Big data analytics has gradually emerged to be the prominent collective phenomenon in the industry, and analytics tools enable key stakeholders to translate hordes of consumer data into actionable insights. More than ever, retailers are now taking advantage of their in-store connected working environment investments to empower distribution associates and even cashiers and other staff with real-time analytics. The demand for advanced big data analytics tools has been bolstering the retail analytics market, globally. The process of retail analytics begins with gathering data from multiple sources, followed by data mining for gaining insights into business decisions in retail marketing and warehousing. Moreover, big data analytics provides an additional benefit to retailers, by enabling them to devise and test their strategies before implementation. Even consumers have an advantage of getting product insights, thereby, improving their decision process. The trend is revolutionizing the retail market.
Increased Innovations in Retail Digital Marketing Techniques
Digital marketing techniques, such as CRM, social media analytics, and content management, help in identifying the customers and provide the best strategies to approach them. Moreover, the rise of digital marketing software services offer details of the products to the customer, which plays a crucial role in redefining the purchasing preference of a majority of the target audience. In addition, big data analytics can enhance overall capabilities by generating back-end activities, such as order management, warehouse logistics, data analytics, mobile support, and tracking. The growth of the big data and Internet of Things, along with the rise in the usage of smart gadgets, is further boosting the big data analytics in retail market. For instance, companies like Amazon, EBay, and others are continuously updating the way consumers think about their services and the way they go about their daily shopping routine with the help of digital marketing techniques.
Merchandising and Supply Chain Analytics Segment may Account for a Significant Share
Merchandising and supply chain analytics are an add-on to the retail market, as they can manage the resources by planning inventory, delivery, warehousing, and demand forecasting, distribution, and scheduling to optimize the workflow. The growth in the adoption of analytics is largely fueled by technological advancements in the field of ICT, and increased market penetration of broadband and mobile devices. The primary factors adding value to the retail industry are complex processes, like packaging, order pickup schedules, delivery management, and others, which can be fed into the analytical software.
Asia-Pacific to Witness Highest Growth Rate
The major contributors to the market in the region are China and India, as the countries together account for the lion’s share of the revenue generated in the retail industry in APAC. The presence of a robust retail industry setup with rapidly prospering economies, and boasting of the largest consumer base, as compared to the Rest of the World, the market for analytics finds immense potential for deployment in the region. Other major factors driving the growth of the market in the region are the growth in consumer electronics, industrial, transportation & logistics, and other industries, which essentially make up the retail industry.
Key Developments in the Market
- May 2017 - SAP SE released ‘SAP Anywhere’, which is a cloud-based, mobile-friendly solution, specifically designed for businesses with less than USD 10 million in sales. It enables small businesses to sell wholesale or retail, B2B or B2C, and integrates with both, Amazon and eBay sales platforms.
Reasons to Purchase this Report
- Impact of opportunities offered by analytics and IoT initiatives
- Analyze various perspectives of the market with the help of Porter’s five forces analysis
- Growth of various applications, such as supply chain analytics and social media analytics
- Regional analysis of the market
- Identify the latest developments, market shares, and strategies employed by the major market players.
- 3 months analyst supports, along with the Market Estimate sheet (in excel)
- This report can be customized to meet your requirements.
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1.1 Key Deliverables of the Study
1.2 Study Assumptions
1.3 Market Definition
1.4 Key Findings of the Study
2. Research Approach and Methodology
3. Executive Summary
4. Market Dynamics
4.1 Market Overview
4.2 Factors Driving the Market
4.2.1 Increased Emphasis on Predictive Analysis
4.2.2 Increased Innovations in Retail Digitalization Techniques
4.3 Factors Restraining the Market
4.3.1 Non-Uniformity of Data
4.3.2 Lack of General Awareness and Expertise in Emerging Regions
4.4 Industry Attractiveness - Porter's Five Forces Analysis
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Consumers
4.4.3 Threat of New Entrants
4.4.4 Threat of Substitute Products or Services
4.4.5 Competitive Rivalry among Existing Competitors
5. Global Big Data Analytics in Retail Market Segmentation and Forecast
5.1 By Application
5.1.1 Merchandising & Supply Chain Analytics
5.1.2 Social Media Analytics
5.1.3 Customer Analytics
5.1.4 Operational Intelligence
5.2 By Business Type
5.2.1 Small & Medium Enterprises
5.2.2 Large-scale Organizations
5.3 By Geography
5.3.1 North America
5.3.4 Rest of the World (ROW)
6. Competitive Intelligence - Company Profiles
6.1 SAP SE
6.2 Oracle Corporation
6.3 Qlik Technologies Inc.
6.4 Zoho Corporation
6.5 IBM Corporation
6.6 Retail Next Inc.
6.7 Alteryx Inc.
6.8 Tableau Software, Inc.
6.9 Adobe Systems Incorporated
6.10 Microstrategy Inc.
6.11 Prevedere Software Inc.
6.12 Targit AS
6.13 Pentaho Corporation
6.14 ZAP Business Intelligence
6.15 Fuzzy Logix LLC
7. Investment Analysis
8. Future of Big Data Analytics in Retail Market
- SAP SE
- Oracle Corporation
- Qlik Technologies Inc.
- Zoho Corporation
- IBM Corporation
- Retail Next Inc.
- Alteryx Inc.
- Tableau Software Inc.
- Adobe Systems Incorporated
- Microstrategy Inc.
- Pentaho Corporation
- ZAP Business Intelligence
- Fuzzy Logi.