The Smart Data Blog

Amazon and Whole Foods – Big Data Comes to Retail

Posted by Kirk Newell on Jul 9, 2017 2:02:00 PM

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Many retail industry observers are asking why e-commerce giant Amazon purchased the brick & mortar grocery chain Whole Foods. The unanimous answer is: access to real-world customer data that is richer and more robust that what Amazon can acquire from online purchases.

With Whole Foods, Amazon can augment its online data with customer purchasing behaviors offline by tracking in-store purchases in real-time and build on existing customer profiles. This strategy is bolstered by Amazon’s recent technology patent enabling it to control what customers search for online while connected to an in-store WiFi network, allowing the company to keep customers pointed toward products available on its site.

supermarket-949913_640.jpgAccording to news reports, Whole Foods’ visitor data will be continuously tracked and recorded to help Amazon understand whether you spend more time in the produce department or on the baby food aisle.  The technology can even determine how much time customers spend in front of a particular product brand.

Whatever one thinks of being tracked while shopping, the data rewards are endless for Amazon and its brand partners. If consumers can be convinced that there is a benefit to having their in-store behaviors tracked, Amazon has the opportunity to transform and possibly re-invigorate the retail industry.

As we’ve seen time and again, data has become the new “precious metal” that all companies are looking to leverage. If anyone had any doubts of the significance of data to an enterprise and its growth, the Amazon strategy for retail should dispel them.

Of course, at Cambridge Semantics, we’re always encouraged by the ever-growing interest in big data by industries of all kinds. What we know, too, is that Amazon and other companies wishing to expand their data intake and the value derived from it will need to adopt solutions like the Anzo Smart Data Lake®.

The Cambridge Semantics’ Anzo SDL platform uses semantic graph models to link and contextualize diverse enterprise data at scale. The graph models in Anzo SDL provide users with intuitive self-service data discovery, analytics and visualization capabilities across all entities and relationships in the data lake. Anzo SDL features the in-memory graph database, Anzo Graph Query Engine, which recently shattered a previous record of loading and querying a ‘trillion triples’ by 100x.

To learn more about the Anzo Smart Data Lake, download our whitepaper.

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Topics: Big Data, Retail