To talk about the future of the digital publishing industry, we have to talk about tech innovations like big data and predictive analytics. For some publishers, this is intimidating stuff. And I get that. Change is hard. It can be challenging to get a handle on these innovations, and to see how they can help you as a publisher. But once you do...wow, it's exciting and, dare I say, inspiring.
To get you excited, let’s take a look at these technologies, what they are and how they can help you be a more efficient and profitable publisher.
Big Data “is the ability to customize and personalize a user experience based on what you know about that user." Some of the best examples of big data are in advertising. With big data, advertisers are instantly able to gather information about users and use that data to create new ads that are user-specific and speak to an individual’s needs and interests.
Beyond the ads themselves, big data makes life much easier for advertising sales professionals. Like publishers, sales people in advertising have an abundance of data sources to digest, including different territories and disparate spreadsheets. Before big data, it could take up to two days to process all that data and give sales people access to it--an eternity in advertising.
Publishers are hampered by a similar scenario. Processing data from different territories, retailers and currencies typically takes up to 90 days. That kind of delay makes it very difficult, if not impossible, to see how your promotional efforts are impacting sales. Not only that, but aggregating all this data is time consuming.
With big data, what was once a cumbersome process becomes streamlined. Advertising sales teams, for example, can now get access to all the data they need in “about 8 seconds.”
As a publisher, just imagine how much easier that kind of immediate access to data would make your life. That once cumbersome sales reporting process becomes as simple as clicking a button. Instead of waiting 90 days, you could see each day exactly how well your titles were doing in all your territories and with which retailers. You’d see which marketing activities were having a positive impact and which weren’t, and adjust accordingly. You’d go from gut-based decisions to data-driven ones. No more messy spreadsheets, no more complicated pivot tables. With big data, you would be a far more efficient and profitable publisher.
Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends (for a deeper dive, go here). The most relevant example of predictive analytics is Amazon’s “recommended for you” function.
Here’s a snapshot of my personal Amazon page. Based on my previous purchases, Amazon can recommend similar books that I might enjoy. And by and large, it’s pretty accurate. Each of the items look interesting to me, and I’d be willing to buy at least two of them.
On the surface this isn’t that revelatory. Amazon has had this function for a while. But imagine what you could do with even this simple version of predictive analytics. You could take a similar “recommended for you” function and add it to the end of your eBooks. That way, readers are seeing other books in your catalog that are similar to what they’ve just read and have the opportunity to purchase them right there and then.
Predictive analytics will also give publishers unprecedented insight into who their customers are. The more you know about who your audience is, the more you know what they want. And that information is gold.
Imagine having data that tells you even before you sign a book what audience it will appeal to. That same data can give you actionable insight into how to market that title as well. After all, if you know enough about your audience to calculate more precisely than ever what they will like in a book, you can determine with the same level of accuracy the marketing messages they’ll respond to.
Predictive analytics also gives you insight into emerging trends. You can see early on which trends in subject matter are on the rise, as well as territories and genres. Sure, that information is available today, but it's generally limited to annual reports from Nielsen BookScan. Predictive analytics can give you the same (arguably better) data, but based on your specific titles, authors and territories, and it can give it to you whenever you want it.
Justin Marks is a Content Marketing Manager at Vearsa. When he’s not helping publishers run and grow their eBooks business, he’s running his own small publishing company. Oh, and he loves cookies.
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