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Big Data Analytics in Retail Market by Component, Deployment Type, Organization Size, Application and Region: Industry Analysis and Forecast 2020-2026

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    Report

  • 287 Pages
  • September 2020
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5174650
The Global Big Data Analytics in Retail Market size is expected to reach $14.1 billion by 2026, rising at a market growth of 23.4% CAGR during the forecast period.

Big data describes a huge volume of data that is utilized to uncover trends, patterns, and associations, particularly related to the behavior and interactions of humans. For the retail business, big data is utilized for getting a prominent understanding of customer shopping propensities and how to draw in new customers. Organizations are being enabled and empowered by big data analytics to create customer proposals dependent on their buying history, resulting in customized shopping experiences. These big data analytics solutions additionally help in anticipating patterns and taking strategic decisions that are based on an analysis of the market.

Increment in spending on big data analytics instruments, growth in need to deliver customized user experience to expand sales, and increment in development of the e-commerce sector is a portion of the main components that are boosting the development of the global market. However, issues in gathering and combining the data from different frameworks and difficulties in capturing user information are foreseen to confine the big data analytics in retail market development. On the other hand, integration of new advancements, for example, IoT, AI, and machine learning in big data analytics in retail, and growth in demand for prescient analytics in retail are foreseen to give profitable growth opportunities to the worldwide big data analytics in the retail market during the analysis period.

The episode of COVID-19 is foreseen to trivially affect the development of big data analytics in the retail market. Even though the retail industry is significantly hit by lockdown forced in numerous nations, the spending on big data analytics by retail organizations is anticipated to be maintained as planned according to the research and study led by Sisense. The retail industry is observing diverging patterns for essential and non-essential retail products in most of the nations, especially in nations, for example, the U.S., and India, which are the most influenced by the pandemic.

Based on Component, the market is segmented into Software and Services. Based on Deployment Type, the market is segmented into On-premise and Cloud. Based on Organization Size, the market is segmented into Large Enterprises and Small & Medium Enterprises. Based on Application, the market is segmented into Supply Chain Operations Management, Sales & Marketing Analytics, Customer Analytics, Merchandising Analytics, and Others. Based on Regions, the market is segmented into North America, Europe, Asia-Pacific, and Latin America, Middle East & Africa.

The major strategies followed by the market participants are Partnerships and Product Launches. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation, IBM Corporation, and Oracle Corporation are the forerunners in the Big Data Analytics in Retail Market. Companies such as Salesforce.com, Inc., Alteryx, Inc., and Adobe, Inc., Teradata Corporation, SAP SE, Zoho Corporation Pvt. Ltd., and MicroStrategy, Inc. are some of the key innovators in the market.

The market research report covers the analysis of key stakeholders of the market. Key companies profiled in the report include IBM Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, Salesforce.com, Inc., Adobe, Inc., Teradata Corporation, MicroStrategy, Inc., Alteryx, Inc., and Zoho Corporation Pvt. Ltd.

