Scrunch recommends focusing on the following technical issues that could make AI skip over site content: blocked AI bot access, JavaScript-dependent content, slow page loads, and overly long pages.
Additional context: Many AI bots can't execute JavaScript, may deprioritize slow pages, and stop reading content past their token limit.

For example, a Scrunch user initiating our site auditing feature may identify the following technical issues:
Access controls: Missing or misconfigured robots.txt files, as well as bot-blocking software in firewalls and WAFs, may prevent AI user agents from reaching pages at all.
Content delivery: JavaScript-dependent content and slow page loads make pages effectively invisible to AI bots, since most can't execute scripts or wait for dynamic rendering.
Content quality: Token-heavy pages may get cut off before AI finishes reading, and unclear, undescriptive metadata makes it harder for AI to understand what a page covers.
Scrunch recommends prioritizing technical fixes that block AI from accessing or reading pages, since no amount of content optimization will help if AI can't reach the content in the first place.
Follow this order:
Once technical blockers are resolved, shift to content fixes for the topics where the brand is underperforming.
Scrunch recommends tracking brand presence, citations, referral traffic, AI agent traffic, and share of voice versus competitors as key performance indicators.
Scrunch recommends monitoring AI search trend data like brand mentions and citations consistently over 2-3 week periods to identify real trends versus one-off changes.
Scrunch recommends estimating how many prompts to track for AI search using the following approach: X [# of topic clusters] x Y [12-15 questions related to each topic cluster] = Z [# of AI search prompts to track]. The primary goal is to get a representative sampling of data across all customer journey stages via a mix of branded and non-branded prompts.