Generative AI is the latest buzzword in the digital marketing world. As consultants, we've been exploring the potential of one large language model-based chatbot, ChatGPT, to harness the power of AI and help us work more efficiently. We recently put ChatGPT to the test and asked it 42 questions about Google Analytics 4, but it only answered 12 correctly - a success rate of just 29%.
It's important to remember that AI cannot replace the expertise of an analyst. The key to a successful generative AI project is to have a clear expectation for the output so any AI-generated materials can be edited and shaped. It is an assistant, not an expert. We can use it to automate manual tasks, such as quality assurance checks, and save time. For example, it can analyze and optimize a retailer’s shopping baskets or validate a piece of code - tasks which would normally take two hours can now be achieved in just 30 minutes.
Whilst generative AI has the potential to revolutionize many aspects of our digital workflows, it is important to approach its applications with a balanced perspective. There are limitations in accuracy, particularly concerning recent updates and nuanced details. However, as the technology matures, the potential will grow for AI to be used as a tool to augment our capabilities and drive efficiencies in our everyday work.
Originally reported by Martech: https://martech.org/the-pitfalls-and-practical-realities-of-using-generative-ai-in-your-analytics-workflow/
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