Expert publishing blog opinions are solely those of the blogger and not necessarily endorsed by DBW.
Consumption habits across industries, spanning different products and services, are evolving dramatically in the digital era. And the book publishing sector is not immune to these winds of change.
Like film, music and other forms of content, books, too, are undergoing a major transformation in terms of both development and distribution, thanks to rapidly changing customer expectations. Empowered readers today demand an intuitive user experience, as well as personalized, engaging and interactive content, for both academic and non-academic books.
Unfortunately, the near-term growth outlook for book publishers looks rather lackluster. According to a PwC report, the industry is expected to expand at a compound annual growth rate of about 1.7 percent over the next five years.
Suffice it to say, maintaining the status quo will not help. In order to sustain relevance in a dynamic marketplace—as well as boost revenues and profitability—publishers will have to embrace innovation by leveraging disruptive digital technologies. Specifically, they must overhaul their current approach toward product development and marketing for enhanced agility and customer alignment.
This requires compelling, actionable insights on readers’ behavior and needs that can foster smart decision-making.
Mining Data for Reader Insights
To unearth insights on various aspects of readers’ engagement (or lack thereof) with books, publishers need to deploy sophisticated data analytics tools and systems. This is critical, considering that book connoisseurs today consume and share content on a host of different digital platforms.
And for aggregating, curating and analyzing the massive volume of structured and unstructured data, “big data” can come in handy. Advanced data analytics setups can help publishers source, store and mine relevant data from an increasing number of accessible information sources, including social media, sensors, live video feeds, Google searches, emails and government sources.
This, in turn, can pave the way for effective tracking of content consumption patterns across various phases of the reader’s experience lifecycle.
In fact, many publishers have already started rolling out big data programs. For instance, at Penguin Random House UK, decisions pertaining to the publishing process are informed by the company’s integrated consumer insights initiatives. Likewise, Barnes & Noble has invested in an enterprise data warehouse to gain comprehensive knowledge of its customers’ reading habits through exhaustive analysis of in-house data, running into terabytes.
Overhauling Content Development
The education segment is poised to record the fastest rate of growth among all book publishing sub-sectors in the next five years. To capitalize on this significant opportunity for top-line expansion, educational publishers will, however, have to revamp their current gut-based approach toward editorial content development, and pivot to data-driven decision-making.
Gone are the days when instructors’ feedback on curriculum material was the sole determinant of subsequent iterations in pedagogic content modules. In a direct-to-customer world dominated by social media networking, publishers can gain real-time and more comprehensive feedback from their end readers.
By aggregating and tracking tweet hashtags, Facebook likes and online book reviews, firms can glean in-depth insights around student and teacher opinions. This is where natural language processing technologies can play an enabling role by performing semantic analysis of user sentiment, thereby letting publishers adapt their editorial plans accordingly.
It also makes business sense for content creators and distributors to analyze learning outcomes at individual levels. For example, AltSchool, a collaborative group of micro-schools operating in Silicon Valley and New York City, uses proprietary software to collect huge amounts of information on each enrolled student. By mining various parameters concerning a student’s academic profile–including learning patterns and outcomes, social habits, and levels of engagement with content–AltSchool has been able to tailor its learning resources and methodologies.
Publishers can take a page out of the AltSchool book to capture and respond to user data at a granular level. This will help them gauge the effectiveness of their content, and customize their educational publications according to the needs of K-12 and high school students. The end result would be the creation of a loyal customer base receptive to increased cross-selling and up-selling.
Likewise, publishers operating in the higher education segment must proactively engage with the ecosystem of faculty, students, alumni and administrators to capture data relating to learners’ and teachers’ experiences. Insights generated from an analysis of this data can be used to create more engaging and interactive content, incentivizing higher student enrollments and course completion rates.
As a case in point, prominent academic publisher Elsevier created with a massive open online course (MOOC) a few years ago to gain direct access to the higher education ecosystem and bolster traditional sales.
Another unique way big data analytics can power content innovation is by helping publishers better understand readers’ affinity for various configurations of a given product. Customer insights around these dimensions can allow book companies to deliver the ideal product mix, at both general and personalized levels.
For instance, Elsevier has used data capture, search and analysis tools to create the “article of the future,” an innovative article format involving enhanced functionalities, including tagged and searchable audio files, videos, interactive images and embedded maps. The publisher has been able to leverage this template for providing its audience with a unique and truly dynamic reading experience.
Big data can also help drive increased sales and brand loyalty for non-educational publishers, by fostering a transformation of their marketing function.
In a highly cluttered marketplace, publishers need to formulate distinct (and unique) content positioning strategies, and undertake targeted, informed marketing campaigns for higher mindshare and return on investments (ROI).
Sophisticated data aggregation and mining tools can enable publishers to blend consumer insights with their product pricing and marketing strategies, and better understand why a certain book or series was not successful. Big data can also help determine the most profitable markets and evaluate the unique interests and preferences of readers in them. Based on these findings, publishers can craft relevant promotional and advertising strategies to achieve optimum sales.
Conversely, predictive analytics can help companies effectively forecast demand for different titles across genres, based on their sales patterns, as well as those concerning the overall industry. Firms can use these insights to conceptualize and execute relevant customer outreach initiatives—across different engagement channels—that resonate with the target audience.
Data mining can also be used to answer key questions related to content discoverability, purchase and consumption. Where and how do readers find books? What factors influence a purchase decision? What are the reading habits of bargain shoppers?
The good news for publishers is that they can now access tools such as Google Analytics and Shopify, which facilitate cost-effective collection of data around cart abandonment, IP addresses, clickstreams, traffic sources, and so on.
Armed with a holistic understanding of their audiences, publishers can optimize pricing based on location, categories and performance. By analyzing metrics concerning reader engagement and sales across different product categories, publishers can tweak their marketing plans, as well as make informed decisions on when and how much to invest in an author.
Another tangible way big data can shape marketing optimization is by delivering concrete insights on packaging of books. Reader analytics can be harnessed to craft relevant and attractive cover designs that help catalyze sales.
Rebuilding Customer Relationships
Finally, reasserting control over customer relationships is something book publishers can realistically hope to achieve through the institutionalization of big data. Over the years, online retailers such as Amazon have leveraged transactional and click data gathered across touch points to offer relevant deals and recommendations, emerging as gatekeepers who maintain strong control over readers.
Publishers can reclaim this lost space by establishing direct customer engagement channels, and reducing their dependence on intermediaries, to capture, own and harness their own big data. Firms could look at establishing dedicated reader interaction hubs—through mobile apps and online platforms—and offering effective avenues for their different audience segments to communicate with each other. This could potentially help companies increase cross-selling and up-selling to existing customers, as well as increase brand affinity.
An interesting example is Random House, which is leveraging big data insights to launch personalized marketing campaigns through its BookScout app . Similarly, Globe Pequot Press has used data-based insights to enhance customer engagement via its Falcon.com website, an online community for outdoor enthusiasts.
Going forward, the fundamental imperative for both education and non-academic publishers will be to effectively use data to transform themselves into dynamic, nimble businesses that can respond swiftly to changing reader requirements.
For companies to sustain competitive advantage, data-driven decision-making around product development and marketing will be vital, as they transition from the traditional print environment to a landscape characterized by multiple content creation and distribution formats.
To that end, big data could certainly play a major enabling role in this regard, by promoting development of relevant content for different audience niches, as well as effective cross-channel reader engagement for higher marketing ROI.
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