United Breaks Privacy with Passenger App

The Wall Street Journal: “United rolled out a new app to its flight attendants earlier this year with so much information about people, the airline has been reluctant to turn on all the functionality. The tool can show flight attendants information on each frequent flier’s five previous flights—green if it was a good flight, yellow or red if something went wrong, like a delay. But United is worried some customers might consider that stalking … Personal milestones like birthdays are left to the judgment of flight attendants. They can decide whether they think a customer would appreciate the recognition or recoil.”

“The devices can give flight attendants real-time information on tight flight connections for passengers, confirm whether a wheelchair has been ordered for a customer and help keep track of unaccompanied minors. Many now allow flight attendants to offer instant compensation for maladies like spilled coffee or broken entertainment screens. Better service onboard in coach will go to those with higher status.”

“Airlines acknowledge the devices have made the job more complex for flight attendants. Sara Nelson, president of the Association of Flight Attendants union, says the devices can reduce situational awareness. If flight attendants have to study the screen to correctly recognize each customer, they may not be spending as much time staying alert to what’s going on in the cabin.” She comments: “I’m a little shocked there hasn’t been more backlash. I think the public has generally decided they like the personalized service, they like to be able to resolve their issues faster, not have to tell people as much. And they’ve sort of sacrificed their privacy for those conveniences.”

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Retail Math: Ladder of Causation

The Wall Street Journal: “Suppose, for example, that a drugstore decides to entrust its pricing to a machine learning program that we’ll call Charlie. The program reviews the store’s records and sees that past variations of the price of toothpaste haven’t correlated with changes in sales volume. So Charlie recommends raising the price to generate more revenue. A month later, the sales of toothpaste have dropped—along with dental floss, cookies and other items. Where did Charlie go wrong?”

“Charlie didn’t understand that the previous (human) manager varied prices only when the competition did. When Charlie unilaterally raised the price, dentally price-conscious customers took their business elsewhere. The example shows that historical data alone tells us nothing about causes—and that the direction of causation is crucial.”

“Machine-learning systems have made astounding progress at analyzing data patterns, but that is the low-hanging fruit of artificial intelligence. To reach the higher fruit, AI needs a ladder, which we call the Ladder of Causation … To reach the higher rungs, in place of ever-more data, machines need a model of the underlying causal factors—essentially, a mathematics of cause and effect.”

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H&M Stores Buy Into Big Data

The Wall Street Journal: “H&M, like most retailers, relies on a team of designers to figure out what shoppers want to buy. Now, it’s using algorithms to analyze store receipts, returns and loyalty-card data to better align supply and demand, with the goal of reducing markdowns. As a result, some stores have started carrying more fashion and fewer basics such as T-shirts and leggings … H&M’s strategy of using granular data to tailor merchandise in each store to local tastes, rather than take a cookie-cutter approach that groups stores by location or size, is largely untested in the retail industry, consultants say.”

“The H&M store in Stockholm’s swanky residential Östermalm neighborhood hints at how data can help. The store used to focus on basics for men, women and children, with managers assuming that was what local customers wanted. But by analyzing purchases and returns in a more granular way, H&M found most of the store’s customers were women, and fashion-focused items like floral skirts in pastel colors for spring, along with higher-priced items, sold unexpectedly well.”

“With the help of about 200 data scientists, analysts and engineers—internal staff and external contractors—H&M also is using analytics to look back on purchasing patterns for every item in each of its stores. The data pool includes information collected from five billion visits last year to its stores and websites, along with what it buys or scrapes from external sources … The chain uses algorithms to take into account factors such as currency fluctuations and the cost of raw materials, to ensure goods are priced right when they arrive in stores.” Nils Vinge of H&M comments: “The algorithms work around the clock and adjust continuously to the customers’ ever-changing behavior and expectations.”

