Speech analytics converts recorded voice interactions into searchable text and structured data — enabling automated analysis of interaction content, compliance phrase detection, topic trending, sentiment scoring, and the identification of root causes behind performance metrics that operational data alone can't explain.
Voice interactions contain the richest customer intelligence in the contact center, but it's locked in audio files that humans can't analyze at scale. Speech analytics platforms unlock this intelligence — identifying why customers are calling, which agent behaviors drive satisfaction, where compliance risks occur, and what competitors are being mentioned. RLM advises on speech analytics strategy and platform selection for contact centers ready to turn voice data into operational intelligence.
A structured advisory process — from discovery and market evaluation to vendor selection and post-deployment optimization — tailored to your specific environment and objectives.
We assess the analytical questions your contact center needs speech analytics to answer — compliance monitoring, topic trending, agent behavior analysis, competitive intelligence — and the interaction volume and quality that determine platform requirements.
We evaluate speech analytics platforms — Verint Speech Analytics, Calabrio Analytics, NICE Nexidia, Tethr, CallMiner — against your use cases, transcription accuracy requirements, language support, and the analytics workflow that converts insights to operational action.
We design the topic category structure and phrase library — defining the interaction topics, compliance phrases, competitor mentions, and sentiment indicators that the analytics platform will detect and measure.
We design the operational workflow that converts speech analytics insights into action — automated QM flagging for compliance violations, trend alerts to operations managers, and the coaching connection that addresses identified agent behavior patterns.
These are the dimensions that consistently separate successful CX deployments from costly ones — and the questions RLM will help you answer before any commitment.
Speech analytics accuracy depends on transcription quality. Evaluate transcription accuracy across your specific conditions — audio quality variation, accent diversity, background noise, and domain vocabulary — not just vendor-quoted accuracy rates.
Simple phrase matching catches exact compliance language but misses paraphrasing. Evaluate whether the platform offers semantic analysis that detects intent regardless of exact wording.
Speech analytics value degrades as business vocabulary and product names evolve. Evaluate the category taxonomy maintenance process — who owns updates, the trigger for reviewing categories, and the effort involved.
Speech analytics platforms surface patterns but humans must interpret and act. Evaluate the analyst workflow — how insights are reviewed, prioritized, and converted to action — and the organizational capacity required to realize analytics value.
Multi-language contact centers need speech analytics support for every language handled. Evaluate transcription accuracy and analytical capability for each language in your interaction mix.
"RLM helped us select and implement the right CCaaS platform in half the time it would have taken us on our own. Their vendor knowledge is unmatched — they knew exactly what questions to ask."
"We had a legacy premise system and 90 days to migrate. RLM built the plan, managed the vendors, and we hit the deadline with zero customer disruption."
Talk to an RLM advisor who specializes in CX technology. We'll help you find the right solution for your business — without vendor bias.