Recent Strategies Deployed in Big Data Analytics in Retail Market

Partnerships, Collaborations, and Agreements
  • Jun-2020: Teradata came into partnership with dotData, a leader in full-cycle data science automation and operationalization for the enterprise. The partnership aimed to use the robust enterprise data management and analytic capabilities of Teradata’s Vantage platform and dotData’s autoML 2.0 platforms for creating a powerful end-to-end data science solution, from data collection and preparation through feature engineering to machine learning operationalization. The partnership streamlined and simplified the movement of data between Teradata and dotData to help the companies’ joint customers derive more value from their AI and machine learning initiatives.
  • Mar-2020: SAP announced its partnership with Wipro, an India-based IT, consulting, and business process Services Company. Together, the companies have been working on new software products and co-developing solutions for the fashion and wider retail industry. The companies is expected to develop new tools for retailers to better manage business processes and customer experience.
  • Feb-2020: Microsoft announced a partnership with Myntra, a lifestyle brand. The partnership is expected to accelerate digital transformation and provides a better experience to its customers. Myntra is applying advanced analytics and machine learning to gain a comprehensive understanding of customers and deliver personalized products, marketing, and service for the customers.
  • Jan-2020: Microsoft entered into a partnership with dunnhumby, the leader in customer data science. Under this partnership, the latter company is expected to move its widely-used customer insights products to Azure, Microsoft’s cloud platform, providing retailers and suppliers’ instant and secure access to dunnhumby’s customer data science tools. The partnership aims to enable more retailers and their suppliers to gain deep shopper and business insights, better understand their customers’ needs and preferences, and improve collaboration.
  • Dec-2019: SAP SE together with Accenture, launched NewsPage 9. This solution was launched for the Asia-Pacific and African regions. NewsPage 9 uses SAP Cloud Platform and SAP HANA services, for delivering an integrated view of consumer trends, secondary demand, and supply chain management signals.
  • Oct-2019: SAP SE extended its partnership with an international retail application specialist, GK Software SE, for delivering industry-specific solutions. The partnership has been demonstrated through nearly 100 joint projects around the world. The companies were focused on new trends and innovations in cloud technologies, experience management, artificial intelligence, and mobile applications within the retail sector.
  • Oct-2019: Teradata teamed up with Google Cloud following which Teradata Vantage is available on Google Cloud. The collaboration expanded Teradata’s cloud reach to all three leading public cloud companies, offering its customers greater flexibility. Adding Google Cloud Platform to the global footprint already offered by Teradata provides customers with unrivaled choice and flexibility with how and where they use Teradata Vantage.
  • Oct-2019: MicroStrategy announced a technology partnership with DataRobot, a leader in enterprise artificial intelligence (AI). The partnership was aimed to make it easier for businesses to integrate AI into their most popular applications and core processes by using HyperIntelligence cards to deliver AI-driven insights and recommendations. HyperIntelligence seamlessly administers trusted and predictive analytics directly into popular business applications on both web and mobile, including Google’s G Suite, Microsoft Office 365, and SaaS applications such as Salesforce, Workday, and Confluence, making it possible to instantly reveal insights to users without interrupting their existing workflows.
  • May-2019: Adobe signed a partnership agreement with Software AG, an enterprise software company. The partnership was aimed at helping companies in transforming their customer experience management (CXM) by bringing together customer data from across multiple enterprise systems into a centralized and actionable real-time customer profile.
  • Apr-2019: IBM collaborated with The Fashion Institute of Technology’s (FIT) FIT/Infor Design and Technology Lab. The collaboration was focused on transforming how the fashion industry operates and helped in building the creative fashion workforce of the future. FIT has been using IBM’s artificial intelligence (AI) for fashion capabilities, a suite of application programming interfaces (APIs) developed and trained for the fashion industry. The suite leverages deep learning, natural language processing, and computer vision to help fashion companies improve customer experience, enhance their product design, development, and merchandising/planning activities, and augment merchandise performance analysis.

Acquisitions and Mergers
  • Feb-2020: Salesforce took over Evergage, a provider of personalization and customer data platform. The real-time, cross-channel personalization and machine learning capabilities of Evergage complement Salesforce Marketing Cloud’s robust customer data, audience segmentation, and engagement platform, allowing companies to deliver more relevant experiences during moments of interaction across the entire customer journey.
  • Aug-2019: Salesforce completed the acquisition of Tableau Software. Together, the companies aimed to transform the way people understand not only their customers but their whole world by providing powerful AI-driven insights across all types of data and use cases for people of every skill level.
  • Apr-2019: Alteryx, Inc. took over ClearStory Data, an enterprise-scale, continuous intelligence analytics solution for complex and unstructured data. The acquisition enabled Alteryx to provide an end-to-end, self-service data science and analytics platform that fuels remarkable business and social outcomes.