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Ocean Medallion: Smooth Cruising on a ‘Smart’ Ship

Quartz: John Padgett, chief experience and innovation officer of Carnival Cruises, “previously worked for Disney, where he was instrumental in the creation of the MagicBand, a wristband meant to help reduce the aggravations of the typical Disney vacation … At Carnival, Padgett and his team quickly set out to create Carnival’s own version of the Disney MagicBand, called the Ocean Medallion. It uses AI to take the MagicBand technology to another level. Instead of just alleviating the ‘friction’ of typical travel experiences (lines, room keys, paying for things) it will use data to anticipate what you want to do, eat, and see.”

“The Medallion, offered first on Carnival’s Princess cruise line, is about the size of a quarter … It facilitates boarding and cuts down on wait times. It can be used to pay for things on the cruise, it unlocks the door to your room as you approach, and can be used on the ship-wide gambling platform. Carrying the Medallion means the staff knows your name and where you are. If you order a drink, they can come find you to deliver it. If you go to another bar on board, the staff already knows what you like. The Medallion also updates your information, keeping track of your likes and dislikes, what activities you enjoy, and what you consume. It anticipates other activities you’ll enjoy and the side trips you’ll want to take.”

“In many ways the Medallion is a beta launch of the first fully wired smart city. What it takes to make it work could one day be used on land. Padgett says the technology is innovative because the preferences you reveal are updated in real time. You order a Martini and every crew member on the ship instantly knows more information about you, and is that much closer to determining whether you might enjoy trying scuba diving—or just kicking back in your stateroom with an old episode of The Love Boat.”

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Mistaken Identities: Fake Birthdates Foil Facebook

The Wall Street Journal: “A recent survey of U.S., French, German, Italian and British consumers found that 41% had intentionally falsified personal information when signing up for products and services online. Most common was providing a fake phone number … Respondents also said they have provided a false birth date, made up a postal address, lied about a name or selected the wrong gender.”

“All the lying does seem to foil advertisers. It is ‘a much bigger problem than people are aware of,’ says Nick Baker, director of research and consulting of U.K. market research company Verve, which conducted a 2015 survey showing a large amount of fake information on website registrations and the like. Incorrect birth years, he says, are particularly nefarious because advertisers are often trying to match up habits or buying patterns with a specific age group.”

“But some companies that provide data to marketers say they are depending less and less on biographical information. Preethy Vaidyanathan, the chief product officer of New York-based marketing technology company Tapad, says they track much more valuable information from phone and web browser use.”

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Bingo Box: China Leads Robo-Retail Revolution

The New York Times: “A global race to automate stores is underway among several of the world’s top retailers and small tech start-ups, which are motivated to shave labor costs and minimize shoppers’ frustrations, like waiting for cashiers … Companies are testing robots that help keep shelves stocked, as well as apps that let shoppers ring up items with a smartphone … China, which has its own ambitious e-commerce companies, is emerging as an especially fertile place for these retail experiments.”

“One effort is a chain of more than 100 unmanned convenience shops from a start-up called Bingo Box, one of which sits in a business park in Shanghai. Shoppers scan a code on their phones to enter and, once inside, scan the items they want to buy. The store unlocks the exit door after they’ve paid through their phones … Not to be outdone, JD, another big internet retailer in China … put readable chips on items to automate the checkout process. At its huge campus south of Beijing, JD is testing a new store that relies on computer vision and sensors on the shelves to know when items have been taken.”

“While such technologies could improve the shopping experience, there may also be consequences that people find less desirable. Retailers like Amazon could compile reams of data about where customers spend time inside their doors, comparable to what internet companies already know about their online habits … In China, there is less public concern about data privacy issues. Many Chinese citizens have become accustomed to high levels of surveillance, including widespread security cameras and government monitoring of online communications.”

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Mastodon: The Anti-Facebook?

