Conversation intelligence uses AI to extract signals from sales and support calls — coaching opportunities, compliance risks, revenue patterns, and customer intent. It is how high-performing teams learn from every call, not just the ones they happen to review.
Conversation intelligence is the practice of using AI to capture, transcribe, and analyse customer conversations — then surfacing actionable insights for sales performance, customer experience, and regulatory compliance.
These three terms are related but distinct. Understanding the differences helps you choose the right approach for your team.
The technology layer. Converts voice to text and detects keywords, emotions, and patterns. Speech analytics is a component of both call QA and conversation intelligence.
The quality assurance process. Uses speech analytics (or manual review) to score calls against a rubric and identify coaching needs. Primarily inward-facing (improving agent performance).
The broadest category. Encompasses call QA but also includes revenue intelligence — deal risk signals, objection patterns, competitive mentions, and forecasting inputs from calls.
Which agents consistently skip discovery questions? Which agents give up after the first objection? Conversation intelligence identifies the specific, repeatable behaviours that separate high performers from average ones — then gives managers the transcript evidence to coach on.
When a customer says "I need to talk to my wife about this" or "we are also looking at one other option" — conversation intelligence flags these as risk signals on active deals. Sales managers can prioritise follow-up before deals go cold.
When customers mention a competitor by name — what context triggers the comparison? How do agents typically respond? Conversation intelligence aggregates this across hundreds of calls to surface patterns that product and marketing teams can act on.
For regulated industries (insurance, banking, lending, telecom), conversation intelligence checks every call for mandatory disclosures and prohibited language — automatically. A human QA team checking 2% of calls cannot provide this coverage.
What are the most common objections on calls this month? Are they changing over time? When a pricing objection doubles in frequency, it may signal a market shift — conversation intelligence catches this before it shows up in the CRM.
In practice, conversation intelligence starts with a call recording. The recording is transcribed — ideally in the actual language of the call, including any code-switching between Hindi and English. The transcript is then analysed for quality signals (did the agent complete all required steps?), emotional signals (how was the customer feeling?), and content signals (what topics, objections, or competitor names came up?).
The output is a structured summary of the call, a quality score, flagged moments that need attention, and — at scale — trend data across all calls reviewed.
The global conversation intelligence market is dominated by tools built for English-language, US-focused enterprise sales — Gong, Chorus, Clari. These tools provide excellent value for the use cases they were designed for, but they do not handle Hindi, Hinglish, or Indian regulatory compliance natively.
Bolo Aur Likho brings conversation intelligence to Indian sales and contact centre teams — with native support for Hindi, Hinglish, Tamil, Telugu, Marathi, and 90+ other languages, and with India-specific compliance patterns built in. Free to use, no contract required.
Upload any call recording. Instant transcript, sentiment, and quality analysis. Free, no signup.
Try Free →