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  • How Brands and Agencies Are Experimenting With ChatGPT From Copywriting to Chatbots | Patrick Kulp - Adweek
  • ChatGPT might change advertising — but it won’t revolutionize it | Chris Kelly - Marketing Dive ... Even though its unlikely to upend the ad world any time soon, the buzzy conversational AI model could prove useful for savvy marketers
  • How Brands Can Use ChatGPT And Other Generative AI For Content Marketing | Jia Wertz - Forbes
  • Marketers move beyond the basics of ChatGPT with new tools | Marty Swant - DIGIDAY

NLP -Based Brand Awareness and Market Research

It’s difficult to develop actionable business strategies when you don’t know how customers feel about your brand. By using sentiment analysis and getting the most frequent context when your brand receives positive and negative comments, you can increase your strengths and reduce weaknesses based on viable market research. NLP-based software analyzes social media content, including customer reviews/comments, and converts them into insightful data. Natural Language Processing (NLP) Use Cases For Business Optimization | Ilia Iorin - MobiDev

How Does This Algorithm Work?

1. Analyze an entire list of comments and classify them using a sentiment analysis model.
2. Get the most frequent words and phrases from both positive and negative comments.
3. Perform market research based on the data collected.

Based on this algorithm, it is possible to assign a value to the output information. This value might be considered as a positive, negative, or neutral emotion. Marketers can use this data to make more informed decisions in their marketing strategies and campaigns.

NLP-Powered Competitive Analysis

Most founders will conduct competitor analysis and research when starting a business. This task enables them to better understand their market, competitors, customers, and other important details about their industry. There are dozens of tools available to help entrepreneurs monitor their competitors. NLP-powered engines like Zirra simplify the process for automatically building a competitive landscape. When Zirra analyzes something, it gathers a list of companies and ranks them from zero to one. This rank shows how closely these companies are related to each other using a multimodal semantic field. The algorithms solutions like Zirra create the list of companies by scanning the Internet for articles and putting the data into an NLP module that closes out semantic relationships between companies. Natural Language Processing (NLP) Use Cases For Business Optimization | Ilia Iorin - MobiDev