Chain of Thought
Prompting technique and model capability where the model explicitly articulates its thinking process in intermediate steps before arriving at the final answer.
Essential for reliable AI analyses in marketing. Enables traceability of calculations and recommendations for stakeholders.
Explanation
Chain of thought dramatically improves accuracy on complex tasks. Originally a prompting technique ("Let's think step by step"), now natively integrated in reasoning models. Advantages: Better results on math, logic, multi-step problems. Debugging possible through visible intermediate steps. Can be enhanced with few-shot examples.
Marketing Relevance
Essential for reliable AI analyses in marketing. Enables traceability of calculations and recommendations for stakeholders.
Example
Prompt: "Calculate the ROAS of this campaign. Think step by step." → Model shows: Total costs → Attributed revenue → Division → Interpretation.
Common Pitfalls
Significantly increases token consumption. Not all models benefit equally. Can lead to overengineering on simple questions.
Origin & History
Chain of Thought is an established concept in the field of Artificial Intelligence. The concept has evolved alongside the growing importance of AI and data-driven methods.