Today, Amazon Web Services Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced the general availability of Contact Lens, a set of capabilities for Amazon Connect enabled by machine learning, that gives contact centers the ability to understand the sentiment, trends, and compliance of customer conversations to improve their experience and identify crucial feedback. Amazon Connect is a fully managed, easy-to-use cloud contact center service that helps companies of any size deliver superior customer service at lower cost—based on the same technology that powers Amazon’s award-winning customer service. Companies like John Hancock, Capital One, Intuit, GE Appliances, Square, Fujitsu, Mutual of Omaha, and Dow Jones use Amazon Connect to run their contact centers at lower cost, while easily scaling to thousands of agents. With Contact Lens, contact center supervisors can discover emerging themes and trends from customer conversations, conduct fast, full-text search on call transcripts to troubleshoot customer issues, and improve contact center agents’ performance with call analytics—all from within the Amazon Connect console. Coming late-2020, Contact Lens will also provide the ability for supervisors to be alerted to issues during in-progress calls, giving them the ability to intervene earlier when a customer is having a poor experience. Contact Lens requires no technical expertise, and getting started takes just a few clicks in Amazon Connect. To get started with Contact Lens for Amazon Connect, visit https://aws.amazon.com/connect/contact-lens
Contact centers are often the only personal connection that a customer has with a company, and the experiences these customers have interacting with agents can have a profound impact on customer trust and loyalty. Contact centers field large volumes of customer calls every day, resulting in millions of hours of recorded calls. These conversations contain valuable customer feedback, but given the volume, companies struggle to extract and analyze this information in a timely fashion, if at all. Most companies that try to get value from this data use legacy contact center analytics offerings, but these technologies are expensive, slow at providing call transcripts, and lack the required level of transcription accuracy—all of which makes it difficult to quickly detect customer issues and provide precise feedback to customer service agents and supervisors. Existing contact center solutions also lack the ability to provide real-time analytics on in-progress calls, which prevents supervisors from identifying and helping frustrated customers before they hang up. As a result of these challenges, many organizations face high levels of customer churn, long hold times, agent turnover, and regulatory fines.
Contact Lens helps contact center users address these problems by providing fully managed, machine learning-powered analytics capabilities within Amazon Connect, with no coding or machine learning experience required. Contact Lens uses highly accurate machine learning technology to transcribe calls, and automatically indexes call transcripts so they can be searched from the Amazon Connect console. Contact Lens also uses machine learning to make it easier for supervisors to search voice interactions based on call content (e.g. customers asking to cancel a subscription or return an item), customer sentiment (e.g. calls that ended with a negative customer sentiment score), and conversation characteristics (e.g. talk speed, long pauses, or customers and agents talking over one another). By clicking on the search results, supervisors can view a contact detail page to see the call transcript, customer and agent sentiment, a visual illustration of conversation characteristics, and use this information to share feedback with their agents to improve customer interactions. Contact Lens also uses natural language processing to help supervisors uncover new issues (e.g. a price discrepancy between a website and an email promotion) on the contact detail page by visually identifying words and phrases in call transcripts that indicate reasons for customer outreach. With Contact Lens, supervisors can automatically monitor all of their agents’ interactions for customer experience, regulatory compliance, and adherence to script guidelines by defining custom categories on a new page in Amazon Connect that allows them to organize customer contacts based on words or phrases said by the customer or agent (e.g. a customer mentioning a competitor, membership in a customer loyalty program, certain regulatory disclosures, etc.). Contact Lens also includes machine learning capabilities to automatically detect and redact sensitive personally identifiable information (PII) like names, addresses, and social security numbers from call recordings and transcripts to help customers more easily protect customer data.
Later this year, Contact Lens will introduce new features that provide supervisors with real-time assistance by offering a dashboard that shows the sentiment progression of live calls in a contact center. This dashboard continuously updates as the interactions evolve and allows supervisors to look across live calls to spot opportunities to help their customers. Real-time alerting gives supervisors the ability to engage and de-escalate situations earlier.
