Natural Language Processing and Natural Language Understanding

Goals

To provide insights regarding Natural Language Processing (NLP) and Natural Language Understanding (NLU), including data that indicate growth, particularly in its e-commerce use. The data insights should include:
  • A summary of how NLU and NLP are used for commerce or in general.
  • Any available statistics around NLU and NLP usage and chatbots.

Early Findings

  • There is a wealth of information around this topic.

Natural Language Processing (NLP) and Natural Language Understanding (NLU)

  • The Natural Language Processing (NLP) market was valued at $10.76 billion in 2020. The market is expected to grow to $48.46 billion by 2026.
  • NLP is expected to see increased adoption, particularly by large organizations, due to their increased adoption of deep learning and machine learning (ML) technologies. Health centers and call centers are some other areas driving the growth of NLP.
  • NLP has been employed successfully for commercial and non-commercial applications, including speech recognition, virtual assistants, customer service chatbots, and sentiment analysis.
  • Natural Language Understanding (NLU) is seeing increased applications in powering chatbots, voicebots, and voice assistants. Currently, 67% of companies are working on conversational assistants.
  • About 51% indicated that they would spend more on conversational AI than mobile apps in the future.
  • Also, "within the next few years, mobile chatbots are anticipated to revolutionize the marketing and commerce sectors."

How They Work

  • NLU is a sub-component of NLP, which is part of the broader spectrum of artificial intelligence (AI).
  • By utilizing fundamental meaning and ML, NLP engines can identify entities and isolate values to understand user intent better.
  • It analyzes statements and extracts vital entities such as location, date, time, and other variables to make suggestions.

NLP in E-Commerce

  • NLP is emerging as a solution that bridges the gap between the human thought process and autonomous technology. It provides unique applications in the e-commerce sector by analyzing vast amounts of everyday data and analyzing them to generate the best search results.
  • Many e-commerce platforms rely on NLP to extract attributes and improve their product search, which helps consumers view relevant products when they shop online.
  • "Advanced NLP-based sorting systems enhance the online shopping experience by understanding the behavior of target customers."
  • The top NLP applications in e-commerce include product search, customized product recommendation, product success prediction, auto-generated product description, and voice search.

Summary

  • NLP and NLU are seeing growth across several industries commerce, marketing, healthcare, and customer service.
  • Product search is among the most significant uses of NLP in e-commerce.
  • NLP is applicable across commercial and non-commercial sectors.

Research proposal:

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