As retail executives generate large amounts of big data from analytics and BI applications, they must have a strategy in place that is designed to leverage all of that data. Once valuable information is culled and packaged, how can it be used to engage customers more effectively? Even more important is how retail executives that require a high degree of personalization capabilities can use data to their advantage. One solution is to tap into the power of natural language generation or NLG.
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.
Panetta explains the importance of NLG. “Visualization has been a major driver of modern business intelligence (BI), but data in this form can be difficult to fully interpret. Natural-language generation (NLG) is able to create a written or spoken content-based narrative of data findings alongside the visualizations to produce a full story about key action items. Currently, BI teams integrate stand-alone NLG engines, but as the technology evolves, that will change. NLG will enable next-generation BI and analytics platforms to automatically find, visualize and narrate important findings. The technology will expand analytics to a broad audience as well as reduce time and cost for regular batch reports.”
NLG makes it easy to create multiple versions of product descriptions very accurately, in multiple languages, very quickly. This simplifies the process of creating a regular stream of personalized content that can be leveraged across multiple channels.
NLG and personalized content
Sharing product descriptions with customers that is personalized to their unique interests helps make the purchasing process much easier. NLG taps into the power of metadata by automatically creating text using structured data which is important because unique product description text can be created for a variety of products. The key point is that you can create text at scale in milliseconds which saves a lot of time and helps deliver content that each customer actually wants.
Another benefit of NLG is that it can understand grammatical structures. NLG merges metadata and content to create grammatically accurate text with wording that sounds just like a person would say. The good news is that a writer on the e-commerce team 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.
Applications for using NLG
- Digital Commerce: NLG is the ideal technology to create thousands of product descriptions for entire product catalogs.
- Brick & Mortar: NLG easily customizes store landing pages with data such as store hours and menus.
- Publishing: NLG creates thousands of news stories allowing publishers to create articles more quickly, at a reduced cost, and potentially with fewer errors than a person might make.
- SEO: NLG helps tag images for SEO purposes, an undeniably manual task. In this way, it abstracts information from pictures, combines that information with product descriptions, and creates new text to drive better search results.
Better personalization leads to customer loyalty
NLG is powerful technology that helps retail teams streamline operations, improve content quality, reduce costs and create superior digital experiences. Securing these benefits means that retailers can spend valuable time creating more compelling stories that focus on how customers are using a company’s products.
Using NLG allows retailers to easily share fresh, personalized content across multiple channels. Businesses that want to create a continual stream of content that is targeted for individual customers should learn more about NLG since it improves the overall customer experience which leads to increased customer loyalty.