74.REST OF ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 75.REST OF ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 76.LAMEA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 77.LAMEA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 78.LAMEA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE 2019-2027 ($MILLION)
TABLE 79.LAMEA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 80.LAMEA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COUNTRY, 2017-2025 ($MILLION)
TABLE 81.LATIN AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 82.LATIN AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 83.LATIN AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 84.LATIN AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 85.MIDDLE EAST BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 86.MIDDLE EAST BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 87.MIDDLE EAST BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 88.MIDDLE EAST BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 89.AFRICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT 2019-2027 ($MILLION)
TABLE 90.AFRICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019-2027 ($MILLION)
TABLE 91.AFRICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019-2027 ($MILLION)
TABLE 92.AFRICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019-2027 ($MILLION)
TABLE 93.KEY NEW PRODUCT LAUNCHES (2016-2019)
TABLE 94.PARTNERSHIP (2016-2019)
TABLE 95.ACQUISTION (2016-2019)
TABLE 96.PRODUCT DEVELOPMENT (2016-2019)
TABLE 97.KEY EXPANSIONS (2016-2019)
TABLE 98.COLLABORATION (2016-2019)
TABLE 99.AGREEMENT (2016-2019)
TABLE 100.ADOBE INC.: KEY EXECUTIVES
TABLE 101.ADOBE INC.: COMPANY SNAPSHOT
TABLE 102.ADOBE INC.: OPERATING SEGMENTS
TABLE 103.ADOBE INC.: PRODUCT PORTFOLIO
TABLE 104.CISCO SYSTEMS, INC.: KEY EXECUTIVES
TABLE 105.CISCO SYSTEMS, INC.: COMPANY SNAPSHOT
TABLE 106.CISCO SYSTEMS, INC.: PRODUCT PORTFOLIO
TABLE 107.INTERNATIONAL BUSINESS MACHINES CORPORATION: KEY EXECUTIVES
TABLE 108.INTERNATIONAL BUSINESS MACHINES CORPORATION: COMPANY SNAPSHOT
TABLE 109.INTERNATIONAL BUSINESS MACHINES CORPORATION: OPERATING SEGMENTS
TABLE 110.INTERNATIONAL BUSINESS MACHINES CORPORATION: PRODUCT PORTFOLIO
TABLE 111.ORACLE CORPORATION: KEY EXECUTIVES
TABLE 112.ORACLE CORPORATION: COMPANY SNAPSHOT
TABLE 113.ORACLE CORPORATION: OPERATING SEGMENTS
TABLE 114.ORACLE CORPORATION: PRODUCT PORTFOLIO
TABLE 115.ORACLE CORPORATION: KEY STRATEGIC MOVES AND DEVELOPMENTS
TABLE 116.SAP SE: KEY EXECUTIVES
TABLE 117.SAP SE: COMPANY SNAPSHOT
TABLE 118.SAP SE: OPERATING SEGMENTS
TABLE 119.SAP SE: PRODUCT PORTFOLIO
TABLE 120.SAS INSTITUTE INC.: KEY EXECUTIVES
TABLE 121.SAS INSTITUTE INC.: COMPANY SNAPSHOT
TABLE 122.SAS INSTITUTE INC.: PRODUCT PORTFOLIO
TABLE 123.SISENSE INC.: KEY EXECUTIVES
TABLE 124.SISENSE INC.: COMPANY SNAPSHOT
TABLE 125.SISENSE INC.: PRODUCT PORTFOLIO
TABLE 126.TERADATA CORPORATION: COMPANY SNAPSHOT
TABLE 127.TERADATA CORPORATION: PRODUCT PORTFOLIO
TABLE 128.TIBCO SOFTWARE INC.: KEY EXECUTIVES
TABLE 129.TIBCO SOFTWARE INC.: COMPANY SNAPSHOT
TABLE 130.TIBCO SOFTWARE INC.: PRODUCT PORTFOLIO
TABLE 131.TABLEAU SOFTWARE: KEY EXECUTIVES
TABLE 132.TABLEAU SOFTWARE: COMPANY SNAPSHOT
TABLE 133.TABLEAU SOFTWARE: PRODUCT PORTFOLIO