Product Launches and Product Enhancements
  • Jul-2020: IBM launched Watson Advertising Social Targeting with Influential, a new solution that uses artificial intelligence (AI) to help brands identify influencers that best align with their brand values. The new solution within the Watson Advertising suite of targeting products is the result of IBM's expanded collaboration with Influential, a leader in advanced social media technology. The social targeting tool helps brands communicate with an audience. The solution uses IBM Watson Natural Language Understanding on the IBM public cloud to process and analyze social media data to help expedite influencer identification.
  • Mar-2020: Adobe made enhancements to its Experience Platform. This platform integrates data silos and offers more tools to analyze customer data. This is expected to allow data to be collected from the web and mobile channels with the use of a single JavaScript library tied to the first party domain for all Adobe products.
  • Jan-2020: Oracle Retail unveiled Consumer Insights for helping the retail marketers use enriched customer data attributes alongside third-party consumer data from Oracle Data Cloud to find prospective lookalike customers. Oracle Cloud provides data sets composed of profile-based, transaction-level data along with other demographic attributes.
  • Nov-2019: Oracle launched two new solutions, the Digital Sales Solution and its customer data management (CDM) platform for Oracle Service Cloud. The Digital Sales Solution is the latest addition to the Oracle Customer Experience (CX) Cloud suite and has a new user interface for helping sales representatives in recognizing and qualifying good opportunities. The new solution also seeks to help sales representatives save time by reducing the number of fields needed to find and update customer relationship management (CRM) records.
  • Nov-2019: Salesforce introduced Customer 360 Truth, a new set of data and identity services. These services help the companies in building a single source of truth across all of their customer relationships. Customer 360 Truth connects data from across sales, service, marketing, commerce, and more to create a single, universal Salesforce ID for each customer. All of a customer’s previous interactions and shared preferences are brought together to create a complete view so companies can better serve and even predict their needs.
  • Oct-2019: Teradata released Vantage Customer Experience (CX) for transforming the customer experience at the world’s most innovative data-driven companies. Vantage CX helps brands in delivering relevant, personalized experiences in real-time, across all interactions, to drive incremental revenue and lower the cost-to-serve. Teradata also launched Vantage Analyst: a set of capabilities for Vantage customers, which empowers business analysts to perform machine learning and advanced analytics.
  • Sep-2019: Oracle made upgradation to the Oracle Customer Experience (CX) Cloud. The updates include digital assistants for sales, customer service, and marketing; data-enriched B2B sales capabilities. The updates to Oracle CX Cloud are fueled by data and machine learning for helping the customers in taking the advantage of powerful data insights to get ahead of customer needs and ensure a positive, unforgettable customer experience.
  • Sep-2019: Adobe launched Customer Journey Analytics in Adobe Analytics. It uses the power of Adobe Experience Platform, which standardizes and stitches together customer data from across an organization and opens up new creative ways to understand insights across online, offline, and third-party channels.
  • Sep-2019: Zoho introduced Zoho One, the operating system for businesses. This system has been designed for running the entire organization from marketing, sales, finance, and HR to operations and business intelligence.
  • May-2019: IBM introduced the Business Transactional Intelligence (BTI) solution. This solution is powered by artificial intelligence for providing anomaly detection and visualization capabilities for mitigating supply chain disruptions and accelerating data-driven decision making. BTI was designed to enable companies to use deeper insights into supply chain data to help them better manage their businesses.

Market Segmentation

By Component
  • Software
  • Services

By Deployment Type
  • On-premise
  • Cloud

By Organization Size
  • Large Enterprises
  • Small & Medium Enterprises

By Application
  • Supply Chain Operations Management
  • Sales & Marketing Analytics
  • Customer Analytics
  • Merchandising Analytics
  • Others

By Geography
  • North America
  • Europe
  • Asia-Pacific
  • LAMEA

Companies Profiled
  • IBM Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • SAP SE
  • Salesforce.com, Inc.
  • Adobe, Inc.
  • Teradata Corporation
  • MicroStrategy, Inc.
  • Alteryx, Inc.
  • Zoho Corporation Pvt. Ltd.

Unique Offerings
  • Exhaustive coverage
  • Highest number of market tables and figures
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  • Assured post sales research support with 10% customization free

Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Big Data Analytics in Retail Market, by Component
1.4.2 Global Big Data Analytics in Retail Market, by Deployment Type
1.4.3 Global Big Data Analytics in Retail Market, by Organization Size
1.4.4 Global Big Data Analytics in Retail Market, by Application
1.4.5 Global Big Data Analytics in Retail Market, by Geography
1.5 Methodology for the Research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.2 Executive Summary
2.1.3 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Enhancements
3.2.3 Geographical Expansions
3.2.4 Mergers & Acquisitions
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2016-2020)
3.3.2 Key Strategic Moves: (Partnerships, Collaborations, and Agreements: 2016, Aug to 2020, Jun) Leading Players
3.3.3 Key Strategic Moves: (Product Launches and Product Enhancements: 2017, Jan to 2020, Jul) Leading Players
Chapter 4. Global Big Data Analytics in Retail Market by Component
4.1 Global Big Data Analytics in Retail Software Market by Region
4.2 Global Big Data Analytics in Retail Services Market by Region
Chapter 5. Global Big Data Analytics in Retail Market by Deployment Type
5.1 Global On-premise Big Data Analytics in Retail Market by Region
5.2 Global Cloud Big Data Analytics in Retail Market by Region
Chapter 6. Global Big Data Analytics in Retail Market by Organization Size
6.1 Global Large Enterprises Big Data Analytics in Retail Market by Region
6.2 Global Small & Medium Enterprises Big Data Analytics in Retail Market by Region
Chapter 7. Global Big Data Analytics in Retail Market by Application
7.1 Global Supply Chain Operations Management Big Data Analytics in Retail Market by Region
7.2 Global Sales & Marketing Analytics Big Data Analytics in Retail Market by Region
7.3 Global Customer Analytics Big Data Analytics in Retail Market by Region
7.4 Global Merchandising Analytics Big Data Analytics in Retail Market by Region
7.5 Global Others Big Data Analytics in Retail Market by Region
Chapter 8. Global Big Data Analytics in Retail Market by Region
8.1 North America Big Data Analytics in Retail Market
8.1.1 North America Big Data Analytics in Retail Market by Component
8.1.1.1 North America Big Data Analytics in Retail Software Market by Country
8.1.1.2 North America Big Data Analytics in Retail Services Market by Country
8.1.2 North America Big Data Analytics in Retail Market by Deployment Type
8.1.2.1 North America On-premise Big Data Analytics in Retail Market by Country
8.1.2.2 North America Cloud Big Data Analytics in Retail Market by Country
8.1.3 North America Big Data Analytics in Retail Market by Organization Size
8.1.3.1 North America Large Enterprises Big Data Analytics in Retail Market by Country
8.1.3.2 North America Small & Medium Enterprises Big Data Analytics in Retail Market by Country
8.1.4 North America Big Data Analytics in Retail Market by Application
8.1.4.1 North America Supply Chain Operations Management Big Data Analytics in Retail Market by Country
8.1.4.2 North America Sales & Marketing Analytics Big Data Analytics in Retail Market by Country
8.1.4.3 North America Customer Analytics Big Data Analytics in Retail Market by Country
8.1.4.4 North America Merchandising Analytics Big Data Analytics in Retail Market by Country
8.1.4.5 North America Others Big Data Analytics in Retail Market by Country
8.1.5 North America Big Data Analytics in Retail Market by Country
8.1.5.1 US Big Data Analytics in Retail Market
8.1.5.1.1 US Big Data Analytics in Retail Market by Component
8.1.5.1.2 US Big Data Analytics in Retail Market by Deployment Type
8.1.5.1.3 US Big Data Analytics in Retail Market by Organization Size
8.1.5.1.4 US Big Data Analytics in Retail Market by Application
8.1.5.2 Canada Big Data Analytics in Retail Market
