Market Research Report
Big Data in Retail - Thematic Research
|Published by||GlobalData||Product code||530636|
|Published||Content info||39 Pages
Delivery time: 1-2 business days
|Big Data in Retail - Thematic Research|
|Published: May 31, 2018||Content info: 39 Pages||
How can retailers benefit from Big Data and Analytics (BDA)?
Cisco estimates that the world generates 122 exabytes of data traffic per month. This traffic is growing at 24% per annum and 82% of it is consumer generated. Most of this data traffic could be monetized via a growing band of hyperscale, internet-facing data centers around the world. Ask any CEO how they expect to sell more products and cut costs and they will tell you that big data features prominently in their strategy. Big data refers to the technology processes by which companies can profit from the large amounts of data to which they have access.
Cloud computing, machine learning (ML), augmented reality (AR), internet TV, the Internet of Things (IoT), robotics, cryptocurrencies, voice, blockchain, and cybersecurity. These are the big investment themes of tomorrow and they all have one thing in common: they generate huge amounts of data.
Big data provides endless opportunities for analytics within retail organizations including real-time in-store analytics, web analytics for ecommerce sites, as well as supporting back-end and cloud based resources.
BDA provides substantial opportunities for traditional retailers as well as e-retailers 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.
Major business challenges can be overcome by introducing a big data solution that is tailored to retailers' needs in general, however it also needs to be appropriate to specific use cases. These may vary depending on retailers' aims and objectives, the allocated budget, existing data sources, and store layout. Certain technologies may already be in use for capturing data such as RFID, beacons, sensors, and surveillance systems.