Electronic publishing industry is waking up to the possibilities of Big Data Analytics. By definition, Big Data Analytics means mining and analysis of data sources and massive volumes of data to discover user patterns, correlations, emerging trends, and resultant revenue impact. Businesses worldwide have begun to employ such valuable pieces of information to better understand market dynamics and user preferences in order to make informed decisions that have a direct impact on the bottom line.
As the popularity and usage of eBooks soar, Big Data Analytics offers a huge opportunity for eBook publishers to analyze end user consumption patterns and maximize sales.
Here are a few examples of user data that eBook publishers can gather from exploring their content repositories:
- Understand sales patterns
Gather information about the users’ geographical location and demographics such as gender, age, profession
- Find out how time/ month/ holidays/ seasons effect the sales of certain eBooks
Understand the buying patterns and correlations
- Discover particulars such as what pages of a book is read most/least, who is the favorite/ least favorite author in an anthology, where in the book does users spend the most amount of time, do people re-read the books
- Understand the sales trends in an author’s collection such as has a buyer purchased multiple books by the same author and so on and so forth.
- Obviously, unstructured data as such is not useful. What matters is how you interpret the data intelligently and use the analysis to gain a comprehensive perception and competitive edge.
Inferences derived by analyzing data can be used to:
- Decide on marketing strategies
- Provide recommendations to readers/buyers
- Help you give suggestions and guidance to authors in order to improve the quality of the book
- Provide titles that are more relevant and in demand with your target audience
- Vary pricing and determine discount programs
- Choose the best time/season and location to launch eBooks
- Help you decide what languages the content be made available
- Plan book tours and other promotional activities.
Consider a scenario where a children’s eBook publisher wants to launch a three-day marketing campaign for promoting a new eBook. Would it be better to let the campaign run from Monday through Wednesday or should the campaign run over the weekend? Analysis of buying patterns from the online store could indicate that most parents buy books for children on Saturdays and Sundays. This information would help make a better choice on when to run the campaign.
In the world of online content, time seems to travel faster and data tends to get outdated quicker. Therefore, gathering feedback about your eBook and reacting swiftly to fast-emerging trends is crucial.
Challenges of Data Analytics
Gathering adequate amount of reliable data for analytics systems is vital in providing statistically accurate predictions. Predictions made based on small data sets can cause more damage than benefits.
The other important aspect to consider is the buyers’/users’ confidentiality. It is not appropriate to gather information about users without their permission. A number of legislations have been passed to protect individual privacy on the internet and regulate the kind of information that can be collected from internet users.
Data Analytics at iPublishCentral
Publishers that use iPublishCentral as their eBook delivery platform have already begun to benefit in manifold ways from data analytics. For example, data about buying and reading patterns was used to provide suggestions in grouping books into collections. These collections have been well received and have contributed to increased retail revenue.
Well, we haven’t gotten to providing accurate alternative endings to eBooks based on personality types or modify the content of eBooks centered on learning habits of individuals. However, Big Data Analytics can provide powerful and advantageous business insights that can be used to improve quality, ease usage, and increase popularity of eBooks and revenue.