An AI engine optimization audit evaluates model visibility, accuracy, and citations in AI-powered search engines like google and yahoo. It highlights how a model seems throughout ChatGPT, Gemini, Perplexity, and Bing Copilot, and identifies gaps within the details, descriptions, and hyperlinks these programs depend on. In distinction, a standard website positioning audit focuses on web site rankings and technical well being in basic search engines like google and yahoo. 
AI search extracts data straight from content material, public sources, and structured knowledge. This shift adjustments how consumers uncover manufacturers and validate options. Development-focused groups profit from exact, constant model particulars in AI summaries, as these summaries affect early analysis, shortlists, and pipeline creation.
This publish provides groups an entire workflow for working an AI engine optimization audit, precedence fixes, a sensible guidelines, and the HubSpot instruments that assist the method. Every part affords clear steps for testing visibility throughout AI engines, measuring accuracy, updating content material, and publishing structured, AI-friendly pages at scale.
Desk of Contents
What’s an AI engine optimization audit?
An AI engine optimization audit is a structured overview that measures how precisely AI search engines like google and yahoo characterize a model. It evaluates visibility, accuracy, and citations throughout programs like ChatGPT, Gemini, Perplexity, and Bing Copilot. The objective is to verify that AI-generated summaries precisely replicate the model’s details, product particulars, and sources.
An AI engine optimization audit differs from a standard website positioning audit. A standard website positioning audit focuses on rankings, crawlability, and technical well being. An AEO audit focuses on entity correctness, model mentions, quotation frequency, and the precision of AI-generated summaries. An AI engine optimization audit identifies outdated details, lacking model mentions, and incorrect citations in AI summaries. These points usually stem from unstructured pages, unclear entities, and inconsistent context.
AI engines pull data from standalone chunks, structured knowledge, and patterns throughout the online. They interpret content material extra precisely when pages use clear headings, outlined entities, semantic triples, and constant formatting.
HubSpot Search Grader gives a free option to assess model visibility in AI search engines like google and yahoo and set up a quick baseline. It enhances foundational work reminiscent of working an internet site audit, bettering the basics within the technical website positioning information, including markup from the structured knowledge walkthrough, and reviewing efficiency in your website positioning report.
How AEO, GEO, and website positioning Work Collectively
AEO, GEO, and website positioning every strengthen how consumers uncover and perceive a model.
- AEO (reply engine optimization) focuses on entity readability, correct citations, and the way AI engines summarize a model.
- GEO (generative engine optimization) focuses on efficiency in generative experiences throughout channels, together with conversational solutions and synthesized outcomes.
- website positioning (search engine marketing) focuses on rankings, crawlability, and technical efficiency in conventional search engines like google and yahoo.
Groups acquire stronger visibility when these workflows run collectively. AEO highlights entity gaps. GEO highlights the depth and usefulness of content material in generative environments. website positioning highlights technical and rating indicators. Including all three dimensions to your website positioning report helps groups monitor visibility adjustments throughout search experiences.
|
Audit Kind |
What the Audit Covers |
Why It’s Necessary |
|
AEO (Reply Engine Optimization) |
Entity definitions, model mentions, citations, factual accuracy, and the way AI programs interpret and summarize the model |
Ensures AI engines clearly perceive who a model is, what it affords, and when to reference the model in direct solutions and summaries |
|
GEO (Generative Engine Optimization) |
Efficiency in generative experiences, together with conversational responses, synthesized outcomes, multi-source solutions, and content material usefulness |
Improves visibility and affect in AI-driven discovery moments the place customers obtain generated solutions as an alternative of hyperlinks |
|
website positioning (Search Engine Optimization) |
Rankings, crawlability, indexing, website structure, technical well being, backlinks, and key phrase efficiency |
Maintains robust visibility in conventional search outcomes and ensures content material will be found, listed, and ranked successfully |
Why run an AI engine optimization audit now?
AI search now performs a big position in how consumers analysis classes, evaluate distributors, and validate options. An AI engine optimization audit provides groups a transparent understanding of how AI engines summarize their model right this moment and the place enhancements may have the best affect.
AI search is reshaping top-of-funnel discovery.
Site visitors is tougher to earn as AI engines turn into the primary cease for contextual solutions. Giant language fashions (LLMs) generate tailor-made responses that present customers with direct steering, lowering the necessity to work together with conventional SERP hyperlinks. Sturdy AEO foundations assist AI engines spotlight correct details and up to date messaging.
