{"id":1451,"date":"2026-07-20T06:56:58","date_gmt":"2026-07-20T06:56:58","guid":{"rendered":"https:\/\/maxaeo.ai\/blog\/30-day-aeo-checklist\/"},"modified":"2026-07-20T06:56:58","modified_gmt":"2026-07-20T06:56:58","slug":"30-day-aeo-checklist","status":"publish","type":"post","link":"https:\/\/maxaeo.ai\/blog\/30-day-aeo-checklist\/","title":{"rendered":"AEO Checklist: A 30-Day Starter Plan for AI Search Visibility"},"content":{"rendered":"

An AEO checklist<\/strong> is a short, repeatable sequence of moves that gets your brand mentioned, ranked, and cited inside AI answers from tools like ChatGPT, Perplexity, Gemini, and Google AI Overviews. This one is built for your first 30 days<\/strong> \u2014 not for running a mature program at scale. If you have never measured how AI describes your company, this 30-day AEO checklist gives you the exact order of operations: baseline audit first, seed prompts second, quick wins third.<\/strong> No guesswork, no 200-item spreadsheet.<\/p>\n

Most guides hand you a flat list of "best practices" and leave you to sequence it. For a beginner the hard part is not knowing what<\/em> matters \u2014 it is knowing what to do on Monday<\/em>. This plan fixes the sequence, and every step ends in a number you can defend.<\/p>\n

\"AEO<\/figure>\n

What is an AEO checklist?<\/h2>\n

An AEO checklist is a defined set of steps that make your content easy for answer engines to select, summarize, and cite. It differs from a classic SEO checklist because the target is not a blue link on a results page \u2014 it is a mention inside an AI-generated answer<\/strong>, often with no click at all.<\/p>\n

The discipline sits under answer engine optimization<\/strong>: structuring pages so large language models quote your facts when a buyer asks a question. A starter AEO checklist has three jobs \u2014 measure<\/strong> where you stand, fix<\/strong> the highest-use gaps, and prove<\/strong> the change with a re-test. Every move in the next 30 days maps to one of those three.<\/p>\n

Why 30 days is the right first horizon<\/h2>\n

Thirty days works because AI answers refresh far faster than organic rankings. Where a new backlink can take months to move a position in classic search, retrieval-based assistants like Perplexity and ChatGPT search re-read the live web and can update their responses within days to weeks of a re-crawl.<\/p>\n

That speed cuts both ways. You can see movement inside a month \u2014 but only if you measured a baseline first.<\/strong> Without a Day 0 snapshot, any "improvement" is a story, not a result, and marketers defending a budget cannot ship stories.<\/p>\n

This is a starter<\/strong> plan, deliberately narrow. Once these 30 days are done, the operating model behind a mature AEO program<\/a> covers ownership, cadence, and scale. For now, keep scope tight.<\/p>\n

Week 1 \u2014 Run a baseline AI visibility audit<\/h2>\n

Start by measuring, not fixing.<\/strong> Your Week 1 job is one number you did not have before: your mention rate<\/strong> \u2014 the share of buyer questions where an AI answer names your brand. Everything else this month is judged against it.<\/p>\n

Open each assistant in a private\/incognito window to strip out personalization, then run your prompt set (built in the next section) across ChatGPT, Perplexity, Gemini, and Google AI Overviews. Run each prompt twice and log five data points every time.<\/p>\n

