The growth of content marketing and the need for marketers to populate an expanding number of channels with high-quality content is keeping marketing executives up late at night. As the amount of content needed to create superior customer experiences continues to rise, it’s important to answer one question. Why is content marketing growing? Simple…the payoff is huge. Hyper-personalized content that targets every customer’s unique interests helps improve the customer experience which, in turn, increases customer loyalty. According to Dawn Papandrea of NewsCred Insights, “content marketing revenues are projected to grow at a 14.4 percent compound annual growth rate from 2017 to 2021.”

The question then becomes, how can marketers satisfy this unquenchable desire for new content? One technology that helps tackle the need for developing and delivering a constant stream of personalized content to customers is natural language generation (NLG).

NLG is an AI-driven software solution that extracts data from a variety of sources to produce naturally worded prose. In this way, it transforms massive amounts of data—raw data and metadata (such as style and color)—into human-readable text. Last year I wrote about NLG and defined it, according to Kaushal Mody of Accenture, as “Natural language generation uses machine learning to mimic the ways human analysts learn from data and provide recommendations for action. As such, the technology turns raw data into human narratives; communicating meaning in the same way people do, and providing complete transparency into how analytical decisions are made.”

Imagine auto-creating copy for thousands of products in seconds, or auto-generating stock performance reports with lightning speed. NLG, in which a computer writes something, is not to be confused with Natural Language Processing, in which a computer reads something, or Natural Language Understanding, in which a computer understands something, as in the case of chatbots.

The market appears headed for growth as analyst firm Gartner estimates that “By 2020, natural-language generation and artificial intelligence will be a standard feature of 90 percent of modern BI platforms, according to Gartner’s 2017 Magic Quadrant for Business Intelligence and Analytics.

There are many ways that NLG helps markers streamline operations and improve target marketing based on customer interests including:

  • Auto-generating editorial text with human-like accuracy without needing additional human resources, making your marketing team operate more efficiently.
  • Create content variations for unlimited personas for highly personalized digital experiences to influence buying behavior and gain a competitive advantage.
  • Reduce the time spent creating large quantities of content down to mere seconds, delivering economies of scale and faster time to value.


NLG Helps Power Ecommerce

One market where NLG provides immediate value is retail. By combining personalization capabilities, NLG helps marketers better understand the shopping habits and interests of their customers. For example, NLG helps you understand if someone is shopping for themselves or for someone else, which then allows you to generate the correct language in context; i.e., “Perfect for Your Birthday” versus “Perfect for Her.”

Using analytics applications allows retail executives to tap into volumes of big data and then leverage insight about their customers. But what’s important is that executives design a strategy that actually leverages all of the data. With a strategy in place the question becomes, “How can it be used to engage customers more effectively?”

NLG is an AI-driven software solution that extracts data from complex sources to produce naturally worded content. NLG is important for retail executives because it:

  • Creates unlimited content variations for personas for hyper-personalized digital experiences and better customer engagement.
  • Influences buying behavior with more targeted and individualized content for increased sales.
  • Means you have to spend less time on routine tasks and more time perfecting digital experiences that compel customers to action.

For retailers, the beauty of NLG is that it simplifies the process of creating multiple versions of something, such as product descriptions in a clothing catalog, very accurately and easily, even across multiple languages. This makes it easy to create a regular stream of personalized content that can be leveraged across multiple channels. 

Personalizing Content = Happy Customers

One way to make the purchasing process easier for people who like to shop online is to personalize content that is tailored to each customer’s unique interests. Tapping into the power of metadata allows marketers to easily create text using structured data which is important because unique product description text can be created for a variety of products. By creating text in a fraction of a second, marketers save time and actually deliver content that meets the customer’s individual interest. Reducing the amount of irrelevant information that a customer receives goes a long way to enhancing and improving the customer relationship.

A subtle, yet important, feature of NLG is its ability to understand grammatical structures. Merging metadata and content that sounds like how a person actually talks is not easy, but for NLG it is very easy. Fortunately, content creators can edit content for tone, syntax and context. For retail departments that need to create highly repetitive text, like a clothing retailer for a product catalog or a company’s annual report, NLG simplifies the entire process.

How is NLG Used?

I’ve focused on how NLG helps retailers improve their omnichannel marketing efforts through personalization, but it’s important to know that there are many industries that benefit from NLG including brick-and-mortar stores, travel and tourism, and human resources. One industry that derives enormous benefit from NLG is in publishing.

NLG is perfect for the publishing industry that needs to create thousands of news stories for a particular topic. Kelly Liyakasa of AdExchanger asserts that NLG allows publishers to create articles more quickly, cheaply, and potentially with fewer errors than human journalists. “It’s a critical capability for the large-scale news agency, whose content is used by other publications and journalists to develop their own localized editorial.”

NLG Increases Customer Loyalty

Regardless of industry, marketers can use NLG to streamline operations, improve content quality, reduce costs, and create superior digital experiences. Through these benefits, marketers can find another silver lining—they can focus on creating more interesting and exciting content that focuses on how customers are using a company’s products.

By leveraging the power of NLG, marketers can easily deliver fresh, personalized content to customers across multiple channels. This helps create a better customer experience which helps secure customer loyalty.