Contact Lens for Amazon Connect

Contact center analytics for Amazon Connect powered by machine learning

Contact Lens for Amazon Connect is a set of machine learning (ML) capabilities integrated into Amazon Connect. With Contact Lens for Amazon Connect, contact center supervisors can better understand the sentiment, trends, and compliance risks of customer conversations to effectively train agents, replicate successful interactions, and identify crucial company and product feedback.

Today, most contact center analytics are based on phone switch activity or customer relationship management (CRM) call notes that are typed in by the contact center agent. What's typically missing from these analytics is insight into the actual conversations between agents and customers. Contact center supervisors are hungry for insight into things like whether agents are having effective conversations, whether any interesting trends in customer sentiment are occurring, or whether the agents are complying with regulatory requirements. This is challenging because audio data is virtually impossible for computers to search and analyze. Therefore, recorded speech needs to be converted to text before it can be used in applications. Historically, customers had to work with transcription providers that required them to sign expensive contracts and were hard to integrate into their technology stacks to accomplish this task. Many of these providers use outdated technology that does not adapt well to different scenarios, like low-fidelity phone audio common in contact centers, which results in poor accuracy. While speech-to-text analytics solutions have long promised access to these type of insights, they have not provided an accurate or cost effective way to extract insights from these conversations.

Using AWS machine learning natural language processing (NLP) and speech-to-text, Contact Lens for Amazon Connect transcribes contact center calls to create a fully searchable archive and surface valuable customer insights. With Contact Lens for Amazon Connect, customer service supervisors can quickly and easily discover emerging themes and trends from customer conversations, directly in Amazon Connect. The machine learning models that power Contact Lens for Amazon Connect have been trained specifically to understand the nuances of contact center conversations including multiple languages and custom vocabularies. With Contact Lens for Amazon Connect, customer service supervisors can conduct fast, full-text search on call and chat transcripts to quickly troubleshoot customer issues. They can also leverage call and chat-specific analytics, including sentiment analysis and silence detection to improve customer service agents’ performance. Contact Lens for Amazon Connect will also allow supervisors to be alerted to issues, like when an agent is unable to help a frustrated customer, giving them the ability to intervene earlier when a customer is having a poor experience. Using these integrated capabilities requires no technical expertise, and getting started takes just a few clicks in Amazon Connect.


Deeper insight in minutes

Contact Lens for Amazon Connect is simple to set up and use. With only a few clicks, you can use ML-powered analytics to discover deep customer insights from your contact center. Through the intuitive UI, you can analyze call and chat transcripts, customer and agent sentiment, and conversation characteristics without any coding.

Pay-as-you-go pricing

With Contact Lens for Amazon Connect, you are only charged for what you use. There are no upfront costs, minimum fees, or long-term commitments, making it a cost-effective way to gain deeper customer insights. Contact Lens for Amazon Connect is also available in the AWS Free Tier, so Amazon Connect customers can try it without any initial investment.

Better customer experiences

Contact Lens for Amazon Connect helps supervisors improve the agent customer interaction by providing insights around what makes a successful call, compliance risks, and trends in topics with new rich metadata around call transcripts and conversation characteristics such as indicators of interruptions, talk speed, sentiment, and custom category labels.


Conduct fast, full-text search on calls and chats for ad-hoc analysis and deep visibility into all conversations. Search on keywords, sentiment scores by customer or agent, and “non-talk” time to identify calls with varying degrees of customer experiences, so you can react quickly to improve contact center experiences. For example, you can identify what utterances are common in successful or unsuccessful calls to improve agent call scripts.

Automated contact categorization

Track all customer conversations for regulatory compliance and monitoring of the customer experience. You can define and manage categories based on your specified criteria directly within Amazon Connect. For example, you can use these category labels to create scorecards that show what percentage of agents adhered to company standard greetings and sign-offs and track that agents are properly handling sensitive customer data.

One view for all analysis

Contact center supervisors can view data and reports from Contact Lens for Amazon Connect directly in the Amazon Connect UI. You can review details of individual calls, analyze transcripts, customer and agent sentiment, and conversation characteristics. For example, you can see how often a customer asks the agent to repeat themselves to identify agent coaching opportunities.

Open and flexible data

Contact Lens for Amazon Connect output file contains call and chat transcripts along with rich metadata such as sentiment, categorization labels, talk speed, and interruptions. You can leverage this data in various existing systems. For example, you can use this data in a BI tool, like Amazon QuickSight, along with your CRM data to gain insights into customer engagements. Your data science teams can also use this data to create custom machine learning models with Amazon SageMaker.

Theme detection (coming soon)

Discover emerging issues and understand the customer service implications with theme detection. Without knowing what to search for, theme detection can help discover issues that that were previously unknown. For example, quickly understand if customers are calling in about a discrepancy in pricing on the website versus a direct mailer. React to trends by taking actions such as updating contact flows and call scripts.

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