There’s an old saying in the publishing industry that “Content is King”, meaning that the creation and curation of the written word is of paramount importance. And it’s still mostly true, but there’s at least one significant corner of the industry where there is a new challenger to the throne. And that’s in the B2B Media sector, where companies publish digital and print magazines aimed at business professionals in specific industries. Many have developed significant revenues from webinars, events, and social media outreach. The new king in all this is DATA, “Big Data” as it’s often called, and along with all that big data comes a big new problem.

It’s true that the availability of business data in publishing is very high compared to many other industries. Publishers collect data from many sources: from prospects and customers, from their own internal systems, from social media, the internet, and even competitors. There’s no shortage of good data – the problem is that it’s not organized or collated into information that allows business leaders to make insightful business decisions.

The Silo Problem

Because of the multiplicity of sources, the data that publishers collect results in data silos, or banks of separate data, gathered mainly for consumption by internal legacy applications. This makes it difficult for management to see the “big picture” without the right tools – and the right culture.

There are several things that publishers can do to transform this siloed data into valuable information. And to solve the question, we need to look at the root causes of the silo issue.  They are threefold:

  • Organization structure
  • Company culture, and
  • Outdated legacy software

Organizational Structure

Publishing companies, as in other industries, are often organized around business functions such as marketing, sales, and production for example. And the data that each department needs to address their own requirements, has an insular nature, rather than an outward-looking business orientation. We must consider data more as a company-wide resource and make it department-agnostic, instead of looking at it as just feeding a particular department’s operational needs. No single department should “own” the data, it should be viewed as a shared asset.

Company Culture

The problem above is often made worse because many departments don’t work directly together, although they do share aspects of the same data. This can result in some departments denying access to data that they regard as their own, based on the application in question. And with the abundance of cloud applications available today, it’s common to have a “Shadow IT” problem, where some applications operate in individual departments, that are completely unknown to the company’s central IT group.

Technology

Old legacy systems that were designed to address specific operational needs, tend to isolate data into silos anyway. These silos are difficult to integrate into newer external systems and often are poorly supported because the skilled resources are no longer available. Loosely related legacy systems often accumulate in organizations that have no standard approach to technology and do not use a single technology platform.

So the net result is that publishers often have a lack of coordinated, unified data, where duplication abounds (often leading to turf wars and infighting over whose data is better), resulting in higher costs, poor productivity and very limited collaboration. No wonder that management is frustrated with their inability to see the big picture!

Silo-Busting

Like many challenging business problems, this issue cannot be resolved without the active support and participation of top management. Re-thinking of data as a company resource takes dedication and commitment from the top to change both the company culture, and where necessary, the organization AND the product. Management must commit to a single open platform in which data is seen from a customer’s viewpoint. Leaders need to change the company culture from one which is product-centric, to one which is customer-centric to be more successful. The effort must be focused and sustained. It demands an ongoing process of continuous product development based on field data. A good example of this is that of a well-known on-line financial newsfeed that adapts its subscriber content using real-time data on exactly where that consumer is in the world at the time of pushing out the copy. They actually shrink the feed to supply only geographically-relevant information that is far more likely to gain immediate interest and to generate a loyal long-term customer. The information is valuable to the reader because it’s both precise, timely and tailored to that particular reader’s interest on an ongoing basis.

How is this done in practice?

It’s important to look at customer sales, not as single transactions, but as a customer journey by building a community with buyers. Modern software tools can help. Customer Engagement and Audience Building software tools are important to the mission of building loyalty. The software develops a “persona”, which defines the characteristics and behavior of the ideal target individual. Then by matching the massive files of acquired consumer data to the “persona” using AI and machine learning techniques, the publisher can create targeted marketing and social media campaigns addressed directly to those matched individuals. The publisher creates timely promotional content that matches that customer’s behavior and perspectives that is more likely to get and keep a customer if sustained over a period of time.

Of course, before the “massive files” of consumer data can be used in this way, we need to unify the data, so that it is “de-siloed”, matched and merged and duplicate data is eliminated. It demands a centralized information processing model, where most functions are integrated. It contains pre-built interfaces to external systems such as Salesforce and Oracle at the front-end, and Business Intelligence at the back end that allow the users to begin to see commonality and patterns in the resulting information. The use of real-time dashboards, for example, helps in presenting condensed and coordinated views of customer behavior, and as a result, provides real insights into how, when, and through which media we should address that particular customer. The essential first step is to change the company culture to treat data as an application-agnostic, company-wide resource, gathered from many internal and external sources, that is managed and controlled centrally on a single platform. If we do that, we can realize the holy grail of providing management with real and timely insights into how to get and keep a customer.