Speech-to-Text (STT)

Why STT matters in outbound

Short attention windows. STT errors → wrong responses → hang-ups in 30 seconds.

• ✓Noise and accent robustness
• ✓Proper noun recognition
• ✓Barge-in stability
• ✓Low latency (< 300 ms to first token)

STT in Coldbot

ElevenLabs Scribe and telephony-optimized models. Streaming STT enables responses before the caller finishes speaking.

Privacy

Transcripts are sensitive. Coldbot offers retention controls, encryption, DPA, and optional recording disable.

Quality metrics

Target WER < 10% for business Polish/English. Monitor errors in analytics and tune pronunciation dictionaries.

Practical use: Speech-to-Text (STT)

Speech-to-Text (STT) is not an abstract label - it shapes daily decisions in cold calling and lead qualification. Sales leaders use it when designing scripts, choosing telephony stack, and defining what “good” looks like in call analytics. In Coldbot deployments, teams align this concept with measurable outcomes: connect rate, qualified meetings, cost per meeting, and time-to-first-contact after a form fill. A practical workflow: document your current manual process, map which steps a voice agent can own (dialing, qualification, booking), configure integrations so data never sits in a recording, then run a supervised pilot before full list volume. Review transcripts weekly with reps so script changes reflect real objections heard on the line.

• ✓Define success metrics before scaling volume
• ✓Pilot on 50–100 calls with QA sampling
• ✓Iterate script based on call analytics
• ✓Expand to adjacent use cases after stable KPIs

Common mistakes to avoid

Teams new to voice AI often optimize for the wrong thing - voice aesthetics instead of meeting conversion, or they scale volume before the script handles top objections. Another failure mode is treating the CRM as optional: without automatic write-back, reps duplicate work and trust in the system drops. Finally, ignoring compliance (DNC lists, calling hours, recording disclosure) creates legal risk that outweighs any efficiency gain. Coldbot onboarding explicitly covers these pitfalls with guardrails, disposition codes, and integration tests before production dialing.

• ✓Scaling before script QA on real calls
• ✓No CRM field mapping - data stuck in audio
• ✓Skipping DNC / consent hygiene
• ✓Changing too many variables at once in A/B tests

FAQ

Frequently asked questions

Related terms