AI engines affect B2B shopping for committees.
AI summaries usually seem earlier than consumers attain an internet site. These early summaries form class expectations, body key capabilities, and have an effect on which distributors seem related. AEO enhancements assist extra constant visibility in these moments.
Incorrect or lacking model details unfold rapidly.
AI engines take in outdated data from outdated pages, legacy listings, and exterior sources. These inaccuracies can unfold throughout a number of programs. Publishing constant, structured updates helps information AI engines towards present details.
Pipeline and income reporting wants correct AI mentions.
Pipeline creation depends upon how clearly consumers perceive a model’s choices. Up to date AI summaries assist extra constant messaging throughout the funnel. Sensible CRM connects content material enhancements to pipeline and income outcomes, which hyperlinks AEO efforts to measurable enterprise affect.
AI search optimization compounds over time.
Clear entity indicators assist AI engines categorize a model extra precisely. Early enhancements create a basis that strengthens recognition and quotation patterns throughout future updates.
Run an AEO Audit (Step-by-Step)
An AEO audit evaluates how AI engines describe a model, highlights errors, and guides updates that strengthen visibility. Every step works as a standalone job that groups can full in sequence or combine into present content material workflows.

Step 1: Outline the entities, matters, and branded phrases you need AI engines to acknowledge
Listing the core details AI engines ought to reference when summarizing your model. Embody firm title, product names, key options, goal personas, and class phrases. Add high-intent matters that align along with your positioning.
Step 2: Check your model in prime AI engines
Run focused prompts throughout ChatGPT, Gemini, Perplexity, and Bing Copilot. Embody non-public or trade fashions if related to your viewers. Check branded queries, class queries, and solution-driven prompts. Groups evaluating Microsoft’s ecosystem can even reference our steering on whether or not entrepreneurs ought to optimize for Bing.

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Professional tip: Use HubSpot’s free AEO Grader to see how your web site is showing in AI search engines like google and yahoo.
Step 3: Seize and categorize all AI outputs
File screenshots and textual content from every engine. Categorize outputs as appropriate, outdated, incomplete, inaccurate, or lacking. Add a column for confidence markers reminiscent of citations, hyperlinks, attributed sources, and contextual accuracy.
Professional tip: Add a confidence-marker column to spotlight which engines pull from reliable sources.
Step 4: Rating visibility, accuracy, and quotation completeness
Create a easy scoring mannequin for visibility, accuracy, depth, and citations. Visibility measures whether or not the model seems. Accuracy measures factual correctness. Depth signifies whether or not product-level particulars seem. Citations measure whether or not AI engines hyperlink to brand-owned sources.
Step 5: Establish entity gaps and semantic errors
Test for incorrect founders, dates, product descriptions, or trade classes. Flag lacking options, outdated positioning, and expired pricing. This step surfaces unclear or inconsistent entity indicators.
What I like: Entity-gap opinions usually reveal inconsistencies throughout About pages, product pages, and listings. Updating these hubs concurrently strengthens AEO, website positioning, and GEO indicators.
Step 6: Overview on-site content material for construction and AEO readability
Consider whether or not the content material makes use of extractable chunks, clear H2/H3 formatting, lists, and specific semantic triples. Overview inside linking and entity particulars throughout key pages. Strengthen structured knowledge utilizing the practices in HubSpot’s structured knowledge information. HubSpot Content material Hub helps structured, entity-friendly publishing at scale.
Step 7: Replace or create supporting content material with an AI-friendly construction
Draft updates utilizing AI instruments, then manually validate every reality. Breeze AI Suite accelerates content material briefs, QA pairs, and optimization duties. Content material Hub and Advertising Hub assist groups mix website positioning and AEO updates with structured enhancing instruments and efficiency insights.
Greatest for: Groups managing giant content material libraries profit most from drafting first-pass updates in Breeze and refining with human overview.
Step 8: Re-test utilizing HubSpot AI search grader
Run one other full take a look at utilizing HubSpot Search Grader after publishing updates. File adjustments, evaluate outputs, and refine your entity listing because the model evolves. An AI engine optimization audit needs to be repeated quarterly or after main content material adjustments.
Operationalize Your AEO Audit in HubSpot
HubSpot’s ecosystem helps your entire AEO workflow:
- AI Search Grader establishes baselines for visibility, accuracy, and citations.
- Content material Hub publishes structured, entity-friendly updates.
- Breeze AI Suite hurries up content material briefs, revisions, and QA duties.
