‘Amazon Charts’ Re-Define ‘Best Seller’

The New York Times: Amazon now tracks “not only the top-selling digital and print books on Amazon, but the ones that customers spend the most time reading … With its lists, Amazon aims to redefine the notion of a best seller, expanding it to include books that are ‘borrowed’ from its e-book subscription service, and ones that are streamed on Audible. As a result, the lists give increased visibility to books that might not typically appear on other best-seller lists.”

“All of Amazon’s acquisitions and new features are having a cumulative effect, allowing the company to draw on its vast customer base and troves of data to discover what is popular, and return that information to customers, creating a lucrative feedback loop … Crowdsourcing and data mining are also driving the company’s approach to its bookstores, which act as showcases for books popular with customers on the site. While the stores have traditional categories, like fiction, nonfiction and travel, the most eye-catching shelves feature categories culled from Amazon’s customer data.”

“The first thing customers see when they walk into the store is a large display table, labeled Highly Rated, which includes books with an average rating of 4.8 stars or higher on a scale of 5 … Another display case, labeled Page-Turners, features books that people finish reading on their Kindle in fewer than three days … Another section features the most ‘wished for’ books from Amazon’s website … The books are all displayed face out. Under each book is a card with the average customer rating, the number of reviews and a featured review from an Amazon reader. Displaying the full cover of each book mimics the visual look of Amazon’s website, and might lure customers to unfamiliar titles.”

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Google Eyes: Watch While You Shop

The Washington Post: “Google executives say they are using complex, patent-pending mathematical formulas to protect the privacy of consumers when they match a Google user with a shopper who makes a purchase in a brick-and-mortar store. The mathematical formulas convert people’s names and other personal information into anonymous strings of numbers.”

“The formulas make it impossible for Google to know the identity of the real-world shoppers, and for the retailers to know the identities of Google’s users, Google executives said. The companies know only that a match has been made. In addition, Google does not get a detailed description of the individual transactions, just the amount spent.”

“Google would not say how merchants had obtained consent from consumers to pass along their credit card information. In the past, both Google and Facebook have obtained purchase data for a more limited set of consumers who participate in loyalty programs. Consumers that participate in loyalty programs are more heavily tracked by retailers, and often give consent to share their data with third parties as a condition of signing up. (Not all consumers may realize they have given such consent, according to the digital privacy advocacy group Electronic Frontier Foundation).”

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Not SeeFood: App Apes ‘Shazam for Food’

The Verge: “In a peculiar case of life imitating art imitating life, Pinterest has announced a new recipe-finding feature that makes use of computer vision to tell you about a dish when you point your smartphone camera at it … It sounds an awful lot like SeeFood, the fake ‘Shazam for food’ app from the HBO comedy Silicon Valley. Pinterest, of course, doesn’t use that terminology anywhere, nor does its marketing material even reference the sitcom or its ludicrous parody, which manifested itself as an app that could only tell you whether an object was or was not a hotdog.”

“When reached for comment regarding SeeFood, a Pinterest representative confirmed to The Verge that the Silicon Valley episode was ‘separate and completely coincidental’.”

“This is all part of a broader artificial intelligence push in the tech industry to apply machine learning techniques to everyday life. By training neural networks on huge mounds of data and translating that into a real-time algorithm, tech giants like Google, Facebook, and Microsoft are now developing software products that can digest and understand the world, from text to photos to even videos.”

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Hit Factories: Making Songs Like Sausages

BBC: “A new study by Music Week magazine shows it now takes an average of 4.53 writers to create a hit single … Ten years ago, the average number of writers on a hit single was 3.52 … Even solo singer-songwriters like Adele, Taylor Swift and Ed Sheeran, whose identities are deeply ingrained into their music, lean on co-writers …. So why is this happening? Are songwriters increasingly lazy or lacking in talent? Or are they second-guessing themselves in the search for a hit?”

“According to Mike Smith, managing director of music publishers Warner/Chappell UK, it is simply that the business of making music has changed.” He comments: “Think back 20 years and an artist would take at least two or three albums to really hone their craft as a songwriter. There is a need to fast-forward that process [which means record labels will] bring in professional songwriters, put them in with artists and try to bring them through a lot faster.”

“Writing camps are where the music industry puts the infinite monkey theorem to the test, detaining dozens of producers, musicians and ‘top-liners’ (melody writers) and forcing them to create an endless array of songs, usually for a specific artist … British songwriter MNEK, who is one of 13 people credited on Beyonce’s hit single Hold Up, says the song is essentially a Frankenstein’s Monster, stitched together from dozens of demos.” He explains: “She played me the chorus. Then I came back here [to my studio] and recorded all the ideas I had for the song. Beyonce snipped out the pieces she really liked and the end result was this really great, complete song.”

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The Stitch Fix Secret: Make Shopping Easy

The New York Times: Stitch Fix is a mail-order clothing service that offers customers little choice in what garments they receive, and shies away from discounts for brand name dresses, pants and accessories. Despite a business model that seems to defy conventional wisdom, Stitch Fix continues to grow … To the company’s founder, Katrina Lake, success comes down to delivering what consumers want: making it easier to shop … In her view, what was important was helping customers find clothing they liked without taking lengthy shopping trips and returning dozens of items.”

