Big Data in Retail: Opportunities and Challenges – Gaining competitive advantage through better understanding retailers’ business and IT priorities

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"Big Data in Retail: Opportunities and Challenges", report discusses retailers' Big Data and analytics related business and technology challenges, and provides a market forecast until 2020 by retail and IT segments. The report analyzes various approaches to analytics, data management and provides advice on how to generate value from data-driven solutions.

Big Data and Analytics provide substantial opportunities for retailers since they already have a wealth of data that can be used for analytics to optimize processes, increase sales and launch new services. Detailed customer profiles can be built on Big Data, cost savings achieved through supply chain efficiencies and superior customer experience offered, which can lift the brand image. Big data solutions allow that data from individual stores can be compared with figures and insight gathered from eCommerce operations, interactive customer apps and log data from systems and sensors across the organization. Social media and socio-economic data can also be integrated into the analysis, as well as input from warehouses and suppliers.

Scope

– The fast-growing market for various Big Data and analytics solutions in retail provides hardware and software vendors, as well as cloud service providers, systems integrators, and consultancies with notable business opportunities

– Most of the hardware innovations that are currently happening in retail such as various IoT solutions have an analytics element that helps to better understand customer behavior and market trends, and optimize various processes from warehouse management and staffing to store traffic and eCommerce websites

– Retailers feel the pressure from competitors advancing in their usage of data for better targeting customers and look to improve their brand image, marketing efforts and operational efficiency

Reasons to Buy

– Gain insight into retailers' Big Data and analytics related priorities. This reports helps you to pitch Big Data and analytics solutions to retailers and understand how these are linked to key business systems, as well as the role that Big Data plays in innovative retail concepts.

Macy's
John Lewis
Marks and Spencer
Cloudera
Spotfire
Splunk

Table of Contents

Table of Contents

1. Background: Retailers’ Business Challenges 3

2. Analytics Opportunities and Technologies 5

2.1 Analytics in Store 5

2.2 Back-end Analytics 6

2.3 Business Intelligence Technologies 8

2.4 Data Collection Technologies 10

2.5 Data Processing and Data Centre Infrastructure Technologies 11

2.6 Vendor Overview 13

3. Retailer Usage Cases 16

3.1 Macy’s 360 degrees view of its customers 16

3.2 M&S runs analytics on Hadoop and uses visualization tools 16

3.3 John Lewis relies on real-time operational insights 17

4. Implementing Big Data Strategies in Retail 18

4.1 Big Data Opportunities 19

4.2 Key Challenges 20

5. Market Opportunity 24

5.1 Big Data in Retail – Global Market by Technology 24

5.2 Big data in retail – Global Market by Retail Segment 27

5.3 Big data in retail – global market by retail channel 29

6. Future of Big Data in Retail 31

6.1 Latest Technologies 31

6.2 Retailers’ IT budget allocation and IT priorities 32

6.3 Opportunities for ICT vendors 35

7. Advice for ICT Vendors and Retailers 37

7.1 Advice for ICT Vendors 37

7.2 Advice for Retailers 38

8. Appendix 39

8.1 Definitions 39

8.2 Further Reading 42

8.3 Contact the author 42

8.4 Contact Us . 43

Table

List of Tables

Table 1: Global market for big data in retail by technology – spending in US$m 24

Table 2: Global market for big data software in retail by technology – spending in US$m 25

Table 3: Software and services driving big data growth in retail (US$m) 26

Table 4: Global market for big data technology by retail segment (US$m) 28

Table 5: Global market for big data technology by retail segment (US$m) 30

Table 6: Key demand and supply side trends driving big data in retail 33

Table 7: Retail categories 39

Table 8: Retail channels 40

Table 9: IT Domains (1) 40

Table 10: IT Domains (2) 41

Figures

List of Figures

Figure 1: Business Intelligence Technologies 9

Figure 2: Big Data Software and Hardware Stacks 14

Figure 3: Retail data sources and flow 19

Figure 4: Key business challenges impacting retailers in adopting big data & analytics 21

Figure 5: Software and services driving big data growth in retail (US$m) 26

Figure 6: Global market for big data technology by retail segment – spending in US$m 27

Figure 7: Technology adoption curve by retailer type and country 29

Figure 8: Global market for big data technology by retail channel – spending in US$m 29

Figure 9: Usage of business intelligence solutions 32

Figure 10: Driving forces behind retailers’ big data strategies 34

Figure 11: Key opportunities for IT vendors catering to the big data in retail market 36

Frequently asked questions

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