Question-first tracking
Model real AI search behavior with full questions instead of keyword fragments.
Products / LemonX AEO / Query Lab
Start Here Question testing systemQuery Lab for AEO Testing inside WordPress.
Query Lab turns user questions into repeatable AI search tests. Instead of tracking only short keywords, LemonX AEO stores question prompts, tags, intent, priority, active state, per-engine results and history so teams can understand how AI answer engines respond over time.
Query Lab visualized
Purpose-built SVG scene for this module.
Version OKPurpose-built SVG scene for this module.
Key features
LemonX AEO v1.0.0Query Lab turns AEO signals into repeatable actions.
Every block below is based on a practical WordPress use case: review the signal, understand the evidence, improve the page, and monitor the next change.
Intent grouping
Separate brand, comparison, educational, local, buyer and troubleshooting questions.
Priority queues
Keep high-value questions near the front of scheduled and manual scans.
Per-engine history
Compare how ChatGPT, Perplexity, Gemini, Copilot and other engines answer the same question.
Change alerts
Flag meaningful changes when a response begins citing you, drops you, or starts citing a competitor.
Citation handoff
Send positive results to AI Citations and missing results to optimization workflows.
Designed around the real WordPress admin workflow for Query Lab.
WordPress scenario
Built for actual site operations, not just a dashboard mockup.
A content team creates a question set for “best WordPress AEO plugin,” “how to create llms.txt,” and “AI citation tracking tool.” The editor tags them as commercial, comparison and educational, runs a scan, and sends missed opportunities to the Content Optimizer.
Why it matters: AEO work becomes useful only when teams can turn answer visibility, content gaps, technical signals and integrations into WordPress actions.
- Collect questions from sales, support, search queries and competitor pages
- Tag questions by intent and business value
- Enable only the engines that matter for the target audience
- Run a baseline scan
- Review good, warn, bad and fail outcomes
Plugin data model
Page content is grounded in the actual AEO plugin structure.
Prompt text, intent, tag group, priority, active state, engine history, latest verdict, last run, change alerts, citation link.
The page is written to match how a WordPress user would see and use the feature: inside the LemonX AEO admin menu, connected with related modules, and reported through the same AEO operating system.
| Capability | Operational value | Area |
|---|---|---|
| Question-first tracking | Model real AI search behavior with full questions instead of keyword fragments. | Start Here |
| Intent grouping | Separate brand, comparison, educational, local, buyer and troubleshooting questions. | Start Here |
| Priority queues | Keep high-value questions near the front of scheduled and manual scans. | Start Here |
| Per-engine history | Compare how ChatGPT, Perplexity, Gemini, Copilot and other engines answer the same question. | Start Here |
Recommended workflow
Use a consistent operating process.
The best AEO results come from a loop: define the opportunity, verify the signal, improve the page, submit or expose the URL, then measure change again.
01
Collect questions from sales, support, search queries and competitor pagesThis step keeps the workflow repeatable inside WordPress and connected to LemonX AEO reporting.02
Tag questions by intent and business valueThis step keeps the workflow repeatable inside WordPress and connected to LemonX AEO reporting.03
Enable only the engines that matter for the target audienceThis step keeps the workflow repeatable inside WordPress and connected to LemonX AEO reporting.04
Run a baseline scanThis step keeps the workflow repeatable inside WordPress and connected to LemonX AEO reporting.05
Review good, warn, bad and fail outcomesThis step keeps the workflow repeatable inside WordPress and connected to LemonX AEO reporting.06
Create content tasks from missed questionsThis step keeps the workflow repeatable inside WordPress and connected to LemonX AEO reporting.Use the page as a source asset: clear definitions, strong schema, internal links and current facts.
SEO and AEO best practices
Make the page easy to crawl, understand, cite and recommend.
For Google SEO, the page needs a clear title, focused H1, helpful headings, internal links, indexable content and structured data. For AEO, it also needs direct answers, entity consistency, source-worthy explanations, FAQs and a relationship with other trusted pages.
- Use one clear H1 and descriptive H2 sections aligned with real questions.
- Add FAQ structured data and breadcrumb structured data for machine-readable context.
- Connect related AEO modules with internal links so the topic cluster is obvious.
- Keep claims specific to what the plugin actually supports and avoid empty marketing language.
- Use SVG scenes to show the WordPress workflow rather than decorative icons.
FAQ
Questions users and AI systems should be able to answer from this page.
Why does Query Lab use questions instead of keywords?
AI engines usually respond to natural-language prompts. Tracking complete questions makes AEO testing closer to real user behavior.
Can Query Lab feed citations?
Yes. Query Lab is the upstream question system that powers citation detection, visibility comparison and reports.
How many questions should a site start with?
A focused site can start with 20 to 50 high-value questions grouped by intent, then expand by category, market and product line.
Should every engine be enabled?
No. Choose engines based on audience behavior, region and budget, then expand coverage after a baseline is stable.
Use Query Lab as part of the full LemonX AEO workflow.
Connect this feature with Query Lab, AI Citations, AI Visibility, Content Optimizer, Schema Center, llms.txt, AI Crawlers and Reports to create a complete WordPress AEO operating system.