Contact Lens for Amazon Connect, a feature of Amazon Connect, helps you follow the sentiment and trends of customer conversations in real time to identify crucial company and product feedback. You can also track the agent compliance of customer conversations in your contact center to ensure standard greetings and sign-offs are used, help train agents, and replicate successful interactions.

Supervisors can conduct fast full-text search on all transcripts to quickly troubleshoot customer issues. Using real-time analytics powered by machine learning (ML), you can also get alerted to issues during live customer calls and deliver coaching to agents while calls are in progress, improving customer satisfaction.

Uncover trends and improve customer service

Easily understand sentiment, conversation characteristics, and agent compliance risks in call transcripts using natural language processing (NLP) and ML-powered speech-to-text-analytics to discover customer insights and identify agent coaching opportunities. Set real-time alerts to flag customer issues for detailed analysis in the analytics dashboard, or use data streams to build dashboards with near real-time analytics that includes sentence-by-sentence transcripts, sentiment analysis, and categories from customer conversations.

Empower your agents to offer exceptional service

Save your agents valuable time on every call by automatically recording and transcribing key parts of customer interactions without the need to take detailed notes. Managers can view call summaries alongside the call recording and contact details in Amazon Connect to quickly understand the context of an interaction, help with follow-up items such as issuing refunds, and provide precise feedback to agents.

Automate and enhance security and operations

Automatically detect and redact sensitive customer data such as name, address, and social security number from call recordings and transcripts. Improve agent compliance with company policies or regulatory requirements by tracking all customer conversations with categories that are understood by an ML-powered categorization engine and based on criteria you determine—for example, words or phrases used in standard greetings and sign-offs.

Get access to Contact Lens analytics on a near real-time basis using contact streams. These streams provide sentence-by-sentence transcripts, sentiment analysis, and categories for ongoing agent-customer conversations with low latency. Supervisors can now join these conversations to assist agents troubleshoot and solve complex customer issues on a live call.