Automation & AI

When I first started experimenting with sentiment analysis in a ticketing system, I expected a quick win: drop in manual triage, faster escalations, happier customers. What I found was more nuanced and, ultimately, more valuable. Sentiment isn't a magic wand — it's a signal. Done well, it helps your team prioritize, improve coaching, and spot trends before they become crises. Done poorly, it creates false alarms and erodes trust in...

Read more...

Running a vendor trial for an AI assistant is one of those projects that looks deceptively straightforward until you’re three vendors in and your inbox is full of demo recordings, feature matrices, and slippery promises about “human-like” understanding. I’ve run more than a few trials like this, and the difference between a trial that leads to a successful deployment and one that wastes months of team time usually comes down to two...

Read more...

When teams ask me whether they should automate a touchpoint or send a customer to a human, I always push back: the right choice isn’t binary. It’s a sequence of decisions guided by risk, value, frequency, and the customer’s context. Over the past decade I’ve seen the best outcomes come from a practical framework that combines data, customer empathy, and fast experiments. Below I share a framework I use at Customer Carenumber Co to decide...

Read more...

When support teams ask me where to start with automation, the conversation quickly moves from flashy AI demos to the boring-but-critical question: which rules actually reduce repetitive work for agents and increase velocity? Over the years I’ve seen teams pour time into automations that sound clever on paper but don’t move the needle on response times, agent load, or customer experience. Here are five practical automation rules I recommend...

Read more...