“Amazon Connect has grown very quickly in its first few years as customers find it very attractive to use the same contact center technology (along with the high scale, strong performance, low cost, and embedded AI) that Amazon has used to scale Amazon.com in its first 25 years,” said Larry Augustin, Vice President Productivity Applications, AWS. “Contact Lens leverages various AWS capabilities—such as storage, transcription, natural language processing, and search—but stitches them together for customers into an easy-to-use contact analysis tool, all usable from the Amazon Connect user interface and with no machine learning or heavy programming required.”
Contact Lens capabilities are built right into the Amazon Connect experience. Contact Lens provides metadata (such as transcriptions, sentiment, and categorization tags) in customers’ Amazon Simple Storage Service (Amazon S3) buckets in a well-defined schema. Businesses can easily export this information and use additional tools like Amazon QuickSight or Tableau to do further analysis and combine it with data from other sources. Contact Lens for Amazon Connect is available today in US East (N. Virginia), US West (Oregon), EU (Frankfurt), EU (London), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo) with availability in additional regions in the coming months.
Intuit Inc. is a global financial platform company that gives everyone the opportunity to prosper. “Customers call us to get answers to their complex tax and accounting questions and our experts handle millions of calls from our customers every year. Amazon Connect made it easy to provide customer service reliably and securely,” said Andy Palmer, Vice President of Engineering, Customer Success at Intuit. “With our customers’ awareness of their calls being recorded and monitored, we have been using Contact Lens for Amazon Connect to gather insights from over 200 million minutes of customer interactions. Features like accurate turn-by turn transcription, redaction of sensitive data, and automated call categorization have allowed us to improve the effectiveness of our customer care organization.”
Accolade is a personalized health and benefits solution that serves employers across the country. “At Accolade, we are passionate about our customer experience, especially because we help our customers with life’s most important questions—concerns about their healthcare. With the AWS launch of Contact Lens for Amazon Connect, we’ve transformed our contact center experience,“ said Stephen Murphy, Senior Director, Cloud Engineering at Accolade. “Since Contact Lens works seamlessly with Amazon Connect, it has allowed us to accomplish what other transcription and speech analytics vendors have struggled to achieve. With Contact Lens for Amazon Connect, we’ve processed thousands of calls and have been able to easily uncover emerging trends to provide our agents with the right guidance, improving our customer experience. Enabling Contact Lens for Amazon Connect took only minutes, saving us months of development time it would have taken to build the same powerful AI tools.”
DH Enterprise designs affordable vacations and turn-key solutions in the areas of travel technology, management, and operations. “Customers love vacations so we built our contact center on Amazon Connect to ensure a great customer experience before their flight even takes off,” said Adam Zerlin, COO of DH Enterprise & Associates. “The demos of Contact Lens for Amazon Connect blew away our team. Enabling Contact Lens took seconds, the sentiment score is incredibly valuable, speech transcription is right out of the box, and the underlying data is incredibly detailed. Instead of manually entering results into monthly agent scorecard reviews, we now have an automated, holistic view of our agent’s performance. Contact Lens has helped us derive valuable insights from customer interactions and enabled us to improve the experience for both our customers and agents.”
Traeger Pellet Grills is a privately held American manufacturer of wood-fired pellet grills and related accessories. “When we decided to migrate hundreds of agents from our incumbent telephony platform, we needed something that was simple, scalable, and open. We wanted something future proof. Amazon Connect was the solution. We were able to replicate and enhance our existing infrastructure within days of creating our AWS accounts. For us, one of the most powerful aspects of Amazon Connect is Contact Lens,” said Bryan Teggart, Head of Customer Experience Operations and Analytics at Traeger Pellet Grills. “Contact Lens allows us to simplify agent workflows by systemically identifying key contact attributes (e.g. product model, contact reason, customer sentiment). Those attributes are invaluable to our CX leadership and product/engineering teams. Last month, we analyzed more than 15,000 hours of agent/customer interactions. We used to spend most of our time trying to identify issues. Now, we spend most of our time fixing them.”
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