Use this scorecard as your Day 0 template:<\/p>\n\n\n\n\n\n\n\n\n\n
Metric<\/th>\nWhat it measures<\/th>\nHow to log it<\/th>\n<\/tr>\n<\/thead>\n
Mention rate<\/strong><\/td>\n% of prompts where your brand appears<\/td>\nMentions \u00f7 total prompts<\/td>\n<\/tr>\n
Position<\/strong><\/td>\nWhere you land in the answer<\/td>\nFirst \/ middle \/ last<\/td>\n<\/tr>\n
Citation rate<\/strong><\/td>\n% of answers that link your domain<\/td>\nNote when the source is your site<\/td>\n<\/tr>\n
Sentiment<\/strong><\/td>\nHow the AI describes you<\/td>\nPositive \/ neutral \/ negative<\/td>\n<\/tr>\n
Competitor set<\/strong><\/td>\nWho appears instead of you<\/td>\nList rival names per prompt<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Log it in a plain spreadsheet. The goal is a repeatable snapshot you can re-run on Day 30 \u2014 not a dashboard yet.<\/p>\n

\"Baseline<\/figure>\n

How to build your seed prompt set<\/h2>\n

Your baseline is only as honest as your prompts. The goal is to mirror how buyers actually ask \u2014 not how you describe your own product.<\/strong> For a first audit, 15\u201325 prompts<\/strong> is the sweet spot: enough to reveal patterns, few enough to run by hand in an afternoon.<\/p>\n

Weight the set across four intent bands instead of piling on brand-name queries (which flatter you and teach you nothing):<\/p>\n\n\n\n\n\n\n\n\n
Prompt type<\/th>\nShare of set<\/th>\nExample<\/th>\n<\/tr>\n<\/thead>\n
Category discovery<\/strong><\/td>\n~40%<\/td>\n"best [category] tools for [use case]"<\/td>\n<\/tr>\n
Use-case \/ problem<\/strong><\/td>\n~30%<\/td>\n"how do I [job your product does]"<\/td>\n<\/tr>\n
Comparison<\/strong><\/td>\n~20%<\/td>\n"[competitor] alternatives" or "X vs Y"<\/td>\n<\/tr>\n
Brand \/ direct<\/strong><\/td>\n~10%<\/td>\n"what is [your brand] and who is it for"<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The 40\/30\/20\/10 split<\/strong> keeps you honest: most AI-driven demand starts with an unbranded question, so most of your prompts should too. For a rigorous view of set size and coverage, see how many AI search prompts you should track<\/a>. Lock this set as Version 1<\/strong> \u2014 you will re-run the exact same prompts on Day 30, so freezing the wording matters.<\/p>\n

Week 2 \u2014 Fix your entity core<\/h2>\n

AI cannot recommend a brand it cannot cleanly identify.<\/strong> Week 2 makes your company legible to a model: a crisp identity, consistent facts, and machine-readable markup. For most beginners this is the highest-use week because it fixes root causes, not symptoms.<\/p>\n

Work through these in order:<\/p>\n

    \n
  1. Rewrite your About page<\/strong> so the first sentence states plainly what the company is, who it serves, and the category it competes in. Assistants lift this framing almost verbatim.<\/li>\n
  2. Align your brand facts<\/strong> \u2014 name, founding, category, key claims \u2014 so they match across your site, LinkedIn, Crunchbase, and review platforms like G2. Contradictions make models hedge.<\/li>\n
  3. Add Organization and Article schema<\/strong> that reflects only what is visible on the page. Google is explicit that structured data must match on-page content in its structured data guidelines<\/a>.<\/li>\n
  4. Confirm AI crawlers can reach you<\/strong> \u2014 check that robots.txt<\/code> isn't blocking assistant user-agents (GPTBot, PerplexityBot, Google-Extended), and that key pages render without heavy client-side JavaScript.<\/li>\n<\/ol>\n

    Do these four and you remove the most common reason a capable product stays invisible: the model isn't sure who you are.<\/strong><\/p>\n

    Week 3 \u2014 Content quick wins that earn citations<\/h2>\n

    Answer-first formatting is the fastest content lever you have.<\/strong> In Week 3, restructure your highest-intent pages so the answer a buyer wants sits at the very top \u2014 before context, before story. Assistants extract self-contained passages; give them clean ones to lift.<\/p>\n

    Three moves, in priority order:<\/p>\n