Start with one conversation type, not the whole funnel
Pick a single, well-defined job — qualifying inbound leads, or booking appointments — rather than trying to automate the entire customer journey at once. A narrow first deployment is easier to review, easier to fix, and gives you a real basis for deciding what to automate next.
Decide the escalation path before launch, not after a complaint
Every automated flow needs a clear answer to "what happens when the agent can't handle this?" — a defined handoff to a human, not a dead end. Deciding this upfront also clarifies what the agent should and shouldn't attempt in the first place.
Write the qualifying questions down before building the agent
If a human rep would ask about budget, timeline and fit on a qualifying call, the agent needs the same structure — not a vague instruction to "have a helpful conversation." Specific questions produce specific, usable data; vague instructions produce inconsistent transcripts nobody can act on.
Decide what you'll measure in the first 30 days
Response time, qualification rate, and human handoff rate are usually more useful early signals than raw call volume. Agree on these before launch so the first review is a real evaluation, not a retrospective guess at what mattered.
Review real transcripts in week one, not just dashboards
Aggregate metrics hide the specific phrasing or edge case that's actually going wrong. Reading a sample of real conversations in the first week catches issues a summary number won't surface until it's already cost you leads.
How Lira handles this
Every call and chat gets a full transcript, summary and structured outcome automatically, and human handoff is a configurable step in any agent — not a separate system to bolt on.
See Conversation Intelligence →