(8th-January-2020)
One of the key aspects of NLG resides in its ability to understand grammatical structures. NLG can merge content and metadata that produces grammatically correct text with wording that is just like an average person would use. A self-service interface allows editors to enhance tonality, control vocabulary, generate text arbitrarily using rules, and view content quality metrics—in any language. For organizations that have to generate highly repetitive text, like a clothing retailer for a product catalog or a company’s annual report, NLG makes the process much simpler.
Fig: Explanation about NLG Working
NLG Features
Auto-generate editorial texts without the need for additional human resources, helping marketing teams operate more efficiently.
Create content variations for unlimited personas for highly personalized digital experiences.
Reduce the time spent creating large quantities of content down to mere seconds, delivering economies of scale and faster time to value.
Examples of NLG in Markeing
1) Publishing: NLG creates thousands of news stories allowing publishers to create articles more quickly, at a reduced cost, and potentially with fewer errors than human journalists.
2) Finance & Insurance: News reports on stock market results can easily be generated by AI-driven NLG software. This can also be used in the crypto currency market.
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