there is a story behind every book

Publisher’s Key Performance Indicators for Reader Engagement

Jellybooks records a wealth of data from participating readers, but raw data by itself is insufficient for publishers to make decisions. Jellybooks does not stop at data collection though. We process, aggregate, analyse and visualise the data as well. Jellybooks uses data to tell a story about the book, the story of how readers engage with the cover, the description, the content and more.

One of the means by which Jellybooks tells the story behind the book is to focus on several key performance indicators (KPIs) that we summarize in numbers and four simple colours for weak, good, very good and excellent, but also bring to life as interactive graphs.

The key parameters are:

Reader Completion Rate

A book’s completion rate is the percentage of readers who start the book and also finish the book. The lower the percentage the more users give up on the book mid-stream, though the completion rate is often decided in a book’s first 100 pages. In calculating the completion rate we exclude those readers who downloaded the book, but didn’t get started (life got in the way, a better book popped up or any of a million other reasons).

The completion rate is a very powerful indicator of how strongly the content engages readers. It is one of the core KPIs for measuring reader satisfaction with content. If readers didn’t finish the novel, it was probably not that great.

Book Recommendation Factor

This is an adaptation of the Net Promoter Score (NPS) concept. We ask readers after they have finished reading the book, if they would recommend the book to friends. In calculating this KPI, we only use the response from those who genuinely finished the book and then calculate a percentage reflecting the balance of promoters and detractors for the book. The recommendation factor is a strong indicator of the word-of-mouth potential for a book.

Cover Match Factor

This is an indicator measuring if readers thought the content of the book matched the expectation raised by the cover. We don’t ask readers if the cover is pretty or would make them pick the book (we test the latter through A/B cover tests). What we measure is “Did the cover deliver what it promised”. There is no point having a cover promising the reader one thing, when the book is in fact about something else. Advertising – and a book’s cover is advertising - that does not deliver what it promises has a tendency to dampen or even kill sales. In our tests with large publishers, miss-designed covers have been a leading cause for great and engaging books not actually selling.

We colour code the results for each KPI so you know if the results is poor (blue), good (yellow), very good (green) or excellent (purple) for the particular category.

You don’t need an analyst or data scientist to evaluate the data. Anybody in a publishing house from editor to publicist, marketing specialist or social media interns can make use of the data. This is smart data not big data and it is at its most powerful when shared across the team and with the author.

Let's look at each of these KPIs in more detail on the next couple of pages.

Contact us about Reader Analytics