Insights & Actions
Run 1 · complete
Insights this run
Answer engines confuse “Boo Lab” with a dating app and a gaming/casino platform Action required
On the two brand-interrogation prompts (“is Boo Lab legit”, “Boo Lab pros and cons”), the answer engines did not return boolab.ai at all. Instead they described a “Boo” 3D-avatar/dating app and a “Boo Lab” online-gaming/casino platform (“verified by the Malta Gaming Authority”). The single-word brand “Boo” collides with high-volume unrelated products, so a prospect asking an AI about Boo Lab gets someone else's reputation. This is the highest-leverage problem in the baseline: it poisons branded discovery.
Zero presence in the core “AI agent / AI coworker” category (10% visibility, last place) Action required
Across 7 unbranded category-recommendation prompts, Boo Lab was named 0 times. Zapier (45%), Agentforce (30%), n8n (30%), Lindy (25%), and Copilot Studio (20%) own the category. Boo Lab's overall visibility of 10% comes almost entirely from prompts that named it. The models don't know Boo Lab competes here.
The exact product pitch loses on problem-first prompts Notable
“One AI across engineering, support, and marketing” and “one tool that plugs into Slack, GitHub, and analytics instead of five tools” are Boo Lab's literal homepage pitch, yet the answers recommend Zapier, HubSpot Breeze, Sigma, and Notion AI. The problem-first prompts (no brand named) are where a company actually discovers a new tool, and Boo Lab is absent from all of them.
The one substantive win shows the model CAN place Boo Lab correctly Info
On “Boo vs Microsoft Copilot for a small team” the answer correctly described Boo (boolab.ai) as “proactive work delivery across tools” at position 2. When the prompt disambiguates and the query is comparison-shaped, the model places Boo Lab accurately. That's the template: give the models disambiguated, comparison-shaped owned content and they use it.
Action ledger
Publish a disambiguating “What is Boo Lab?” entity page + Organization/FAQ JSON-LD
Ship a crisp entity page on boolab.ai (“Boo Lab is an AI coworker for companies…”) with Organization, Product, and FAQPage JSON-LD that states the category explicitly, plus an FAQ answering “is Boo Lab an AI agent platform?”. Pair with a stats/entity page and consistent “Boo Lab (the AI coworker)” phrasing across owned properties so retrieval and future training pin the right entity. Why this works: models resolve ambiguous single-word brands using structured entity signals + category-consistent owned content; today there is almost none for the AI-coworker “Boo”.
Expecting branded-prompt visibility to move up
Write the definitive “AI coworker vs AI agent platform” pillar guide (unbranded, honest)
A category-defining guide answering “what is the best AI coworker for a company” that honestly frames the landscape (Zapier/n8n = automation, Copilot/Agentforce = suite-locked, Lindy = personal assistant) and where a cross-team AI coworker like Boo fits. Schema-marked, stats-backed, updated-dated. Why this works: category-recommendation and problem-first prompts pull from authoritative unbranded guides; Boo Lab is cited in none today.
Expecting category visibility to move up
Ship “One AI coworker vs five point tools” comparison + Boo vs Zapier/Lindy pages
Boo Lab's differentiator (one hire across every team vs stitched point tools) is a comparison story the models will cite. Draft “Boo Lab vs Zapier” and “Boo Lab vs Lindy” honest comparison pages plus a “why one AI coworker beats five point tools” piece, all schema-marked. Why this works: comparison prompts and problem-first prompts pull heavily from “X vs Y” pages; competitors have them and Boo Lab does not.
Expecting problem_first + comparison visibility to move up