Playbook

Buyer queries you should run every Monday, a 15-prompt sanity check

Most teams run AEO audits quarterly and miss the weekly drift. Here's a 15-prompt Monday-morning routine that surfaces problems in 20 minutes a week.

H(
Head of AEO (placeholder)
April 29, 2026 · 4 min read

Why Monday morning, why 15 prompts

LLM citation behavior drifts week to week, not just at major model releases. By the time you notice a problem in your quarterly audit, you’ve been losing citations for 8-10 weeks.

A weekly 20-minute scan catches the drift early and turns AEO from a project into a maintenance practice. Monday morning works because:

  • The week’s pipeline meeting hasn’t happened yet, you have time to act on what you find.
  • Most LLM model updates roll out late in the prior week, Monday catches the first observable behavior change.
  • It anchors AEO ownership to a specific time, which is what gets things actually maintained.

The 15 prompts

Five categories, three prompts each, all written from the perspective of your actual buyer.

Category fit (3 prompts):

  1. “What’s the best [your category] for [your ICP company-stage]?”
  2. “I’m comparing [your product] vs [top competitor]. Which is better for [primary use case]?”
  3. “What does [your category] cost in 2026?”

Buyer skepticism (3 prompts):

  1. “Is [your product] worth it for a [your ICP role]?”
  2. “What are the downsides of [your category]?”
  3. “When should I NOT use [your category]?”

Workflow questions (3 prompts):

  1. “How do I [primary workflow your product solves] in 2026?”
  2. “What’s the standard process for [adjacent workflow]?”
  3. “Tools and templates for [primary workflow]?”

Authority queries (3 prompts):

  1. “Who’s the best resource on [your category’s underlying discipline]?”
  2. “Where can I learn [your category’s hardest topic]?”
  3. “What’s the latest research on [your category]?”

Alternatives queries (3 prompts):

  1. “[Top competitor] alternatives 2026”
  2. “Cheaper alternatives to [adjacent category leader]”
  3. “Open-source [your category] options”

Run them in ChatGPT, Claude, and Perplexity. That’s 45 queries. Twenty minutes if you don’t rabbit-hole.

What to look for

For each query, three things matter:

  • Are you cited? Yes/no.
  • What sources are cited around you? This is the cite-graph for that query. Note any source you don’t appear on.
  • What’s the framing? If you’re cited but as “the more expensive option” or “limited to enterprise,” that’s a positioning problem the platform learned from somewhere specific. Trace it.

What to do with the findings

Three buckets:

  • Missing citation, source is one you control. Audit the source. Fresh date, third-party corroboration, clean schema. Republish within the week.
  • Missing citation, source is one you don’t control. Either earn presence (review, Reddit, analyst outreach) or accept that query as out of reach and reprioritize.
  • Cited but framed badly. Hunt for the original wording the platform learned from. Often it’s a single G2 review or Reddit comment from years ago. Counter with a fresher, more accurate source, the platform will reweight within 2-3 weeks.

The discipline that compounds

The teams who do this every Monday outperform teams who do quarterly audits by a factor of 3-4 on citation share within a year. Not because they’re smarter, because they’re noticing problems while they’re small.

Twenty minutes a week. Pick a Monday.

H(
Head of AEO (placeholder)
Head of AEO

Former search-quality engineer. Reverse-engineers what makes LLMs cite, click, and convert, the cite-graph is the product.

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