Within the world of customer engagement, predictive analytics have revolutionized the ability for enterprises to match materials with the audiences most suited to appreciate them. In regards to content, this has traditionally meant creating channels based on customer profiles and then funneling content to the appropriate market. Now, with the increasing sophistication of analytic algorithms – combined with a component-based, hypertext approach to content creation that XML vocabularies such as DITA enable – content can be configured on demand, customized to match the consumer profile.
"Content can now be configured on demand, customized to match the consumer profile."
Descriptive versus predictive
The key to this evolution is the transition from descriptive to predictive and on to prescriptive marketing. In the traditional customer profile, hindsight is 20/20 in the eyes of the marketer: existing materials are evaluated based on how they did previously. This is a simple descriptive process, but it limits the ability to better match content to customer needs except by small evolutions or by accident.
With predictive analytics, marketers can build "a fluid and multi-dimensional map of prospect interests," according to Ilan Mintz, Marketing Coordinator at Penguin Strategies. Mintz describes how predictive content analytics aggregates data within the pieces a user reads, then builds and catalogs a topic composite akin to a word cloud. From there, the composite is tied to the profile of that user or user group.
Mintz claims that this approach to content marketing allows for a graphical view of content-related interest. This in turn facilitates new insights, such as:
- Content personalization.
- Competitor analysis.
- Anticipation of trends.
- Lead nurturing and tracking/predicting sales cycles.
In all, Mintz points to the increased ability to target audiences with personalized content as the return on investment in content data analysis.
More content than ever
This has given new power to marketers and content authors, particularly in an environment that is already awash in materials. Digital content is at a higher premium than ever according to the Content Marketing Institute, with 70 percent of B2B content marketers in 2014 saying they created more content than the previous year, with no end in sight for the trend. However, increased volumes isn't a meaningful measure of success for marketers. The impact of the content, which in and of itself is defined by the goals of those who run lines of business, must be measured and interpreted – and, according to Tjeerd Brenninkmeijer and Arjé Cahn, co-founders of Hippo, engagement metrics are a "notoriously fluffy" and increasingly unhelpful way to appraise successful content.
"Over the next two years, predictive content analytics will provide smart businesses a means of gaining better insight into customer's interactions with content," the Hippo co-founders told CMSWire. "And by equipping their marketers with better access to analytics and more decision-making power, businesses will reap the benefits."
Through a deepened understanding of the role that predictive analytics can play in modern content marketing, authors and marketers have more effective tools to affect customer engagement.