GetGo

Overview

Modern support teams are caught between two rising pressures: customers expect instant, accurate answers around the clock, and the cost of staffing a team large enough to deliver that manually keeps climbing. Most organizations end up trading one for the other — fast but sloppy, or accurate but slow.

This is the story of how Peson closed that gap. By deploying an AI-driven support layer built for both speed and precision, they cut average resolution time to under a minute while raising answer accuracy and holding their team steady. The result is support that scales with demand instead of headcount — and customers who get the right answer the first time.

The Opportunity

As Peson grew, its support volume grew faster. Ticket counts climbed 20% year over year, and the team's median first-response time stretched to 2000 hours. Complex questions sat in queues while agents worked through a backlog of repetitive ones — password resets, billing lookups, order status — that consumed the majority of their time but required little judgment.

The strain showed up everywhere. Customer satisfaction scores dipped during peak periods. Agents burned out on monotonous tickets and churned. Every seasonal spike forced a scramble to hire and train temporary staff who were rarely up to speed before the surge passed. Leadership faced a familiar dilemma: keep expanding the team and watch support costs balloon, or cap headcount and let service quality slide.

Neither option was acceptable. What Peson needed was a way to handle far more volume without sacrificing the accuracy and tone that its customers valued — and without simply throwing more people at the problem. The opportunity wasn't just faster replies; it was reclaiming the team's capacity for the conversations that genuinely needed a human.

The Solution

Peson deployed an AI support system designed around a simple principle: resolve what can be resolved instantly, and route the rest to the right person with full context already attached.

The system connects directly to Peson knowledge base, help documentation, and internal systems, so it answers from the same sources of truth agents rely on rather than guessing. When a customer submits a query, the AI interprets intent, pulls the relevant information, and returns a precise, on-brand answer in seconds. For account-specific requests, it securely retrieves the customer's own data — order history, subscription status, past tickets — and resolves the issue end to end.

Precision was the non-negotiable. Rather than optimizing purely for deflection, the system is tuned to recognize the limits of its own confidence. When a question is ambiguous, high-stakes, or outside its knowledge, it hands off to a human agent along with a full summary of the conversation and the context it has already gathered — so no customer has to repeat themselves and no agent starts from scratch.

The Result

Within 28 weeks of full deployment, the impact was clear across every metric that mattered:

Average query resolution dropped to under one minute, down from 2000 hours, as the AI handled the bulk of routine tickets instantly and at any hour. First-contact resolution rose to 23%, meaning customers got a complete answer without follow-ups or escalation. The system now resolves 67% of incoming queries autonomously, freeing agents to focus on the complex, relationship-defining conversations where human judgment adds the most value.