AI Visibility Study: Customer Support Platforms

Content

Why we ran this study

At GEO Advisor we measure how software categories show up in AI generated answers. As buyers increasingly ask AI for tool recommendations, visibility inside models is a new competitive surface. This study looks at customer support and helpdesk platforms to understand who gets recommended, how they are framed, and which buying signals drive those recommendations.

Methodology

We ran 300 prompts across buyer intents, persona contexts, and product comparisons. For each brand we measured:

• Mention rate

• Sentiment

• Share of voice

We combined those signals into an AI Visibility Score and extracted the qualitative drivers models reference when recommending or rejecting a product.

Top results

Zendesk: 97.3

Mentioned in 71.7 percent of queries
Share of voice: 37.4 percent

AI frames Zendesk as best in class for multichannel support and mature analytics. The platform is the go to when the question is about scaling operations or reporting.

Strengths surfaced by AI:

• Multichannel and omnichannel capabilities

• Robust analytics and reporting

• Large ecosystem of apps and integrations

Tradeoffs surfaced by AI:

• Steep learning curve and complex onboarding

• Pricing that scales quickly with agents

(Insert image: Zendesk card with score and summary)
Caption: Zendesk leads on visibility driven by enterprise depth and analytics.

Intercom: 84.5

Mentioned in 56.7 percent of queries
Share of voice: 29.6 percent

Intercom shows up as the leader for real time chat and in app messaging. Models recommend it when the context emphasizes product led onboarding or live engagement.

Strengths surfaced by AI:

• Real time chat and in app messaging focus

• Product led onboarding and self serve flows

• Automation and bots for quick workflows

Tradeoffs surfaced by AI:

• Cost at scale for larger teams

• Less depth for ticketing and backend support operations

(Insert image: Intercom card with score and summary)
Caption: Intercom is recommended for real time engagement and product led growth.

Freshworks / Freshdesk: 77.9

Mentioned in 63.3 percent of queries
Share of voice: 33.0 percent

Freshworks appears as an accessible, easy to adopt option. AI often recommends it for teams prioritizing value and speed to launch.

Strengths surfaced by AI:

• Affordable pricing and clear value proposition

• Intuitive UI and easy onboarding

• Omnichannel and multichannel support for smaller teams

Tradeoffs surfaced by AI:

• Limited enterprise reporting and analytics maturity

• Questions around scalability for large operations

(Insert image: Freshdesk card with score and summary)
Caption: Freshworks ranks for ease of adoption and price conscious teams.

Big takeaway

In customer support, AI favors real time engagement, ease of onboarding, and multichannel coverage. Those attributes increase recommendation frequency and positive framing. Once teams scale, pricing and operational depth become the dominant drivers of sentiment. In short, early stage signals win visibility, and enterprise signals win trust.

For product and marketing teams this matters. If you want AI to recommend your platform to growing buyers, emphasize quick time to value and clear stories about channel coverage. If you sell to enterprise buyers, surface integration depth and reporting credentials in short answers so models can pick them up.