The Washington Post: “Mastodon, a Twitter-like social network has had a massive spike in sign-ups … As the #DeleteFacebook movement has gained steam, people are registering for Mastodon at four times the rate that they normally do, according to Eugen Rochko, the service’s creator. Between Monday and Tuesday alone, Mastodon gained about 5,800 new users … That’s more new registrations than what Mastodon typically sees over an entire week.”

“For a social network — Mastodon has 1.1 million users to Facebook’s 2.2 billion — that may not sound very impressive. But what makes Mastodon increasingly attractive, particularly in a post-#DeleteFacebook world, is its attitude toward data and control … Mastodon’s code is open-source, meaning anybody can inspect its design. It’s distributed, meaning that it doesn’t run in some data center controlled by corporate executives but instead is run by its own users who set up independent servers. And its development costs are paid for by online donations, rather than through the marketing of users’ personal information.”

“Rooted in the idea that it doesn’t benefit consumers to depend on centralized commercial platforms sucking up users’ personal information, these entrepreneurs believe they can restore a bit of the magic from the Internet’s earlier days — back when everything was open and interoperable, not siloed and commercialized.”

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How Big Data Disrupts Big Brands

The Washington Post: “Launched in 2015, ZX Ventures is charged with ‘disrupting’ the beer industry by developing and investing in businesses that will provide value and improve user experiences — and make more money for AB InBev — somewhere down the road. They’ve invested in e-commerce delivery systems, beer-rating applications and home-brew suppliers, all of which provide data points that can tell them about trends and help them get ahead of the market.”

“According to its mission statement, ‘ZX Ventures is hopelessly dedicated to creating and analyzing the data necessary for determining our ideal strategies, products and technologies. We believe that the more we know and learn about our consumers and products, the better chance we have of anticipating their needs in the future.’ Translation: They want to know everything about purchasing patterns and decisions. What are customers looking for? What are influencers thinking? How can they make it easier to get AB InBev’s products into the hands of people who might want beer?”

“The ZX Ventures team is interested in access to a large number of data points: The most popular and trending beers, styles and search terms in any region around the world. Are more people giving high ratings to saisons in London than Los Angeles? Are Bavarians searching for IPAs available to them? What are the most highly rated beer bars in the Southeast? Which beer styles have grown the most in the last year, in terms of average ratings or the number of searches, and where? If certain cities are rating sour beers higher than the norm, for example, Elysian’s sour pineapple seasonal or a new wild saison from Wicked Weed could be given extra promotional play in those markets.”

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Retailers Miss Mark With ‘Targeted’ Emails

The Wall Street Journal: “Traditional retailers were once pioneers of using data to zero in on what customers want. But as the importance of their catalogs and mailings have been overtaken by email and other online media, they have struggled—sometimes to the frustration of their customers.”

Brendan Witcher of Forrester comments: “Nearly 90% of organizations say they are focused on personalizing customer experiences, yet only 40% of shoppers say that information they get from retailers is relevant to their tastes and interests. The ugly truth is that most retailers haven’t done the (hard) work of understanding how to use the data.”

“At no time is that more evident than during the year-end shopping bonanza, when retailers deluge customers with messages. During last year’s holiday season, retail emails increased 15% compared with the rest of the year, but shoppers opened 15% fewer of them, according to a study of eight billion messages by marketing-services firm Yes Lifecycle Marketing.”

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Google Gaggle: Predicting Restaurant Wait Times

USA Today: “Google Search (and eventually Google Maps) will show diners the estimated wait times for local restaurants to help them skip the crowds and jump the lines. The new feature expands on Google showing consumers looking to change their oil and get their hair cut how busy local businesses typically are. Google gathers this information from aggregated and anonymized data from users who allow Google to track their location using Google apps on their phones or other devices.”

“Now, says Google, diners can click on a time frame and see live or historical data on how busy a restaurant is expected to be and the estimated wait time. The information will be available for nearly 1 million sit-down restaurants around the globe. And up next, says Google: Grocery stores.”

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