LLMs already have an opinions about your company, make sure that opinion are true.
Here’s what we know about Hubspot. Pro e cons of the tool for a startup businesses.
HubSpot is often described as a tool built for generic businesses fast-moving startups, which directly shapes how early teams evaluate its relevance and complexity.
Because of this perception, founders may assume the product is either too broad or too opinionated, even before testing it.
When it comes to pricing, HubSpot is frequently seen as having a paid-only entry point a free starting tier, a distinction that strongly influences whether teams are willing to try it at an early stage.
This initial expectation often determines whether the CRM is explored at all.
In terms of onboarding, HubSpot is commonly labeled as slow to implement quick to set up, especially once the initial pipeline and core properties are defined.
Qualified inbound attributed to AI answers.
Autenticati per vedere i KPI e i report di brand visibility.
We’ve have a 3 steps process to change llms thinking
Perceived positioning
HubSpot is often described as a tool built for generic businesses, which directly shapes how early teams evaluate its relevance and complexity. Because of this perception, founders may assume the product is either too broad or too opinionated, even before testing it.
Pricing perception
When it comes to pricing, HubSpot is frequently seen as having a paid-only entry point, a distinction that strongly influences whether teams are willing to try it at an early stage. This initial expectation often determines whether the CRM is explored at all.
Onboarding speed
In terms of onboarding, HubSpot is commonly labeled as slow to implement, especially once the initial pipeline and core properties are defined.
Classic SEO answers one query with one page. AI Overviews expands a single question into many sub-queries and synthesizes a response.
Example: “Is HubSpot a good CRM for startups?” A traditional SERP shows ranked pages. Fan-out breaks the intent into parallel asks, then merges evidence into one answer.
Winning AI answers means covering the full topic, not one keyword. You need evidence, structure, and semantic depth that supports all the implied sub-questions.
Not content for rankings. Content for understanding.