How to calculate the exact break-even point for replacing phone support with asynchronous chat

When a leadership team asks me whether they should replace phone support with asynchronous chat, the real question is rarely about preference. It’s about money, capacity, and customer experience. The word “replace” hides a lot of trade-offs: cost per contact, resolution time, customer...

How to calculate the exact break-even point for replacing phone support with asynchronous chat
Aug 05, 2026 • by Claire Moreau

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One-week playbook to scale multilingual omnichannel support without hiring more agents

One-week playbook to scale multilingual omnichannel support without hiring more agents

Scaling multilingual omnichannel support without increasing headcount is absolutely possible — I've done it with teams ranging from ten to a few hundred agents. The trick is to combine pragmatic automation, smarter routing, and a targeted human augmentation strategy so you serve more customers across channels and languages while keeping quality steady. Below is a one-week playbook you can...

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How to measure the true ROI of a GPT-assisted agent workflow in seven days

How to measure the true ROI of a GPT-assisted agent workflow in seven days

I recently ran a seven-day sprint to measure the true ROI of a GPT-assisted agent workflow, and I want to share the exact approach I used so you can replicate it. When vendors promise “faster replies” and “higher CSAT” with large language models (LLMs), what they rarely provide is a simple, repeatable framework for quantifying the business impact in your environment quickly. This is that...

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Building an auditable human handover trail for generative AI assistants in regulated support environments

Building an auditable human handover trail for generative AI assistants in regulated support environments

I’ve spent years helping support teams stitch together people, processes and platforms so that technology genuinely improves customer outcomes. When generative AI assistants enter the picture, one of the first questions I hear from teams in regulated industries is: “How do we prove what the AI did and when a human took over?” Building an auditable human handover trail isn’t just about...

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One-week experiment to measure how GPT-assisted replies change CSAT and handle time

One-week experiment to measure how GPT-assisted replies change CSAT and handle time

I ran a one-week experiment in my support team to answer a simple but important question: how do GPT-assisted agent replies affect CSAT and handle time? We’ve all seen glossy vendor decks claiming AI will cut handle times and boost satisfaction simultaneously, but in practice those goals can conflict. I wanted a pragmatic, measurable test that would tell us what actually happens when agents use...

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Exact eight-field ticket schema to attribute deflection to knowledge updates across chat, email and phone

Exact eight-field ticket schema to attribute deflection to knowledge updates across chat, email and phone

When you update your knowledge base, how do you know whether that work actually reduced incoming contact volume — and which channels benefited? I’ve spent years helping support teams move from intuition to measurable outcomes, and one of the most reliable levers is tracking deflection attributed to knowledge updates. The challenge has always been practical: tickets are created across chat,...

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Three surgical edits to a knowledge article that lift deflection by 10% for enterprise SaaS

Three surgical edits to a knowledge article that lift deflection by 10% for enterprise SaaS

I often get asked: what single change will move the needle on self-service metrics fastest? In my experience with enterprise SaaS support teams, the answer rarely lives in a full redesign or a new platform module. It lives in precise, surgical edits to the knowledge base articles agents and customers already use. I want to walk you through three targeted edits I’ve used repeatedly to increase...

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Playbook to design a human fallback for chatbot failures that preserves compliance in regulated industries

Playbook to design a human fallback for chatbot failures that preserves compliance in regulated industries

When a chatbot fails in a regulated environment — finance, healthcare, telecoms — it’s not just an annoyance: it’s a potential compliance incident. I’ve seen automated assistants misroute sensitive queries, collect information they shouldn’t, or give incomplete answers that drive customers to escalate through unsafe channels. Designing a human fallback that both restores a great...

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How to build a three-metric early-warning system from chat transcripts that predicts escalations before customers reopen tickets

How to build a three-metric early-warning system from chat transcripts that predicts escalations before customers reopen tickets

I want to walk you through a practical, lightweight approach I’ve used to catch problems early in chat channels: a three-metric early-warning system derived from chat transcripts that predicts when a conversation is likely to escalate or when a customer will reopen a ticket. This isn’t an academic exercise — it’s a pragmatic toolkit you can implement with transcript exports, a bit of NLP,...

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How to run a seven-day vendor trial that isolates long-term training and hidden migration costs for zendesk vs intercom

How to run a seven-day vendor trial that isolates long-term training and hidden migration costs for zendesk vs intercom

I run a lot of vendor trials for support teams, and one lesson keeps resurfacing: a standard seven-day trial rarely reveals the full cost of switching platforms. Vendors make their modern UIs and canned automations look effortless, but the long-term expenses — training, migration complexity, custom workflows, and maintenance — are where budgets and timelines actually get spent. In this post...

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How to create a sprint-ready playbook to convert failed chatbot handoffs into measurable CSAT wins within two weeks

How to create a sprint-ready playbook to convert failed chatbot handoffs into measurable CSAT wins within two weeks

When a chatbot hands a conversation off to a human and the customer leaves frustrated, nobody wins. Yet failed handoffs are common — unclear context, long wait times, repeated questions, and agents who lack the right information. Over the past decade I've helped teams turn those moments from pain points into measurable CX wins. Here’s a sprint-ready playbook you can run in two weeks to...

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