8.1.5.2.1 Canada Big Data Analytics in Retail Market by Component
8.1.5.2.2 Canada Big Data Analytics in Retail Market by Deployment Type
8.1.5.2.3 Canada Big Data Analytics in Retail Market by Organization Size
8.1.5.2.4 Canada Big Data Analytics in Retail Market by Application
8.1.5.3 Mexico Big Data Analytics in Retail Market
8.1.5.3.1 Mexico Big Data Analytics in Retail Market by Component
8.1.5.3.2 Mexico Big Data Analytics in Retail Market by Deployment Type
8.1.5.3.3 Mexico Big Data Analytics in Retail Market by Organization Size
8.1.5.3.4 Mexico Big Data Analytics in Retail Market by Application
8.1.5.4 Rest of North America Big Data Analytics in Retail Market
8.1.5.4.1 Rest of North America Big Data Analytics in Retail Market by Component
8.1.5.4.2 Rest of North America Big Data Analytics in Retail Market by Deployment Type
8.1.5.4.3 Rest of North America Big Data Analytics in Retail Market by Organization Size
8.1.5.4.4 Rest of North America Big Data Analytics in Retail Market by Application
8.2 Europe Big Data Analytics in Retail Market
8.2.1 Europe Big Data Analytics in Retail Market by Component
8.2.1.1 Europe Big Data Analytics in Retail Software Market by Country
8.2.1.2 Europe Big Data Analytics in Retail Services Market by Country
8.2.2 Europe Big Data Analytics in Retail Market by Deployment Type
8.2.2.1 Europe On-premise Big Data Analytics in Retail Market by Country
8.2.2.2 Europe Cloud Big Data Analytics in Retail Market by Country
8.2.3 Europe Big Data Analytics in Retail Market by Organization Size
8.2.3.1 Europe Large Enterprises Big Data Analytics in Retail Market by Country
8.2.3.2 Europe Small & Medium Enterprises Big Data Analytics in Retail Market by Country
8.2.4 Europe Big Data Analytics in Retail Market by Application
8.2.4.1 Europe Supply Chain Operations Management Big Data Analytics in Retail Market by Country
8.2.4.2 Europe Sales & Marketing Analytics Big Data Analytics in Retail Market by Country
8.2.4.3 Europe Customer Analytics Big Data Analytics in Retail Market by Country
8.2.4.4 Europe Merchandising Analytics Big Data Analytics in Retail Market by Country
8.2.4.5 Europe Others Big Data Analytics in Retail Market by Country
8.2.5 Europe Big Data Analytics in Retail Market by Country
8.2.5.1 Germany Big Data Analytics in Retail Market
8.2.5.1.1 Germany Big Data Analytics in Retail Market by Component
8.2.5.1.2 Germany Big Data Analytics in Retail Market by Deployment Type
8.2.5.1.3 Germany Big Data Analytics in Retail Market by Organization Size
8.2.5.1.4 Germany Big Data Analytics in Retail Market by Application
8.2.5.2 UK Big Data Analytics in Retail Market
8.2.5.2.1 UK Big Data Analytics in Retail Market by Component
8.2.5.2.2 UK Big Data Analytics in Retail Market by Deployment Type
8.2.5.2.3 UK Big Data Analytics in Retail Market by Organization Size
8.2.5.2.4 UK Big Data Analytics in Retail Market by Application
8.2.5.3 France Big Data Analytics in Retail Market
8.2.5.3.1 France Big Data Analytics in Retail Market by Component
8.2.5.3.2 France Big Data Analytics in Retail Market by Deployment Type
8.2.5.3.3 France Big Data Analytics in Retail Market by Organization Size
8.2.5.3.4 France Big Data Analytics in Retail Market by Application
8.2.5.4 Russia Big Data Analytics in Retail Market
8.2.5.4.1 Russia Big Data Analytics in Retail Market by Component
8.2.5.4.2 Russia Big Data Analytics in Retail Market by Deployment Type
8.2.5.4.3 Russia Big Data Analytics in Retail Market by Organization Size
8.2.5.4.4 Russia Big Data Analytics in Retail Market by Application
8.2.5.5 Spain Big Data Analytics in Retail Market
8.2.5.5.1 Spain Big Data Analytics in Retail Market by Component
8.2.5.5.2 Spain Big Data Analytics in Retail Market by Deployment Type
