AEO Prompt Architecture: Q0 Principles we Recommend for B2B SaaS Companies If you want to measure and optimize your brand’s visibility in AI platforms, you’ll need to generate a set of sample prompts for your AI visibility tool to track. And the quality of the reports you get from any tool depend on how strategically you’ve built that sample prompt set. And of course, if you want a hand doing this at your company, we’d love to explore how we can help. If you don’t set up your sample prompts strategically, you’ll waste a lot of time and a lot of money to get a lot of noise. Most of the major answer engine optimization tools (and all the best ones today) rely on you creating a sample set of prompts. These tools feed those prompts into AI platforms over and over again, and bring the response data back to you. Any metrics regarding share of voice, mention rankings, sentiment, and citations that these tools give you comes from the responses to the prompts you tell it to input. That means even if you’re using one of the best options on the market today, the reports you get back will only be as useful as the prompts you put in. If you’re feeding your AI visibility tool prompts that don’t strategically map to your desired outcomes (or worse: letting them generate your prompts for you with AI), the numbers you get back won’t help your marketing strategy, either. Every major AEO tool’s plans come with a predetermined prompt cap, and you pay more to add extra prompts to the mix. Those initial prompt limits may seem like plenty at the beginning, but they burn up fast. Plus, some tools will charge you per prompt per platform as well. For example, if you want to track the prompt "What are the top three enterprise sales enablement software platforms? So for example, Scrunch’s starter plan includes 350 prompts. However, every individual prompt is assigned a single platform.