Reader analytics are garnering huge attention at the moment and there are at least four major talks at this year’s Frankfurt Book Fair discussing how and why publishers and authors can collect data on their readers. But with reader analytics taking the spotlight in publishing, the debate over the ethics of data harvesting and its uses has been brought to our doorstep.
Consensual data is happy data
The big issues around data harvesting are not just what information businesses and official organisations are collecting about us, it’s whether or not they’re doing it with our consent. For once, however, publishing is ahead of the curve on getting this one right.
Although big boys like Amazon remain the mysterious bastions of data collection they’ve always been, smaller companies specialising in reader analytics are proving to be honest, open and respectful about harvesting data. For example, Jellybooks use “reading campaigns” for as-yet unreleased books to provide information to publishers, in a similar way that a screen test would for a film studio. Jellybooks gathers data from readers who have volunteered to be monitored and received a free digital copy of the campaign book, which is clearly marked, so that the reader remembers they’re being observed.
What’s more, while Jellybooks have said that “though in principle [non-anonymised] data could be provided to the author or publisher” they do not give it. Despite some rumours, Jellybooks also does not gather data by measuring eye-movement, but by observing how the reader interacts with their app as they read. Jellybooks, and most reader analytics collectors, are more interested in the time of day consumers read, how long they read for, when they highlight or perform searches on text, and the operating system, device or browser being used. These are added to information the reader voluntarily provides, such as gender and age.
When working with companies like Jellybooks, publishers don’t need to feel compromised about using this data: it’s not an invasion, it’s a gift!
Data driven decisions
But why is data such hot property in the first place? Some have wondered – both in horror and hope – that reader analytics might effect the editorial process, but Jellybooks has said that this misunderstands how people read and the kind of data reader analytics can collect: “Readers judge a book as a whole based on storyline, language, characters, plot, etc. and not on individual chapters.” Though the data can be utilised in this way, knowing that “x” number of people dropped off at page 57 is not necessarily helpful to an author or a publisher.
Excitingly, what reader analytics can provide are evidence-based assessments of how a book is likely to perform in the market. Data on completion rates and recommendations gathered during the commissioning stage, for example, can help reduce the risk inherent in signing new books by indicating whether or not a book might be popular.
Later in the publishing process, analytics can also help marketing departments figure out how much budget to assign to their titles, what their audience looks like and how to find them – are they young or old, male or female? Do they binge-read on beach holidays, meaning you should get WHSmith Travel on board, or do they dip in on their on their commute to work, meaning you can grab them with a poster on the tube?
Best of all, this data is available via third-party companies like Jellybooks, meaning that although publishers have to pay fees for their data, they don’t need to make the huge investments in building platforms and software that was previously required. This information is more easily available to publishers than ever before.
Scratching the surface
Reader analytics still clearly has its limits and they may never become a magic wand for book sales, but the truth is that the possibilities for using this data are only just starting to be explored. Moreover, the software for collecting this data are still in its – albeit impressive – infancy. Looking ahead there is talk of Jellybooks developing some kind of “FitBit for books,” which will take retail copies of books into account as well as the pre-sales titles currently available. Others claim that one day soon we will be able to use data to predict the next big bestseller.
There can be no arguing that data harvesting is here to stay. The only, opportunity-filled question remains: how else are we going to use it?