8.2.5.5.3 Spain Big Data Analytics in Retail Market by Organization Size
8.2.5.5.4 Spain Big Data Analytics in Retail Market by Application
8.2.5.6 Italy Big Data Analytics in Retail Market
8.2.5.6.1 Italy Big Data Analytics in Retail Market by Component
8.2.5.6.2 Italy Big Data Analytics in Retail Market by Deployment Type
8.2.5.6.3 Italy Big Data Analytics in Retail Market by Organization Size
8.2.5.6.4 Italy Big Data Analytics in Retail Market by Application
8.2.5.7 Rest of Europe Big Data Analytics in Retail Market
8.2.5.7.1 Rest of Europe Big Data Analytics in Retail Market by Component
8.2.5.7.2 Rest of Europe Big Data Analytics in Retail Market by Deployment Type
8.2.5.7.3 Rest of Europe Big Data Analytics in Retail Market by Organization Size
8.2.5.7.4 Rest of Europe Big Data Analytics in Retail Market by Application
8.3 Asia-Pacific Big Data Analytics in Retail Market
8.3.1 Asia-Pacific Big Data Analytics in Retail Market by Component
8.3.1.1 Asia-Pacific Big Data Analytics in Retail Software Market by Country
8.3.1.2 Asia-Pacific Big Data Analytics in Retail Services Market by Country
8.3.2 Asia-Pacific Big Data Analytics in Retail Market by Deployment Type
8.3.2.1 Asia-Pacific On-premise Big Data Analytics in Retail Market by Country
8.3.2.2 Asia-Pacific Cloud Big Data Analytics in Retail Market by Country
8.3.3 Asia-Pacific Big Data Analytics in Retail Market by Organization Size
8.3.3.1 Asia-Pacific Large Enterprises Big Data Analytics in Retail Market by Country
8.3.3.2 Asia-Pacific Small & Medium Enterprises Big Data Analytics in Retail Market by Country
8.3.4 Asia-Pacific Big Data Analytics in Retail Market by Application
8.3.4.1 Asia-Pacific Supply Chain Operations Management Big Data Analytics in Retail Market by Country
8.3.4.2 Asia-Pacific Sales & Marketing Analytics Big Data Analytics in Retail Market by Country
8.3.4.3 Asia-Pacific Customer Analytics Big Data Analytics in Retail Market by Country
8.3.4.4 Asia-Pacific Merchandising Analytics Big Data Analytics in Retail Market by Country
8.3.4.5 Asia-Pacific Others Big Data Analytics in Retail Market by Country
8.3.5 Asia-Pacific Big Data Analytics in Retail Market by Country
8.3.5.1 China Big Data Analytics in Retail Market
8.3.5.1.1 China Big Data Analytics in Retail Market by Component
8.3.5.1.2 China Big Data Analytics in Retail Market by Deployment Type
8.3.5.1.3 China Big Data Analytics in Retail Market by Organization Size
8.3.5.1.4 China Big Data Analytics in Retail Market by Application
8.3.5.2 Japan Big Data Analytics in Retail Market
8.3.5.2.1 Japan Big Data Analytics in Retail Market by Component
8.3.5.2.2 Japan Big Data Analytics in Retail Market by Deployment Type
8.3.5.2.3 Japan Big Data Analytics in Retail Market by Organization Size
8.3.5.2.4 Japan Big Data Analytics in Retail Market by Application
8.3.5.3 India Big Data Analytics in Retail Market
8.3.5.3.1 India Big Data Analytics in Retail Market by Component
8.3.5.3.2 India Big Data Analytics in Retail Market by Deployment Type
8.3.5.3.3 India Big Data Analytics in Retail Market by Organization Size
8.3.5.3.4 India Big Data Analytics in Retail Market by Application
8.3.5.4 South Korea Big Data Analytics in Retail Market
8.3.5.4.1 South Korea Big Data Analytics in Retail Market by Component
8.3.5.4.2 South Korea Big Data Analytics in Retail Market by Deployment Type
8.3.5.4.3 South Korea Big Data Analytics in Retail Market by Organization Size
8.3.5.4.4 South Korea Big Data Analytics in Retail Market by Application
8.3.5.5 Singapore Big Data Analytics in Retail Market
8.3.5.5.1 Singapore Big Data Analytics in Retail Market by Component
8.3.5.5.2 Singapore Big Data Analytics in Retail Market by Deployment Type
8.3.5.5.3 Singapore Big Data Analytics in Retail Market by Organization Size
