IBM partnered with a telecommunications company to leverage generative AI, transforming it from a documentation tool into a valuable marketing knowledge generator. By standardizing customer service call transcripts and converting them into a common format, the company was able to improve consistency in documentation. This standardized data was then integrated into the CRM system, allowing marketing and product teams to analyze customer opinions, competitor mentions, and product complaints. This approach influenced marketing strategies and product development within the company.
Another case study highlighted the enterprise resource planning startup Rillet, which used generative AI to create marketing case studies from recordings of customer conversations. By inputting question-and-answer session recordings into a generative AI tool, the company was able to generate case studies that were around 70% complete. This utilization of generative AI helped streamline the process of creating marketing materials based on customer interactions.
Manish Goyal, IBM’s senior partner for global artificial intelligence and analytics emphasized the importance of educating employees on the use of AI tools within the organization. Whether using AI Copilots for productivity or complex tools for marketing campaigns, team members need to understand how to utilize the technology safely. Goyal also highlighted the benefits of open source AI models, such as TensorFlow, PyTorch, Scikit-learn, and OpenCV, as they provide transparency on the data the models are trained on.
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https://www.emarketer.com/content/ibm-rillet-generative-ai-productivity-tool-marketing-machine