LIST OF FIGURES

FIGURE 01.KEY MARKET SEGMENTS
FIGURE 02.BIG DATA ANALYTICS IN RETAIL MARKET, 2019–2027
FIGURE 03.BIG DATA ANALYTICS IN RETAIL MARKET, BY REGION, 2019-2027
FIGURE 04.TOP IMPACTING FACTORS
FIGURE 05.TOP INVESTMENT POCKETS
FIGURE 06.MODERATE BARGAINING POWER OF SUPPLIERS
FIGURE 07.LOW-TO-MODERATE BARGAINING POWER OF BUYERS
FIGURE 08.LOW-TO-MODERATE THREAT OF SUBSTITUTES
FIGURE 09.MODERATE-TO-HIGH THREAT OF NEW ENTRANTS
FIGURE 10.LOW-TO-HIGH COMPETITIVE RIVALRY
FIGURE 11.BIG DATA ANALYTICS IN RETAIL ANLYTICS MARKET: KEY PLAYER POSITIONING
FIGURE 12.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY COMPONENT, 2019–2027($BILLION)
FIGURE 13.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR SOFTWARE, BY REGION,  2019 & 2027 (%)
FIGURE 14.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR SERVICE, BY REGION,  2019 & 2027 (%)
FIGURE 15.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY DEPLOYMENT, 2019–2027($BILLION)
FIGURE 16.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR ON PREMISE, BY REGION,  2019 & 2027 (%)
FIGURE 17.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR CLOUD, BY REGION, 2019 & 2027 (%)
FIGURE 18.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY ORGANIZATION SIZE, 2019–2027($BILLION)
FIGURE 19.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR LARGE ENTERPRISES, BY REGION,  2019 & 2027 (%)
FIGURE 20.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR SMES, BY REGION, 2019 & 2027 (%)
FIGURE 21.BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, BY APPLICATION, 2019–2027($BILLION)
FIGURE 22.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR SALES AND MARKETING ANALYTICS, BY REGION, 2019 & 2027 (%)
FIGURE 23.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR SUPPLY CHAIN OPERATIONS MANAGEMENT, BY REGION, 2019 & 2027 (%)
FIGURE 24.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR MERCHANDISING ANALYTICS, BY REGION, 2019 & 2027 (%)
FIGURE 25.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR CUSTOMER ANALYTICS, BY REGION, 2019 & 2027 (%)
FIGURE 26.COMPARATIVE SHARE ANALYSIS OF BIG DATA ANALYTICS IN RETAIL MARKET FOR OTHERS, BY REGION, 2019 & 2027 (%)
FIGURE 27.U.S. BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 28.CANADA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 29.UK BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 30.GERMANY BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 31.FRANCE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 32.REST OF EUROPE BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 33.CHINA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 34.INDIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 35.JAPAN BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 36.AUSTRALIA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 37.REST OF ASIA-PACIFIC BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 38.LATIN AMERICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 39.MIDDLE EAST BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 40.AFRICA BIG DATA ANALYTICS IN RETAIL MARKET REVENUE, 2019-2027 ($MILLION)
FIGURE 41.COMPETITIVE DASHBOARD
FIGURE 42.COMPETITIVE DASHBOARD
FIGURE 43.COMPETITIVE HEATMAP OF KEY PLAYERS
FIGURE 44.TOP WINNING STRATEGIES, BY YEAR, 2016-2019
FIGURE 45.TOP WINNING STRATEGIES, BY DEVELOPMENT, 2016-2019
FIGURE 46.TOP WINNING STRATEGIES, BY COMPANY, 2016-2019
FIGURE 47.R&D EXPENDITURE, 2016–2018 ($MILLION)
FIGURE 48.ADOBE INC.: REVENUE, 2016–2018 ($MILLION)
FIGURE 49.ADOBE INC.: REVENUE SHARE BY SEGMENT, 2018 (%)
FIGURE 50.ADOBE INC.: REVENUE SHARE BY REGION, 2018 (%)
FIGURE 51.R&D EXPENDITURE, 2016–2018 ($MILLION)
FIGURE 52.CISCO SYSTEMS, INC.: REVENUE, 2016–2018 ($MILLION)
FIGURE 53.CISCO SYSTEMS, INC.: REVENUE SHARE BY REGION, 2018 (%)
FIGURE 54.R&D EXPENDITURE, 2016–2018 ($MILLION)
FIGURE 55.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE, 2016–2018 ($MILLION)
FIGURE 56.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE SHARE BY SEGMENT, 2018 (%)
FIGURE 57.INTERNATIONAL BUSINESS MACHINES CORPORATION: REVENUE SHARE BY REGION, 2018 (%)
FIGURE 58.R&D EXPENDITURE, 2016–2018 ($MILLION)
FIGURE 59.ORACLE CORPORATION: REVENUE, 2016–2018 ($MILLION)
FIGURE 60.ORACLE CORPORATION: REVENUE SHARE BY SEGMENT, 2018 (%)
FIGURE 61.ORACLE CORPORATION: REVENUE SHARE BY REGION, 2018 (%)
FIGURE 62.R&D EXPENDITURE, 2016–2018 ($MILLION)
FIGURE 63.SAP SE: REVENUE, 2016–2018 ($MILLION)
FIGURE 64.SAP SE: REVENUE SHARE BY SEGMENT, 2018 (%)
FIGURE 65.SAP SE: REVENUE SHARE BY REGION, 2018 (%)
FIGURE 66.SAS INSTITUTE INC.: REVENUE, 2016–2018 ($MILLION)
FIGURE 67.TERADATA CORPORATION: KEY EXECUTIVES
FIGURE 68.R&D EXPENDITURE, 2016–2018 ($MILLION)
FIGURE 69.TABLEAU SOFTWARE: REVENUE, 2016–2018 ($MILLION)
FIGURE 70.TABLEAU SOFTWARE: REVENUE SHARE BY REGION, 2018 (%)

 
 

In accordance with several interviews that were conducted of the top level CXOs, the adoption of big data analytics in retail software has increased over time to boost the decision-making capability of the organizations and improve the business insights of the retail companies. In addition, the ability of the big data analytics in retail software to provide different opportunities for business and gain new insights to run the business efficiently is increasing its popularity among the end users. 

According to the CXOs of the leading companies, increase in economic strength of developing nations such as China, India, and others, is expected to provide lucrative opportunities for the market growth. North America is expected to dominate the market during the forecast period. Moreover, the emerging countries in Asia-Pacific and Latin America are projected to offer significant growth opportunities during the forecast period. The global players are focusing toward product development and increasing their geographical presence, owing to growing competition among local vendors in terms of features, quality, and price. In addition, these players are adopting various business strategies to enhance their product offerings and strengthen their foothold in the market.

Proliferation of smart devices, increasing internet connectivity in Europe and Asia-Pacific is further propelling the demand for predictive analytics in these regions. Moreover, surge in cloud adoption and increase in investment in big data analytics are expected to boost the growth of the predictive analytics market in the coming years. Moreover, the outbreak of the COVID-19 pandemic in 2020 has led to innovation of predictive analytics solution for combating the COVID-19 crisis and helping retail industry to form their future business strategies.   

 

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