8.3.5.5.4 Singapore Big Data Analytics in Retail Market by Application
8.3.5.6 Malaysia Big Data Analytics in Retail Market
8.3.5.6.1 Malaysia Big Data Analytics in Retail Market by Component
8.3.5.6.2 Malaysia Big Data Analytics in Retail Market by Deployment Type
8.3.5.6.3 Malaysia Big Data Analytics in Retail Market by Organization Size
8.3.5.6.4 Malaysia Big Data Analytics in Retail Market by Application
8.3.5.7 Rest of Asia-Pacific Big Data Analytics in Retail Market
8.3.5.7.1 Rest of Asia-Pacific Big Data Analytics in Retail Market by Component
8.3.5.7.2 Rest of Asia-Pacific Big Data Analytics in Retail Market by Deployment Type
8.3.5.7.3 Rest of Asia-Pacific Big Data Analytics in Retail Market by Organization Size
8.3.5.7.4 Rest of Asia-Pacific Big Data Analytics in Retail Market by Application
8.4 LAMEA Big Data Analytics in Retail Market
8.4.1 LAMEA Big Data Analytics in Retail Market by Component
8.4.1.1 LAMEA Big Data Analytics in Retail Software Market by Country
8.4.1.2 LAMEA Big Data Analytics in Retail Services Market by Country
8.4.2 LAMEA Big Data Analytics in Retail Market by Deployment Type
8.4.2.1 LAMEA On-premise Big Data Analytics in Retail Market by Country
8.4.2.2 LAMEA Cloud Big Data Analytics in Retail Market by Country
8.4.3 LAMEA Big Data Analytics in Retail Market by Organization Size
8.4.3.1 LAMEA Large Enterprises Big Data Analytics in Retail Market by Country
8.4.3.2 LAMEA Small & Medium Enterprises Big Data Analytics in Retail Market by Country
8.4.4 LAMEA Big Data Analytics in Retail Market by Application
8.4.4.1 LAMEA Supply Chain Operations Management Big Data Analytics in Retail Market by Country
8.4.4.2 LAMEA Sales & Marketing Analytics Big Data Analytics in Retail Market by Country
8.4.4.3 LAMEA Customer Analytics Big Data Analytics in Retail Market by Country
8.4.4.4 LAMEA Merchandising Analytics Big Data Analytics in Retail Market by Country
8.4.4.5 LAMEA Others Big Data Analytics in Retail Market by Country
8.4.5 LAMEA Big Data Analytics in Retail Market by Country
8.4.5.1 Brazil Big Data Analytics in Retail Market
8.4.5.1.1 Brazil Big Data Analytics in Retail Market by Component
8.4.5.1.2 Brazil Big Data Analytics in Retail Market by Deployment Type
8.4.5.1.3 Brazil Big Data Analytics in Retail Market by Organization Size
8.4.5.1.4 Brazil Big Data Analytics in Retail Market by Application
8.4.5.2 Argentina Big Data Analytics in Retail Market
8.4.5.2.1 Argentina Big Data Analytics in Retail Market by Component
8.4.5.2.2 Argentina Big Data Analytics in Retail Market by Deployment Type
8.4.5.2.3 Argentina Big Data Analytics in Retail Market by Organization Size
8.4.5.2.4 Argentina Big Data Analytics in Retail Market by Application
8.4.5.3 UAE Big Data Analytics in Retail Market
8.4.5.3.1 UAE Big Data Analytics in Retail Market by Component
8.4.5.3.2 UAE Big Data Analytics in Retail Market by Deployment Type
8.4.5.3.3 UAE Big Data Analytics in Retail Market by Organization Size
8.4.5.3.4 UAE Big Data Analytics in Retail Market by Application
8.4.5.4 Saudi Arabia Big Data Analytics in Retail Market
8.4.5.4.1 Saudi Arabia Big Data Analytics in Retail Market by Component
8.4.5.4.2 Saudi Arabia Big Data Analytics in Retail Market by Deployment Type
8.4.5.4.3 Saudi Arabia Big Data Analytics in Retail Market by Organization Size
8.4.5.4.4 Saudi Arabia Big Data Analytics in Retail Market by Application
8.4.5.5 South Africa Big Data Analytics in Retail Market
8.4.5.5.1 South Africa Big Data Analytics in Retail Market by Component
8.4.5.5.2 South Africa Big Data Analytics in Retail Market by Deployment Type
8.4.5.5.3 South Africa Big Data Analytics in Retail Market by Organization Size
8.4.5.5.4 South Africa Big Data Analytics in Retail Market by Application
8.4.5.6 Nigeria Big Data Analytics in Retail Market
