2 min read
When a shopper lands on your e-commerce site, she will either browse around or search for specific product info. What if you have a virtual assistant who can chat with her and guide her to exactly what she is looking for, just like in a physical store? This seamless, personalized customer experience is made possible through natural language processing (NLP).
NLP is a field of artificial intelligence (AI) that trains machines to understand human language, interpret and converse with it. It takes into account the form of input (speech or voice). By leveraging deep learning algorithms, today’s NLP models are focused on "next sentence prediction", which is a set of candidate sentences being ranked given an unfinished conversation.
Initially, this was done through simple models based on statistical information. Given an input, they would generate the same result. However, using deep learning helps today’s models produce results with considerable accuracy as they are more complicated to extract information from the data. This has opened doors to a whole new host of applications.
Robots in customer service, equipped with NLP technology, are able to understand conversations in limited domains and direct customers to relevant answers. Sentiment analysis also helps them analyze conversations and gauge satisfaction levels.
NLP also helps marketers understand customers' thoughts and intentions by analyzing their conversations and the webpages they viewed.
For instance, if a visitor is planning a shopping trip in Paris, NLP techniques can analyze the keywords and topics from the webpages he browses, and segment the user into a specific category like “France shopper” with interest keywords like “luxury goods”. Using this knowledge, you can have your web content personalized to his interests, increasing the likelihood of conversion and purchase. The fact that this can be done at scale quickly helps marketers devise marketing strategies in real time.
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