Relevant data for retailers has proved to be coming from five dimensions: customer, product, time, geo-location and channel. By gathering large amounts of this relevant data from many heterogeneous sources and locations in real-time and by processing and analyzing this data, BigDataStack can provide retailers with:
- smart shopping lists
- personalized and contextual offers
- pricing strategies
- products location and distribution
- detailed product information that help them to improve their offer as well as differentiate from the competition
To develop this and other solutions, BigDataStack will manage data collection, aggregation, storage and analysis of data from a multitude of heterogeneous sources and seamlessly analyse them for the predictive services envisioned ehich will lead to an efficient and optimized analytics and real-time decision making enabling the development of data-based value added services.
Thanks to both the big volume of data coming from a number of different sources and to the capability to process this amount of data in real-time:
- Retailers offer will become more attractive for customers thanks to more accurate predictions than those produced nowadays.
- Customers shopping experience will improve because of the personalized and accurate promotions and products they are offered.
- ROI of marketing campaigns will increase, leading to an increase in both sales and customer satisfaction.
The main goal, in this use case, is to test and validate the capabilities of BigDataStack to make predictive analysis in the world of the retailers that helps them to attract and keep customers.
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