Monthly Archives: June 2017

How Amazon could use Big Data to change the way you shop.

Stephen DiFranco – CEO and Founder IoT Advisory Group writing as a guest writer in Entrepreneur magazine bring a fresh perspective on the recent acquisition of Whole Foods by Amazon by describing this buy as a “playground for disruption of retail”. As this gives Amazon a shot at retail analytics, customer traffic management and in–store customer management, going on to add,  that this may also provide a testing ground for Amazon to explore “presence marketing “  – the layering of online and offline buying analytics while tracking the movements of shoppers.

And according to Stephen DiFranco, this acquisition is all about disrupting the retail with Amazon bringing the on-line analytics to off-line shopping.

With Amazon getting a patent for “Physical store on-line traffic control “ just days before acquiring Whole Foods, Stephen DiFranco is sure that Big Data will be a big presence in the off-line retailing from now on. With store visitors encouraged to get connected to the store Wi- Fi, they will then by tracked to know about their typical route thru’ the store, with pertinent suggestions sent to customers to prompt them to buy complementary products. Another scenario may be reminding the customers about frequently brought items and the directing them to that location.

With other biggies in the retail sectors moving for consolidation, and retail margins being very thin, Amazon buying Whole Foods is a great advantage since food retail is best for collecting brick and mortar customer data thereby allowing them to leverage data to push volumes.

With food retailer being the most frequently visited stores, as shopping for food is done twice a week. And with customers looking for convenience, they will be purchasing the same items again and again, week after week.  And this behavior gives out preferences across product lines and lends itself to behavior analysis giving out clear buying patterns across products and categories.

Amazon using a big data application and massive amounts of data pertaining to a number of visits, product category, minimum purchased, can lead the way in enhancing the customer experience by helping in decision making by delivering notifications, discount offers, and other information at an appropriate time.

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Artificial Intelligence will change how companies in future do business.

Vivian Rosenthal – Founder of Snaps, mobile messaging platform writing on Big Data in the Forbes e- magazine tells us how Hollywood always chooses to portray the future in apocalyptic terms with humans reduced to slaves to newer technologies to AI, and offers a counterview of how businesses are using the same technologies to overcome some of their most critical challenges.

According to her, even as there are much still not convinced about the indispensable role machine learning and other artificial intelligence technologies will play in future enterprises, there are many who have used these technologies to make their enterprises smarter, faster and more creative.

Citing CB insights to bring home the point, she shows that it’s not only big tech companies buying AI firms but traditional businesses are also getting into this race by acquiring AI startups and this together with the fact that 34 AI acquisitions were done by in Q1 of 2017, highest at any point of time, indicating wider acceptance of AI.

AI is riding on the convenience of cloud computing, the pervasiveness of processing power, huge, no-cost storage options, and providing enterprises the opportunity to leverage their data by applying machine learning to deliver best in the class customer experience with optimal resources. Vivian then proceeds to bring out how different technology behemoths are using machine learning to increase customer‘s experience.

Pinterest manages to deliver the right pin at the right moment by leveraging machine learning for content discovery, in this, the content recommendations are algorithmically driven and machine learning is used to determine among billions of user interactions the right pin to deliver at the right time. Similarly, Netflix uses machine learning to understand consumer watching pattern, surfing insights thus bring data –informed decision making to content discovery. Amazon‘s Alexa team is trying to surmount the challenges of Natural Language Processing and Generation as we are moving from typing to talking computers.

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