“At the company’s warehouse, Eric Colson, formerly a top data scientist at Netflix, spoke to the role that data science — once the province of high-tech giants — plays in nearly every aspect of the Stitch Fix business. Mr. Colson excitedly illustrated on whiteboards how the company’s systems can narrow down a broad range of women’s pants to a relative few that each individual customer is statistically likely to keep … Algorithms have even cut the number of steps needed for workers to pick out clothes for individual clients.”

“Yet the question remains whether customers who are initially thrilled by receiving a customized box of clothing will remain customers for months or even years … Stitch Fix executives declined to share their retention statistics, but claim that they are above industry averages.”

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Algorithmic Retail: Beyond Dynamic Pricing

The Wall Street Journal: “Advances in A.I. are allowing retail and wholesale firms to move beyond ‘dynamic pricing’ software, which has for years helped set prices for fast-moving goods, like airline tickets or flat-screen televisions. Older pricing software often used simple rules, such as always keeping prices lower than a competitor.”

“These new systems crunch mountains of historical and real-time data to predict how customers and competitors will react to any price change under different scenarios, giving them an almost superhuman insight into market dynamics. Programmed to meet a certain goal—such as boosting sales—the algorithms constantly update tactics after learning from experience … The software learns when raising prices drives away customers and when it doesn’t, leading to lower prices at times when price-sensitive customers are likely.”

“Algorithms can also figure out what products are usually purchased together, allowing them to optimize the price of a whole shopping cart. If customers tend to be sensitive to milk prices, but less so to cereal prices, the software might beat a competitor’s price on milk, and make up margin on cereal.”

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IKEA Asks: Do You Speak Human?

The Verge: ‘If you put an AI in charge of your house — letting it control the lights, the alarms, the temperature, and so on — how would you want it to act? Should it be ‘autonomous and challenging’ or ‘obedient and assisting’? Would you prefer if it sounded male, female, or if it was gender neutral? Should it be religious? These are just some of the questions Ikea is asking its customers in a new survey titled: Do you speak human?”

“With this new survey, Ikea is focused on computer personality, looking to find out what sort of AI people would be happiest to interact with. This is a question that preoccupies the big tech companies, too — that’s why they’re hiring novelists and comedians to finesse the personality of their digital assistants.”

“Ikea is updating the results of the survey as it goes; so far it’s saying that 41 percent of people want their AI to be ‘obedient and assisting,’ 42 percent want it to be ‘gender neutral’ (as opposed to 35 percent for male, 24 percent for female), and 87 percent say they want their AI to ‘detect and react to emotions.’ There’s bound to be some self-selecting bias at work here, as the people who answer this survey are more likely to be interested in technology in general, but it’s still a very intriguing project.”

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New HQs Capture Corporate Culture

The Economist: “Throughout San Francisco and Silicon Valley, cash-rich technology firms have built or are erecting bold, futuristic headquarters that convey their brands to employees and customers … The exteriors of the new buildings will attract most attention, but it is their interiors that should be watched more closely … The big idea championed by the industry is the concept of working in various spaces around an office rather than at a fixed workstation.”

“A fluid working environment is meant to allow for more chance encounters, which could spur new ideas and spark unexpected collaborations … Young workers are thought to be more productive in these varied environments, which are reminiscent of the way people study and live at university. One drawback, however, is that finding colleagues can be difficult. Employees need to locate each other through text messages and messaging apps.”

“The data that firms can collect on their employees’ whereabouts and activities are bound to become ever more detailed … it is not hard to imagine how such data could create a culture of surveillance, where employees feel constantly monitored … A less controversial trend is for unusual office interiors. These can distinguish companies in the minds of their employees, act as a recruiting tool and also give staff a reason to come into the office rather than work from home … The effect of all this is that the typical office at a technology firm is becoming a prosperous, self-contained village. Employees have fewer reasons than ever to leave.”

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Who Will Win The Retail Race?

The Wall Street Journal: “Can physical retailers build intimate digital relationships with their customers—and use that data to update their stores—faster than online-first retailers can learn how to lease property, handle inventory and manage retail workers?”

“It isn’t hard to picture today’s e-commerce companies becoming brick-and-mortar retailers. It’s harder to bet on traditional retailers becoming as tech savvy as their e-competition.”

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Whole Foods: Now Just Another Big Box?

The Wall Street Journal: “Whole Foods Market Inc. wants to cut prices without sacrificing the local products that define its healthy image … Some smaller suppliers and industry consultants say the shift to a more centralized distribution structure and other changes risk compromising Whole Foods’ ability to keep stocked with the latest foodie trends and hot local brands.”

“Many of the changes are being spearheaded by Don Clark, a former Target Corp. executive … The data analytics, centralized purchasing and strict shelf management he brought from Target could save money that Whole Foods can use to lower its relatively high prices … Whole Foods has long divided its 462 stores into 11 regions, each with distinct product offerings like local maple syrup and gourmet pickles. A quarter of Whole Foods shoppers that visited the chain in the past month did so for items they couldn’t find elsewhere, according to a survey by Kantar Retail.”

“Whole Foods co-founder and Chief Executive John Mackey said … his new strategy strikes a balance between the remaining autonomy of regional executives and an easier process for national brands to pitch their products just once at Whole Foods’ Austin, Texas, headquarters. That streamlining will lead to lower prices, he said … But smaller brands and people who work with them say they have less incentive to put up with a more impersonal Whole Foods … And some big brands say Whole Foods’ regionalized approach made it tough to negotiate a nationwide strategy for their brands.”

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