When querying ChatGPT for trends or tactics, failing to specify a time period (e.g., 'in the last 60 days') will result in outdated information. The model defaults to data that is, on average, at least a year old, especially for fast-moving fields like marketing.
Related Insights
A significant portion (30-50%) of statistics, news, and niche details from ChatGPT are inferred and not factually accurate. Users must be aware that even official-sounding stats can be completely fabricated, risking credibility in professional work like presentations.
To signal recency to Large Language Models (LLMs), marketers must include specific time periods (e.g., year, quarter, month, or 'Updated [Date]') directly in content titles. This simple change makes content over 50% more likely to appear in AI-generated results on platforms like ChatGPT, which are rapidly replacing traditional search.
Instead of only giving instructions, ask ChatGPT to first ask you questions about your goal. This leverages the AI's knowledge of what information it needs to produce the best possible, most tailored output for your specific request.
The dominance of AI tools like ChatGPT, which favor new and recently updated information, is rendering traditional 'set it and forget it' evergreen content obsolete. AI citations are, on average, nearly a year newer than traditional search results, signaling a fundamental shift in content strategy that marketers must adapt to.
Getting a useful result from AI is a dialogue, not a single command. An initial prompt often yields an unusable output. Success requires analyzing the failure and providing a more specific, refined prompt, much like giving an employee clearer instructions to get the desired outcome.
Simply using one-sentence AI queries is insufficient. The marketers who will excel are those who master 'prompt engineering'—the ability to provide AI tools with detailed context, examples, and specific instructions to generate high-quality, nuanced output.
AEO is not about getting into an LLM's training data, which is slow and difficult. Instead, it focuses on Retrieval-Augmented Generation (RAG)—the process where the LLM performs a live search for current information. This makes AEO a real-time, controllable marketing channel.
To combat AI hallucinations and fabricated statistics, users must explicitly instruct the model in their prompt. The key is to request 'verified answers that are 100% not inferred and provide exact source,' as generative AI models infer information by default.
AI's preference for recency extends beyond the content to the webpage itself. Pages that haven't been updated in over a year are more than twice as unlikely to be cited by AI models. This means marketers must continuously update the pages, not just the content on them, to maintain visibility in AI search.
AI can provide outdated information. Instead of stating its output as fact ("You are an ESOP"), frame it as a question ("My research suggested you were an ESOP, is that still the case?"). This validates information and turns a potential error into a natural, informed conversation starter.
