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How are Technologies changing the face of Competitive Intelligence?

Within the last 3 years, advances in Artificial intelligence and Deep learning have brought a major breakthrough in Natural language understanding.

How do machines really understand natural language? And why is this so important for competitive intelligence?

During our latest webinar  on “How to harness new technology to improve your competitive monitoring”, our insight expert Shadi explained how technologies are changing the face of Competitive Intelligence.  

Watch the 5min recap video:

HubSpot Video


As explained during the session, here are the key building blocks you should find in Artificial Intelligence platforms that aim to process and analyse information.

The main tasks should include: 

  • Media-to-text option: that converts video, images and audio into text
  • Translation tasks that captures conversations on local media without even knowing the language
  • Summarization: aimed to increase the analysts reading productivity by x100.
  • Named entity recognition: here the objective is to disambiguate meaning by relying on concepts rather than keywords – for example Apple which could be a company versus apple the fruit.
  • Classification, which aims to automatically classify a text into a taxonomy, Organise content by topic and concept, recommend related readings, clusterize information.
  • The Sentiment Analysis aims to extract sentiment of an analyst of a consumer related to a specific product, brand, industry or a topic.
  • The Search Models task which Dramatically removes noise from search tasks with context based search.
  • And finally the Knowledge graph which understands how concepts and entities are connected together around one specific topic.

When plugged together, these building blocks bring a lot of value to information management systems.

In competitive intelligence, it allows companies to achieve true 360 degree monitoring of their business environment by processing by analyzing any content in any language in real time such as: 

  • Who are the key players in your industry ?
  • What are they doing ? Who are they partnering with, are they launching a new product, what are they investing in?
  • Where are they expanding ?

Within the next decade, advances in Deep learning technologies will allow this type of system to predict quite accurately future outcomes by constantly learning from past events.

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