Multi-Tier AI Support and Analytics for a US Community Fiber ISP

Client profile

A US community fiber ISP serving residential communities and the property managers who look after them. The company delivers fiber internet, TV, managed WiFi, and voice. Its in-house customer support team is a central part of how it serves those communities.

Industry: Telecommunications (community fiber broadband) · Region: United States · Products used: GoZupees AI voice and chat agents

The challenge

Serving whole communities puts extra weight on every support conversation. Resident experience shapes how property managers judge the service, and the provider had no clear view of which communities were struggling.

Resident experience shaped community relationships

When residents wait too long, get generic troubleshooting, or feel unheard, they tell the property manager. Those conversations influence whether a community keeps the service. Issues that barely show up in company-wide metrics can be obvious to the people responsible for a single community. The provider had no systematic way to see that risk early.

Demand varied through the year

Support volume rose and fell through the year in some communities, so the team was staffed for peak demand and carried spare capacity in quieter months. Letting wait times grow at peak was a poor fit for a service judged on resident experience.

Changes in the home created extra contacts

Moves to new in-home equipment and service setups generated questions about device setup, WiFi, TV navigation, and billing. Those conversations were harder for residents who were less familiar with the new setup.

Property managers had no priority channel

Property managers called the same line as individual residents and waited in the same queue. A community-wide issue had no priority path and no experience designed for that audience.

Our approach

We deployed a multi-tier AI support system: a residential agent, a property manager agent, and community risk analytics. Call analytics closes the loop, so support conversations can flag communities that need attention.

What we built

Residential support agent

GoZupees AI voice and chat agents handle everyday resident support:

• Connectivity troubleshooting using the provider’s managed WiFi data, so guidance can refer to the resident’s actual network rather than a generic script.
• Equipment setup in plain language and at a patient pace, including WiFi and TV equipment.
• TV and entertainment support, including picture issues and everyday feature questions.
• Billing and account changes.
• Guided flows for residents moving onto a new service setup.

The agent avoids jargon, does not assume technical familiarity, and starts from what the resident sees on screen.

Property manager agent

A separate experience for property managers:

• Priority routing, so property manager contacts are not stuck behind the residential queue.
• Community-wide issue handling, with escalation and status updates when a problem affects more than one home.
• Onboarding help for new communities, including scheduling, resident communication, and go-live support.
• Service summaries covering volume, common issues, and open tickets.
• Billing and account administration for the community.

Community risk analytics

Support data turned into a view of each community:

• A health score from support patterns: volume, repeat contacts, sentiment, resolution time, and escalations. A declining score is a prompt to look closer.
• Flags for communities where a specific issue is rising, so the network team can investigate.
• Tracking during service changes, so the team can see whether a rollout is creating friction.
• Reports account managers can share with a community, covering service quality and how issues were handled.
• Seasonal pattern analysis, so the team can prepare for predictable busy periods.

Results

Within 90 days of launch, the deployment reached 50%+ first-contact resolution.

Metric	Result
First-contact resolution	50%+ within 90 days of launch

Why this matters

When a provider serves residential communities, support quality is a retention issue, not only a cost line. Turning support conversations into community-level signals lets account teams step in early and talk about the relationship with evidence of how the service is actually performing.