Expert publishing blog opinions are solely those of the blogger and not necessarily endorsed by DBW.
In the first post in this series, I introduced the notion of the “Internet of Bookish Things” to describe how ebooks are now nodes on the Internet that can record how books are being read. Over the past two weeks, I followed up with “Reading Fast and Slow – Observing Book Readers in Their Natural Habitat” and “Start Strong or Lose Your Readers.” This week, we will explore a book’s recommendation factor—how likely it is that readers will recommend a book to others, and how this relates to reading behavior.
So what makes readers recommend a book? And can we measure the books that have that X-factor, or—as we at Jellybooks prefer to call it—a high recommendation factor?
In 2003, business writer and strategist Fred Reicheld introduced the concept of the “Net Promoter Score” in the Harvard Business Review as the “one number you need to grow.” The score is a simple but highly effective tool for measuring customer satisfaction. Reicheld later elaborated on the concept in his book The Ultimate Question.
The Net Promoter Score is based on a simple question: Would you recommend this book to a friend?
The reader is asked to answer this question on a scale of 0-10, in which 0 means “definitely not,” 5 means “neutral” and 10 means “absolutely.”
Those who choose 9 or 10 out are considered “promoters.” i.e. strong advocates of the book, those who choose 7 or 8 are considered “neutrals,” and those who choose between 6 and 0 are considered “detractors.” The percentage of those indicating between 6 and 0 is then subtracted from the percentage choosing 9 or 10. The resulting percentage is the Net Promoter Score or NPS.
The NPS is widely used in business as a key metric to grow revenues, as happy customers will typically tell others about the great service or product they received. In publishing, we call this trend “word of mouth,” and it is one of the key drivers of book sales.
At Jellybooks we first used the methodology in a pilot with Simon & Schuster, but with a twist. We surveyed users separately based on whether they had read the book from start to finish or if they had abandoned the book. We then proceeded to calculate a separate score, which we call the “recommendation factor,” for each group or cohort.
Let’s have a look at the results for one specific book.
Those who finished it rated the book as follows:
The recommendation factor for this book was 64 percent – 5 percent = 59 percent. That’s a pretty whopping result.
Note that 120 readers described this book as “awesome,” 190 readers said it was “great,” 70 thought it was “gripping,” 90 described it as “entertaining” and a mere 60 said it was just “good” (multiple answers were allowed). None of the readers who finished the book (including those rating it 0-6) described it as “boring,” “disappointing” or “did not meet my taste.”
Thus, deeming a book “good” does not mean that the reader will strongly recommend it.
Now let us look at the results for those readers who did not finish the book. The title had a completion rate of about 70 percent, so 30 percent of readers did not finish the book; not everybody chose to answer the survey:
The recommendation factor for this book amongst those who did not finish the book was 0 percent minus 33 percent, so negative 33 percent; the difference in recommendation factor between those who finished the book, and those who did not was more than 90 percentage points. That’s a big difference. One swallow does not make a summer, but we have seen this large of a difference in book after book we have tested and surveyed. Readers who don’t finish a book are very unlikely to recommend a book they abandoned. This of course sounds utterly logical and intuitive, but has anybody ever scientifically measured it? We think not!
What’s more, we often hear editors and publishers say to us, “What do I care if people read my books as long as they buy them?” Well, word of mouth is one of the most powerful drivers of book sales. So if reading the book is a prerequisite to recommending it, then authors, agents and publishers should surely care whether book buyers are reading them, lest sales peter out like water in the dessert.
Now of course some books generate great sales on the back of hugely influential reviews, winning major prizes, like the Nobel or Man Booker, and sell on the back of those esteemed endorsements. But if the books are not read, there is no word of mouth and sales potential is limited to the power and influence those gatekeepers still have.
For most other books, word of mouth is one of the key factors that propels a title onto the bestseller list. After that, success involves paying attention to buyers reading the book and being sufficiently engaged by it in order to recommend it to friends. Both of these factors, thankfully, can be measured. The former is the completion rate, as detailed in my earlier posts, and the latter is the recommendation factor.
Now, there is a special case of a modest completion factor (most readers do not finish the book), but a sky-high recommendation factor. We recently encountered such a book, which was a work of non-fiction. Digging into the data, we discovered that those who finished the book were mostly male and over 45 years of age (we ask participants in our reader analytics trials for their age and gender before handing over a free ebook). In other words, this book had niche appeal. Within that niche, however, the completion rate was in fact very high (60 percent compared to 20 percent for a general audience) and the recommendation factor for those who finished it was over 80 percent. This showed the marketing team how to better position and market the book for success. Welcome to the world of data-smart publishing!
Note: All the data reported in this post was collected in pilot projects financed by Innovate UK. EPUB3 files were modified with candy.js by Jellybooks so we could record, store and extract the user’s reading behavior when using iBooks, Adobe Digital Editions (ADE) and selected Android reading applications. The data stored within the ebook file was extracted when the user clicked a “sync” button in the book. All users were informed about the presence of the analytics software.
We will also be holding a workshop on data-smart book publishing at the upcoming Digital Book World Conference in New York City. The workshop takes place on Monday, March 7th from 2pm to 5pm, just prior to the main DBW conference. We will look at the challenges publishers face in collecting data, making sense of data and applying it so they can publish smarter, more efficiently and more profitably. The workshop will include speakers from Elsevier, Piper (Bonnier Germany) and others sharing their experience of turning themselves into data-smart publishers.
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