Individualization Is the New Personalization — AI Meets Content Marketing in 2018


This post was originally published in Target Marketing.

How we navigate the universe is decidedly omnichannel, so one digital platform or touchpoint does not bear more influence on customer purchases than another. Instead, how and why consumers engage and take action is tightly tied to their interests as individuals.

In 2018, brands will continue to crash into the wall of customer identity. Why? It will become clearer and clearer that content marketing programs organized by channel are often unproductive, inefficient and do not optimize results.

As marketers look to take the business results generated by content marketing to a new level in 2018, here are predictions they should heed:

1.Individualization Over Personalization

Customers will no longer accept one-size-fits-some content experiences, so neither should marketers.

For years, marketers have been trying to harness segmentation as a way to employ personalization. But in today’s world, customers expect content experiences that clearly put “me, myself and I” as the priority.

The average person is exposed to 577 marketing messages every day, and that message volume is growing. Despite this, customers filter out all but the most compelling content and then consume the material they love obsessively. Indeed, 70 percent of consumers surveyed by Accenture reported feeling open to more content, especially if it was tailored to their tastes.

For true personalization to occur, content must unequivocally be targeted to each person’s unique interests through an individualization strategy.

To achieve individualization, marketers should deliver content experiences to a segment of one, optimized in real-time based on the actions and preferences inextricably tied to that specific customer’s identity. These could include individual content consumption patterns by topic, categories or time of engagement, for example.

Understanding and tracking individual content preferences that are part of customer identity data can help direct a more strategic content development, distribution and marketing roadmap.

2. Individualization Needs AI

To achieve individualization, artificial intelligence and machine learning will be constant, reliable companions.

Marketers have been spending a disproportionate amount of time on workflow and project management — trying to organize and produce content at scale, while addressing channel proliferation and showing a measurable return on their investment. Some say it’s the holy grail marketers have struggled to solve since the dawning of the digital age — to get the right content in front of the right person at the right time, in the most efficient way possible.

Studies show that to personalize, content marketers have been using a variety of methods — 27 percent have a manual process, 40 percent use some automation with manual processes, 28 percent mostly automate the process with occasional manual intervention, and five percent use a completely automated process. But when major companies are creating over one million digital assets per year, on average, it is impossible for them to manually set up and consistently optimize content to individuals.

In 2018, advances in artificial intelligence and machine learning put the data and analytics in marketers’ hands that allows them to easily see — on an individualized, real-time basis — the content with which their audiences are engaging, as well as when and where. As such, brands will glean accurate trends and insights critical for implementing content marketing strategies based on customer identity and building one-to-one customer relationships.

Even more important, with such robust tools they will have an ability to adjust their content strategies on-the-fly to reach highly engaged, high value individuals. Gartner projects that by 2020, smart personalization engines used to recognize customer intent will enable digital businesses to increase their profits by up to 15 percent.

In 2018, deeper content intelligence will illuminate individual customer content preferences for marketers, and machine learning algorithms will ensure automated cross-channel distribution of content to those individuals is based on what they are most interested in — at the right time. Invariably, content campaign management will become extinct, replaced and guided by data-driven individualization that will also usher in a new era of more dynamic, effective and creative content production fueling an “always on” scalable content marketing strategy.


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