Amazon calls Thanksgiving weekend, the five-day period from Thanksgiving Day through Cyber Monday, the “Turkey 5.” The online retail giant first clucked out the phrase in 2017 and then again in a recent rundown of its sales successes.
Like many retailers, both online and brick-and-mortar, Amazon couldn’t manage the Turkey 5 or the rest of the modern holiday shopping season without data—lots of data, data that’s been parsed and analyzed to help predict how, where, and when you’ll buy something.
“By using analytics, retailers can harness valuable insights from the data at their disposal, in turn, helping them react to changing demands in a far more responsive way,” said Andrew Fowkes, head of Retail Centre of Excellence in the United Kingdom and Ireland for data analytics company SAS. “In the fast-paced retail market, it can help retailers position themselves at the forefront of technological and customer-driven change.”
Much of this analysis takes place in the cloud—or in layman’s terms, by third party companies using their own data centers or those of others. The end result has a huge impact on shoppers’ experience at most any electronics store, fashion boutique, or online superstore. Here’s how:
Determining What Works
That sweater you want to buy for your aunt? After sifting through years of sales data, cloud software likely told the manufacturer to make it and the retailer to sell it.
This type of analysis has been around for ages. But without hard data, managers often relied on gut instinct to pick which products to approve and which not to. Advanced data crunching is able to spot trends sooner and allow retailers to react faster.
For example, phone accessory maker Belkin needed a more reliable method for deciding which products to prioritize on the manufacturing line. Using data analyzed by Amazon Web Services (AWS), Belkin was able to fine-tune its Wemo product line for controlling smart thermostats and light switches. The company also uses AWS to manage its Linksys line of home routers. This insight reduced the time it took to get many of its biggest selling products to market.
Big data helps companies figure out what shoppers want by analyzing their buying patterns over time. Targeted marketing to individual shoppers is one of the upsides, at least for retailers.
Smart retailers blend data generated in their brick-and-mortar locations with the data from their online stores to get a clearer picture. The data, which is typically crunched in the cloud, lets retailers uncover the best way to sell its products.
“Retail shops can use data about what customers are buying online to create a unique brick-and-mortar experience that gets people off the computer and into the store. The more data retailers have and the faster they can get it to in-house personnel, the better,” said Sash Sunkara, co-founder and CEO of RackWare.
The end result? You’ll see emails, mailers, and ads from retailers that show you actual items you’ve searched for or clicked on. Retailers can create custom coupons and other incentives to get you to open your wallet.
Controlling the number of products sitting on store shelves goes hand-in-hand with knowing what to put there in the first place. Help from the cloud makes this process far simpler, and often better for shoppers.
It’s about supply and demand. We all know that snow shovels are big sellers during the winter and not at all in the summer. Shovels sell fastest when a storm is imminent. Stores like Home Depot and Lowes use inventory tracking to ensure they have the right number available in stores. Triggers in the inventory system can automatically order more when stock drops below a predetermined threshold.
In other words, the cloud made sure you can grab a shovel at your local store ahead of that next blizzard.
The next time you use the Starbucks app to pay for a Peppermint Mocha, be sure to thank the cloud for powering the transaction.
Today’s mobile payment services are all powered online by a long list of vendors. Whether you use a retailer’s branded app, or your phone’s built-in payment tool, the cloud untangles all of the touchpoints between your money and the retailer’s virtual cash drawer. The best part? The number of retailers accepting mobile wallets like Apple Pay and mobile payments has ballooned.
ParkBoston, for example, is a mobile app that lets you pay for street parking via your phone, eliminating the need to feed quarters into a meter. It’s as easy as entering your license plate number and the parking zone.
The cloud helps retailers, too. Shopify, an e-commerce platform and payments service provider, is used by nearly 600,000 businesses with total sales over $82 billion. Shopify’s pitch is that it lets entrepreneurs focus on their business without having to worry about the complexities of payments.
And then there’s Amazon Go, the cashierless store that Amazon has rolled out in a handful of cities. Using cameras, Amazon Go uses computer vision and deep learning algorithms to identify when customers pick up a product, what that product is, and what it costs. It’s then added to a virtual shopping basket and charged to the customer’s Amazon account when they exit the store.
In 2002, Stephen Spielberg’s vision of facial recognition in the movie Minority Report was scarily prescient. Corporations used facial recognition to deliver personalized ads to people as they walked around, clouding their vision with virtual billboards.
These days, facial recognition is used for other purposes: preventing theft.
A 2017 report from Loss Prevention Media details how one of the country’s leading retailers uses facial recognition to keep shoplifters out of its stores. In-store cameras send images to FaceFirst, a biometrics platform provider, where the images are run though a database. It can identify repeat offenders in as little as 0.01 seconds and then alert security.
“We now know within seconds of a person walking in the store if they’ve previously been caught stealing from us,” Tom Smith, vice president of loss prevention for ‘Store-Mart,’ told Loss Prevention Media. “We now know which hours of the day see the most shoplifter activity. We now know that 26% of the people we detain, we see again in the brand within one month, on average 13 days later.”