Customer Service Articles & Resources
Latest Articles from Swifteq's Blog
Zendesk Jira Integration: Building a Ticket Escalation Process That Works
Most support teams set up a Zendesk Jira integration for one reason: they want engineering to see the tickets that need a real fix without support having to leave Zendesk to ask for it. The integration handles that part well. What it doesn't solve is everything...
The Precondition Problem: Attributing Contact Drivers Appropriately
Contact driver analysis is supposed to tell support leaders why customers get in touch. You’ll often find that reports only tell you what customers asked about. Those are different questions, and the gap between them is where you risk losing a meaningful share of the...
AI Data Privacy for Support Teams: the Checklist Before You Connect AI to Customer Data
AI data privacy for a support team all starts with one question: does your contract match your configuration? Your team wants AI that can dig into tier 2 and tier 3 tickets: pull the JIRA history, read the logs, and tell you what's broken. That takes real system...
How to Automatically Extract Data From PDFs and Images in Zendesk
Customer support teams often receive important information inside attachments rather than in the ticket itself. A customer may send an invoice, shipping label, scanned form, receipt, contract, or image containing details an agent needs before resolving the request....
Generative AI for Customer Service – Using Common AI Tools for Your Back Office Admin
Every conversation about using generative AI tools in customer service seems to start with the customer-facing side: increasing deflection rates through chatbots. Draft replies faster. Heck, the AI can do it all — you’ll never need to touch a ticket again! While the...
From 2% to 100%: a Practical Guide to Auto QA in Zendesk
Most Zendesk quality assurance (QA) programs run the same way: a team lead pulls a handful of closed tickets each week and scores them against a scorecard, usually somewhere between 2% and 5% of total ticket volume. The other 95%-plus closes without anyone looking at...
Writing Knowledge Base Articles for Humans and AI
Your help center used to be just documentation and a place for customers and support agents to find answers. Now, it's the thing your support bot reads to answer customers, and it never stopped being documentation. This means every article now has two readers at...
When Your QA Score Says “Bad Agent”, and It’s Wrong
A dog barks once in the background of an otherwise perfect call. The agent scores zero. A phone transfer drops the first two seconds of a handoff. The receiving agent is dinged for an incomplete greeting. A customer's real name happens to sound like a profanity. An...
How AI Is Changing Support Engineering Roles
Many of us keep hearing that AI is coming for our jobs. Support engineers are no exception. But the reality on the ground can look quite different. Some teams are using AI every day to streamline workflows, automate repetitive tasks, and surface insights faster....
The Problem With Three Knocks (and What Great Support Teams Do Instead)
In customer support, first touch is always important. But follow-up often gets underestimated when teams talk about what creates a strong customer experience. At small volumes, the processes around follow-up are trivial. The agent sends the key message, the customer...
Is Your QA Scorecard Measuring Quality or Just Script Compliance?
There's a Reddit thread on r/callcentres that every support leader should read. An agent describes waking up on rollover day, the morning QA scores reset, excited and confident. They'd followed the call flow perfectly on every new booking call they knew would be...
If Not Empathy, Why Empathy Shaped?
Nearly every QA rubric in Customer Support has a criterion version of it: “agent demonstrated empathy”. Sometimes it gets a point scale. Sometimes a checkbox. Occasionally a grading guide that says something like "score 3 if the agent showed genuine care for the...
What Should Customer Service QA Actually Measure?
One QA team described reading 8,000 to 9,000 tickets per month by hand, and then moving to AI that runs quality assurance on 100% of tickets, freeing those ten reviewers to do other work entirely. A huge improvement in coverage. That also quietly raises the stakes on...
Hiring for the Queue AI Is Building for You
There's a version of the AI-in-Support conversation that goes like this: AI handles the simple stuff, humans handle the complex stuff, everyone wins. It's a reasonable starting point. It's also incomplete enough to produce some genuinely bad hiring decisions. The...
The Four Signals That Should Drive Your Automation Routing Decisions
Discover the four key signals that help support teams make smarter automation routing decisions and send every ticket to the right place.
