Preeti
IBM helped a telecom company use generative AI to standardize customer service documentation, turning it into marketing insights. This allowed marketing and product teams to analyze customer sentiments, competitor mentions, and product complaints to influence strategies and new product development.
Similarly, startup Rillet used generative AI to create marketing case studies from recordings of client conversations. By inputting these recordings into an AI tool, they were able to generate case studies that were 70% complete.
It is important for employees to be aware of the data they are sharing with generative AI tools, whether for productivity or marketing purposes. IBM emphasizes the importance of understanding how the technology is used and ensuring its safe use. They recommend using open-source AI models like TensorFlow, PyTorch, Scikit-learn, and OpenCV, which provide transparency through “nutrition labels” showing the data the models are trained on.
Overall, the use of generative AI in standardizing documentation and creating marketing materials has proven to be effective for companies like the telecom company and Rillet. It is crucial for employees to be informed about the technology they are using and to prioritize safety and transparency in their AI tools.
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Source link: https://www.emarketer.com/content/ibm-rillet-generative-ai-productivity-tool-marketing-machine
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