8.4.5.6.1 Nigeria Big Data Analytics in Retail Market by Component
8.4.5.6.2 Nigeria Big Data Analytics in Retail Market by Deployment Type
8.4.5.6.3 Nigeria Big Data Analytics in Retail Market by Organization Size
8.4.5.6.4 Nigeria Big Data Analytics in Retail Market by Application
8.4.5.7 Rest of LAMEA Big Data Analytics in Retail Market
8.4.5.7.1 Rest of LAMEA Big Data Analytics in Retail Market by Component
8.4.5.7.2 Rest of LAMEA Big Data Analytics in Retail Market by Deployment Type
8.4.5.7.3 Rest of LAMEA Big Data Analytics in Retail Market by Organization Size
8.4.5.7.4 Rest of LAMEA Big Data Analytics in Retail Market by Application
Chapter 9. Company Profiles
9.1 IBM Corporation
9.1.1 Company Overview
9.1.2 Financial Analysis
9.1.3 Regional & Segmental Analysis
9.1.4 Research & Development Expenses
9.1.5 Recent Strategies and Developments
9.1.5.1 Partnerships, Collaborations, and Agreements
9.1.5.2 Product Launches and Product Enhancements
9.1.6 SWOT Analysis
9.2 Microsoft Corporation
9.2.1 Company Overview
9.2.2 Financial Analysis
9.2.3 Segmental and Regional Analysis
9.2.4 Research & Development Expenses
9.2.1 Recent Strategies and Developments
9.2.1.1 Partnerships, Collaborations, and Agreements
9.2.2 SWOT Analysis
9.3 Oracle Corporation
9.3.1 Company Overview
9.3.2 Financial Analysis
9.3.3 Segmental and Regional Analysis
9.3.4 Research & Development Expenses
9.3.5 Recent Strategies and Developments
9.3.5.1 Product Launches and Product Enhancements
9.3.6 SWOT Analysis
9.4 SAP SE
9.4.1 Company Overview
9.4.2 Financial Analysis
9.4.3 Segmental and Regional Analysis
9.4.4 Research & Development Expenses
9.4.5 Recent Strategies and Developments
9.4.5.1 Partnerships, Collaborations, and Agreements
9.4.5.2 Product Launches and Product Enhancements
9.4.5.3 Geographical Expansions
9.4.6 SWOT Analysis
9.5 Salesforce.com, Inc.
9.5.1 Company Overview
9.5.2 Financial Analysis
9.5.3 Regional Analysis
9.5.4 Research & Development Expenses
9.5.5 Recent Strategies and Developments
9.5.5.1 Acquisition and Mergers
9.5.5.2 Product Launches and Product Enhancements
9.5.6 SWOT Analysis
9.6 Adobe, Inc.
9.6.1 Company Overview
9.6.2 Financial Analysis
9.6.3 Segmental and Regional Analysis
9.6.4 Research & Development Expenses
9.6.5 Recent Strategies and Developments
9.6.5.1 Partnerships, Collaborations, and Agreements
9.6.5.2 Product Launches and Product Enhancements
9.6.6 SWOT Analysis
9.7 Teradata Corporation
9.7.1 Company Overview
9.7.2 Financial Analysis
9.7.3 Regional Analysis
9.7.4 Research & Development Expenses
9.7.5 Recent Strategies and Developments
9.7.5.1 Partnerships, Collaborations, and Agreements
9.7.5.2 Product Launches and Product Enhancements
9.7.6 SWOT Analysis
9.8 MicroStrategy, Inc.
9.8.1 Company Overview
9.8.2 Financial Analysis
9.8.3 Regional Analysis
9.8.4 Research & Development Expenses
9.8.5 Recent Strategies and Developments
9.8.5.1 Partnerships, Collaborations, and Agreements
9.8.5.2 Product Launches and Product Enhancements
9.8.6 SWOT Analysis
9.9 Alteryx, Inc.
9.9.1 Company Overview
9.9.2 Financial Analysis
9.9.3 Regional Analysis
9.9.4 Research & Development Expenses
9.9.5 Recent Strategies and Developments
9.9.5.1 Partnerships, Collaborations, and Agreements
9.9.5.2 Product Launches and Product Enhancements
9.9.5.3 Acquisition and Mergers
9.10. Zoho Corporation Pvt. Ltd.
9.10.1 Company Overview
9.10.2 Recent Strategies and Developments
9.10.2.1 Product Launches and Product Enhancements

Companies Mentioned

  • IBM Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • SAP SE
  • Salesforce.com, Inc.
  • Adobe, Inc.
  • Teradata Corporation
  • MicroStrategy, Inc.
  • Alteryx, Inc.
  • Zoho Corporation Pvt. Ltd.

Methodology

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