A Midwest industrial parts distributor was drowning in 1,400+ monthly support tickets. Here's how they automated 78% of them, saved $141K in year one, and freed their team to grow revenue instead.
Deep-dive into existing support operations: ticket categorization, volume analysis, response time benchmarks, and knowledge base gaps.
Platform deployment, knowledge base creation from SOPs and product catalogs, CRM/ERP integration, and AI training on historical ticket data.
Team training on the new system, escalation workflow setup, monitoring dashboard configuration, and go-live with supervised rollout.
A 200-person industrial parts distributor in the Midwest was fielding 1,400+ support tickets per month across two channels: email and phone. Their 6-person support team spent 70% of their time answering the same 40 questions about order status, shipping timelines, and return policies.
Response times had stretched to 28 hours. Customer satisfaction scores were declining quarter over quarter. And hiring another rep wasn't an option at $58K/year fully-loaded. Something had to change.
The DiscoveryDuring our Week 1 audit, we categorized every ticket from the previous 90 days. The finding was striking: 78% of inbound tickets mapped to fewer than 50 distinct question types. Order status, shipping ETAs, return policy, product specs, warranty claims. The same questions, asked hundreds of different ways.
This is exactly the pattern where AI customer service delivers maximum ROI: high volume, predictable questions, clear correct answers.
The SolutionWe recommended and implemented Zendesk AI with a custom knowledge base built directly from their SOPs, product catalog, and ERP data. The AI was trained to understand the company's specific terminology, product codes, and fulfillment workflows.
Integration with their existing systems took 11 days. Agent training took 3 days. Go-live was day 19.
Key decision: We chose Zendesk AI over newer entrants because the client was already on Zendesk for ticketing. Migrating platforms during an AI rollout doubles the risk. We kept the foundation stable and added intelligence on top.
Within 60 days of go-live, 78% of tickets were resolving without human intervention. Average response time dropped from 28 hours to under 4 minutes. The AI handled the volume while the humans handled the judgment calls.
The support team, still the same 6 people, shifted their focus to complex B2B account management. That shift directly contributed to a 12% increase in repeat order revenue in the following quarter.
Total first-year savings: $141,000. The engagement paid for itself in under 90 days.
In 30 minutes, we'll analyze your support operations, identify your highest-ROI automation opportunities, and give you a clear implementation roadmap at no cost.
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