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Solutions for Machine Learning and Artificial Intelligence in Amazon Connect Contact Lens

Contact Lens for Amazon Connect provides a set of machine learning tools that enable businesses to analyze call recordings for customer sentiment, trends, and compliance

Contact Lens for Amazon Connect provides a set of machine learning (ML) and artificial intelligence (AI) capabilities integrated into Contact Lens. These capabilities enable businesses to create data analytics from actual customer call recordings or utilize live tracking for analyzing customer sentiment, trends, and service agent compliance. Using real customer data improves the accuracy of data analytics specific to a business’s customer base.

Additionally, Contact Lens supports real-time call analytics that enables customer service agents and managers to detect customer experience issues during live calls and resolve issues on the spot. Customer service managers need real-time, accessible customer experience data via alerts while calls are in progress to manage contact centers effectively. 

Live call tracking saves contact center resources while reducing costs by tracking customer experience issues in real-time rather than listening to past recordings. The training of quality customer service agents improves when performed directly and without negatively impacting the customer experience. 

What ML/AI features are available in Connect Contact Lens?

Customer service tools that use ML and AI technology in Contact Lens include:  

  • Automated call categorization
  • Advanced conversational speed analysis
  • Call summarization
  • Analytics dashboards
  • Customizable real-time alert generation
  • Automatic customer sentiment analysis 
  • Secure data redaction for customer data privacy and security 

Automated call categorization provides customer and agent conversation tracking. Tracking customer service agent interactions with customers allows for keeping track of agent compliance with company policies and regulatory requirements. Using an ML-powered engine trained to understand spoken phrases, sentiments, and conversation interruptions provides real-time and recorded call data for customer service agent training and maintaining compliance records. 

The advanced conversation analysis allows users to do a full-text search during calls for keywords, sentiment scoring, and to automatically determine the call category. The data from searching assists in understanding customer trends as well as customer service agent training needs. 

Call summarization uses ML to identify key parts of the agent-to-customer conversation. During and after the call, the system creates a summary of the call transcript for review. 

All the customer call analytics are accessible from the analytics dashboard. The dashboard provides a contact detail page, call transcripts, sentiment analysis, and any alerts generated during customer-to-agent conversations. 

The real-time alerts feature alerts users to customer service issues. Alerts are fully customizable based on the business need. Organizations create rules that alert managers or supervisors in real-time when and where customer service agents need experienced assistance. 

The sensitive data redaction feature automatically removes sensitive or personally identifiable customer information from call transcripts and audio recordings. This includes names, addresses, social security numbers, and other ID identifiers as well as credit card information. 

Using the ML/AI Contact Lens solutions for customer service and experience management provide business value by creating real, secure customer data sets the business can leverage to attract and retain customers. The customer experience improves by providing immediate training as needed when adverse service situations arise or when agents need support from managers or supervisors. 

Other business benefits from using the ML/AI features in Contact Lens include: 

  • Tracking customer experience issues by grouping them into categories based on conversation type and phrase tracking. There’s also the option to use ML-based semantic matching. 
  • Customized API solutions for handling customer service agent uses cases like transferring calls to other agents, escalating to management, or moving the call to the next service level. Once transferred, all the customer data automatically transfers as well, so there’s no need for customers to repeat their issues. 

What business value is gained from data analytics?

What is the business value of data analytics gained from customer contact? Customer data from any channel (phone, text, SMS, chat, or other) provides the foundation to make better decisions and improve short- and long-term profitability. Customer data analysis provides the knowledge to sustain a competitive advantage by attracting new and retaining existing customers. Organizations using customer data analysis respond to market conditions faster while achieving higher levels of customer satisfaction. 

According to Forrester, business organizations must leverage customer data to improve their customer experience. Companies successfully leveraging customer data become customer experience (CX) leaders that exceed business goals, and that creates a competitive business advantage regardless of the industry. By personalizing customer interactions while keeping the human interaction element intact, companies are taking advantage of solutions using ML/AI to become customer experience leaders. 

According to a report by McKinsey, adding personalization to customer service increases revenue by 5% to 15% and marketing strategy efficiency from 10% to 30%. Personalized contact per customer improves the customer experience by helping customers feel heard and appreciated.

How does saving customer data improve the customer experience?

Customer retention is key to succeeding in today’s business world. Improve customer retention by leveraging customer data within the system to improve customer service on the spot while providing customers with personalized information and a human-centered customer experience.

Need help customizing Contact Lens to leverage customer data and improve the customer experience? CloudHesive provides the expertise needed for support, assistance, and implementation using AWS best practices for successful customer service and data management.

CloudHesive provides support and deep expertise in using the Amazon Web Services cloud for the best business advantage. As an Amazon Managed Services Partner and Amazon Premier Partner, CloudHesive helps businesses take full advantage of all the features AWS offers, including Amazon Connect Contact Lens contact and customer service management. See what other customers have to say in case studies available from CloudHesive.