Why chat costs less per contact than voice
A trained chat agent handles two to four conversations at once, so cost per resolved contact typically lands 30–50% below voice. The trade-off is that quality depends heavily on macros, a clean knowledge base and a supervisor watching queue depth.
Push concurrency past four and both CSAT and resolution rate fall off quickly. Any vendor promising six concurrent chats is quoting a number they cannot sustain.
What to specify before you get quotes
Peak concurrent chats, coverage hours in your timezone, target first-response and resolution times, your chat platform (Intercom, Zendesk, Freshchat, HubSpot, Gorgias) and whether agents need order-system write access.
Also decide what happens after hours: a bot with a ticket handoff, a smaller night pod, or a queued-response promise. Undefined after-hours behaviour is the most common source of bad chat CSAT.
Vetting a chat team specifically
Written English is the deciding skill, so ask for anonymised transcripts rather than call recordings, and test spelling, tone and how the agent handles an angry customer in text.
Check that QA scores transcripts, not just handle time, and that macros are reviewed monthly. Stale macros are why chat quality quietly degrades after quarter one.
Where AI genuinely helps on chat
Deflecting repeat FAQs, drafting suggested replies, summarising conversations and auto-tagging tickets. Full autonomous resolution works for narrow, low-risk intents — order status, hours, tracking — and little else today.
We are honest about this: keep humans on anything involving money, cancellations or an upset customer, and use AI to make those humans faster.