- Advertising Hub website positioning instruments spotlight technical points and matter gaps that assist AEO and website positioning work.
- Sensible CRM connects content material updates to engagement, lead high quality, and income insights.
Greatest for: Groups that need a repeatable AEO workflow tied on to content material operations and reporting.
Precedence Fixes After Your Reply Engine Optimization Audit
Excessive-impact fixes deal with correcting model details, strengthening entity readability, publishing structured content material, increasing high-intent protection, updating public listings, and including authoritative citations.
Repair 1: Right model details throughout owned content material.
Replace outdated product descriptions, function lists, and claims. Add semantic triples that clearly set up relationships among the many model, its merchandise, and its classes.
Professional tip: Add semantic triples to product pages, About pages, and glossary entries to strengthen entity readability.
Repair 2: Strengthen entity pages and model hubs.
Make clear who the model serves, what classes it participates in, and which merchandise it affords. Strengthen About pages, glossary entries, and product pages so AI engines have dependable sources for the basics.
Repair 3: Add structured knowledge and higher content material structure.
Publish schema markup for entities, merchandise, and organizational particulars. Strengthen the data structure so AI engines can interpret the location construction rapidly. HubSpot’s structured knowledge information outlines markup patterns groups can operationalize throughout the location.
What I like: Structured knowledge usually turns into one of many quickest methods to appropriate misaligned AI-generated details.
Repair 4: Create supporting content material for high-intent matters.
Develop content material to align with purchaser wants in AI engines. Add explainers, templates, guides, and up to date class pages. Advertising Hub’s website positioning suggestions spotlight matter gaps and content material alternatives.
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Greatest for: Groups constructing matter authority throughout hybrid AEO and website positioning workflows.
Repair 5: Replace digital footprints on high-authority platforms.
Refresh model data throughout LinkedIn, G2, GitHub, YouTube, and different profiles AI engines ceaselessly reference. Create a Wikipedia web page provided that the model meets notability requirements and might observe editorial tips.
Repair 6: Add earned media and authoritative citations.
Strengthen presence throughout respected shops, together with press shops, podcasts, and interviews. AI engines favor manufacturers with constant exterior validation.
Professional tip: Earned media improves quotation patterns and reduces outdated references throughout AI engines.
AI Search Optimization Audit Guidelines
Use this AEO audit guidelines as a repeatable month-to-month or quarterly workflow.
- Establish core entities to guage.
- Check visibility in prime AI engines.
- Seize and categorize outputs.
- Rating visibility, accuracy, and citations.
- Repair entity and semantic errors.
- Replace content material construction and metadata.
- Add structured knowledge and entity markup.
- Re-test with HubSpot AI Search Grader.
- Repeat each quarter.
Ceaselessly Requested Questions About AI Engine Optimization Audits
Groups encounter a number of widespread questions once they start evaluating how AI engines summarize their model.
Do I would like developer assets for an AI engine optimization audit?
Developer assist is just not required for the analysis itself. Developer assets may help when including structured knowledge, updating schema markup, or adjusting website structure that helps clearer entity indicators.
How usually ought to I rerun the audit?
Run the audit quarterly or after main content material, product, or positioning updates. This rhythm retains AI-generated summaries aligned along with your present model particulars.
Ought to I create a Wikipedia web page for my model?
Create a Wikipedia web page provided that the model meets notability standards and might observe editorial requirements. Pages that don’t meet these necessities could also be eliminated, creating confusion for AI engines.
Will llms.txt affect conventional search engine optimisation?
llms.txt manages entry for AI crawlers and doesn’t affect Google’s rating algorithms. It operates independently of conventional website positioning indicators.
What’s one of the best ways to get cited by AI engines quicker?
Publish structured, entity-rich content material with clear semantic relationships. Strengthen exterior citations from respected shops. Use HubSpot AI Search Grader to establish gaps and plan updates.
Getting Began
An AI engine optimization audit highlights how AI search engines like google and yahoo describe a model, identifies accuracy gaps, and guides updates to enhance visibility throughout the client journey. The shift towards AI-generated summaries makes this work an vital a part of discovery, income creation, and development planning. Get began by defining core entities, testing visibility throughout main AI engines, and working an preliminary baseline with HubSpot AI Search Grader.
I’ve seen important enhancements from groups that undertake a constant audit cycle, replace outdated details, and publish structured content material — small enhancements compound. AI engines replace their summaries rapidly when manufacturers publish clear, dependable data in structured codecs.
