From Publishers Weekly:
Thanks to a new generation of software and computing tools, in the future, book marketing will be determined by data rather than by intuition.
If you’re a publishing executive and you haven’t been reading about Big Data, then you soon will be. Big Data is just what it sounds like—data collections of such enormous size they are awkward, expensive, and impossible to process with conventional computing. Big Data also refers to the ability to use distributed computing—parsing out these huge data sets and processing them simultaneously on multiple computers—plus new software tools and deep analysis to create new kinds of predictive business models that will drive the decisionmaking in the future.
But Big Data is also a broad and informal term used to refer to the vast amounts of raw data generated by global online networks and an ever-increasing variety of data-capturing digital technologies. “All the stuff we do online” is how Jake Freivald, v-p, corporate marketing at Information Builders, characterized it. His company, a business intelligence and data analysis firm very much involved in Big Data, spoke on the topic at BISG’s recent Making Information Pay conference.
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In an era when more people than ever are shopping online and consumers are making use of digital apps, e-books, and digital reading devices, all of which capture and transmit a wide variety of usage data back to publishers and retailers, “Big Data holds the promise of helping publishers make better decisions,” Steele said. Publishers can get feedback on how long a reader stays on a certain page or why readers have stopped reading on a certain page. “E-books allow you to modify pricing, and data analysis will let you see how the market responds in real-time, and make changes,” Steele says. Indeed the aggregation, processing, and deep analysis of this kind of data set gives publishers the ability to tie consumer purchases to a promotion, to their friends’ purchases, to reviews, and more.
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Todd Lipcon, an engineer with the Apache Hadoop project management committee, emphasizes that most publishers will make use of Big Data by way of vendors and middlemen rather than try to set up their own processing in-house. Apache Hadoop is described as the core technology driving the adoption of Big Data and the ability to quickly and economically process the huge datasets. “Smaller companies may not need to use it but they still need to think about the kinds of data they do need to collect and whether collecting more data could help their business,” says Lipcon.
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“Publishers aren’t quite there yet,” says Dumbill, referring to the number of publishers he sees at the Strata conferences. Utilizing Big Data projections, he says, will mean a shift from “operational applications to creative and profitmaking applications, in other words, the ability to uncover [new business] opportunities. You have to dig deeply into this information and it will change how a business views data. You will find stuff that you might have missed in the past.”
But Dumbill also makes it clear that Big Data “can also be controversial. You may find out that the grand old men that are supposed to know how the business works may not know it so well. It’s a completely different way of doing business.”
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Bookseer and CoverCake, two recent startups focused on data collection in the book market, have positioned themselves (with differing initial results) as Big Data solutions for book publishers, offering to provide data that will help them decide which promotions are working and which one’s are not.
Launched less than a year ago, Bookseer is a market analysis and intelligence firm based in London and New York, designed to provide data services—with a focus on book marketing—specifically to the publishing market. Started by U.K. publishing veteran Peter Collingridge and technologist Stephen Betts, Bookseer can track and collect data from a wide variety of media outlets—from Twitter, Facebook, and blogs to Amazon sales, Nielsen BookScan sales reports, Google searches, and BitTorrent. After collecting the data, the Bookseer technology can superimpose a timeline of each data feed in a visual outline that allows a publisher to essentially connect the dots. If the marketing department launched an ad campaign or an author is appearing on Good Morning America, Bookseer can provide evidence that a campaign or media appearance very likely caused a spike in print or e-book sales—or didn’t. Collingridge says Big Data has the potential to make book marketing a “demand-driven” practice rather than one driven by supply or by a publisher’s intuition. Collingridge says, “[Publishers] have lots of marketing that doesn’t work and yet they keep throwing money at it because there’s never been a way to measure this stuff. Now, if something’s not working, we can see it and try something else.”
Link to the rest at Publishers Weekly
In a former life, PG was an executive with a company that built software used in business intelligence and big data applications.
Massive and sophisticated data analysis is built into Amazon’s DNA. Contrary to popular opinion, PG believes the key to Amazon’s success is not low prices (although they’re important), but paying very close attention to customer behavior and constantly upgrading the Amazon experience for its customers.
Incidentally, Amazon is not the first major retailer to do this. Extremely sophisticated data collection and analysis was the key to Wal-Mart’s rise during the 1980’s and 90’s to preeminence in meatspace retailing. Wal-Mart’s system could allow someone at corporate headquarters in Bentonville, Arkansas, to monitor sales at a single cash register in a store in Minneapolis.
As with so many things, utilizing the benefits of big data may not fit well within the dominant culture of Big Publishing. It requires a giant mindset change and costs a lot of money to do well.