A Weekend Read - Syz' extra-curriculum activities.
Zebra Technologies (a global technology manufacturer from mobile computers to printers and barcodes) has released its report for the future for retail shopping:
It is a well written document with lots of pictures. Sponsored data is not directly mentioned, but it is written all over it
An extract from page 9.
A DEEP DIVE INTO DATA
Merchants are also investing in business intelligence and analytics technology solutions to take data insights to new heights.
While retail data analysis is nothing new, the reams of consumer information generated in the era of digital shopping, along with the rise of technology equipped to handle and analyze the surge, is recasting how retailers determine what to sell, how to sell, what’s selling, what’s not and why. Digital data analysis is still in its infancy, but its payoff is promising: Companies that integrate data and analytics into their operations are poised to generate productivity and profit gains that are an estimated 5% higher than competitors that don’t.* Hence, it stands to reason that 58% of retailers surveyed are budgeting for big-data solutions for storing and analyzing IoT generated data. When asked what business intelligence and analytics technologies lead their strategic goals, retailers ranked market-basket analysis, customer segmentation and centralized customer data and intelligence as their top tech initiatives. Market-basket analysis, for one, is a timeworn modeling technique used by merchandisers to decipher which types of products shoppers are more apt to purchase together. It’s a wide-ranging tool, as basket analysis offers insight into consumer patterns, preferences and shopping behavior, regional trends, as well as reveals the relationship between products for sale. Combined, these insights inform factors from store layout to marketing. And now the modeling technique is being automated by big data. Sophisticated analytics platforms are transforming reams of market-basket data into insights ripe for actionable merchandising strategies, like a supermarket placing snacks next to baby wipes during the football season, for example, when Dads are shopping for both their kids and their couch-potato stash for the game.
SYT Price at posting:
3.2¢ Sentiment: Buy Disclosure: Held
While retail data analysis is nothing new, the reams of consumer information generated in the era of digital shopping, along with the rise of technology equipped to handle and analyze the surge, is recasting how retailers determine what to sell, how to sell, what’s selling, what’s not and why. Digital data analysis is still in its infancy, but its payoff is promising: Companies that integrate data and analytics into their operations are poised to generate productivity and profit gains that are an estimated 5% higher than competitors that don’t.* Hence, it stands to reason that 58% of retailers surveyed are budgeting for big-data solutions for storing and analyzing IoT generated data. When asked what business intelligence and analytics technologies lead their strategic goals, retailers ranked market-basket analysis, customer segmentation and centralized customer data and intelligence as their top tech initiatives. Market-basket analysis, for one, is a timeworn modeling technique used by merchandisers to decipher which types of products shoppers are more apt to purchase together. It’s a wide-ranging tool, as basket analysis offers insight into consumer patterns, preferences and shopping behavior, regional trends, as well as reveals the relationship between products for sale. Combined, these insights inform factors from store layout to marketing. And now the modeling technique is being automated by big data. Sophisticated analytics platforms are transforming reams of market-basket data into insights ripe for actionable merchandising strategies, like a supermarket placing snacks next to baby wipes during the football season, for example, when Dads are shopping for both their kids and their couch-potato stash for the game.
