Wissee AI-based Product Name Entity Recognition helps brands identify and predict viral products and spot early signals of market trends from millions of users’ social media postings.
If you are wondering how to utilize the full power of user-generated content for product innovation and trend forecast, read on.
‘User generated content’ - or UGC, for short - refers to social media postings, blogs, reviews posted by consumers from online. It’s any and all content created and posted by users.
And UGC is powerful.
Nowadays, consumers’ purchasing decisions are strongly influenced by what they see on social media. This UGC impacts how people make decisions and spend money. So it’s no surprise that UGC data contains valuable information about consumer purchasing behavior.
But, because it’s generated by users all over the world, abbreviations, slang, internet jargon, typos, and non-standard syntactic constructions make it hard data to make sense of, let alone, make an investment decision.
Wissee solves that problem so you can make sense of that data effectively and efficiently with powerful NLP and Machine Learning algorithms built as a result of over a decade of research.
Meet Wissee’s Product Named Entity Recognition
It’s a Deep Learning AI model trained on over 100,000+ proprietary carefully human-annotated training data collected from multiple social media platforms.
And it is the only such model on the market that can automatically recognize product names from UGC text.
The Use of Product Name Recognition Model
Wissee AI-based Product Name Entity Recognition helps to identify hot products from millions of users’ social media postings. Understanding consumer trends on products can help brands and e-commerce sellers gain an early understanding of industry trends and win against competitors.