Big Data and analytics (BDA) provide substantial opportunities for traditional retailers, FMCG companies, and eTailers since they already have a wealth of data that can be used for various analytics to optimize processes, increase sales, and launch new products and 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 provides endless opportunities for analytics within retail organizations, including real-time in-store analytics, web analytics for e-commerce sites, and support for back-end and cloud-based resources. FMCG companies can use Big Data to aid the development of innovative products, target consumers with more personalized and relevant brand communications, and increase consumer loyalty. Retailers and FMCG companies must devise an effective Big Data strategy to enable increased responsiveness to consumers, as well as increase spend per customer.
- This report analyses the impact of big data in retail and FMCG.
- It discusses how big data and analytics (BDA) provide substantial opportunities for traditional retailers, FMCG companies, and eTailers.
- It identifies leading technology and retail & FMCG players who should benefit from the emergence of BDA.
Reasons To Buy
- The report highlights some of the key players in the big data industry and where do they sit in the value chain.
- It identifies the main trends expected over the next two years in the big data theme.
- The report discusses how big data can be managed and its value to consumers and businesses.
- It provides an industry analysis, sighting some key mergers and acquisitions and critical milestones that have changed the course of the data center industry’s evolution.
- The report analyses the impact of big data on retail and FMCG through some case studies, and key recommendations for retailers, FMCG companies, and IT vendors.
- It offers a technology briefing to explain how big data combines traditional data management technologies with new forms of data processing that are better suited to modern formats.