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Amazon Connect Features ML-Powered Solutions to Build Your Business

Get the Real-Time Data You Need to Boost Customer Service, Fraud Risk Detection, and Profits

 

The best (and most efficient) customer service stems from leveraging all Amazon Connect features. How well your business performs in today’s competitive business environment depends on providing a stellar customer experience, and the bar seems to rise daily. 

Statistics bear this out–80% of customers will pay more if they receive excellent customer service. Also, 89% of companies with notably superior customer service are rewarded with a boost in financial performance. Conversely, companies lose an estimated $136.8 billion annually through avoidable customer losses. 

Contact Lens for Amazon Connect empowers you with the real-time conversational analytics and quality management you need. Via machine learning (ML)-based customer insights, agents can connect all the necessary dots to provide the best possible customer experience. In this article, you’ll learn about the ML-enabled features in Contact Lens, and how they can improve agent productivity and customer satisfaction. Let’s begin.

What is Machine Learning?

ML is a type of artificial intelligence (AI) that enables applications to become “smarter” over time through algorithms powered by historical data. As time goes on, applications get better at predicting outcomes. This gives your business immediate, real-time insights and a view into customer behavior trends, company operational patterns, and potential new product ideas. It’s also valuable in fraud detection. 

The ML-Enabled Features in Amazon Connect

Contact Lens provides ML-powered contact center analytics in Amazon Connect. Call center supervisors and quality assurance managers can uncover and understand customer sentiment and trends as well as compliance risks in customer conversations. This information can be used for agent training–successful interactions can be replicated–and your company gets valuable customer feedback.

How it works

Your organization has millions of hours of call recordings. ML ferrets out the most valuable insights into brand perception and customer satisfaction. These call recordings are then converted to text for additional analysis.

These analytics enable a better understanding of agent effectiveness, discovery of emerging trends, and whether agents adhere to company guidelines and regulatory requirements. ML-powered Contact Lens takes what was an expensive, slow process and makes it an out-of-the-box experience within Amazon Connect.

Contact Lens automatically:

  • Transcribes voice conversations
  • Enables search
  • Redacts personal identifiable information
  • Extracts customer sentiment
  • Pulls out agent sentiment

Additionally, it detects customer issues, interruptions, and non-talk time. You also can categorize customer conversations based on your own specified criteria. And all of this takes just a few clicks. 

Build a Healthier Business With Real Time, ML-Generated Information

Through the use of ML analytics, you can improve both agent performance and overall customer service levels in real-time. That means you can take immediate action on identified issues, uncover trends impeding agent performance and productivity, analyze customer sentiment, and gain valuable insights from conversations. 

The key here is real-time. With its enormous financial cost and reputational damage, a poor customer service experience is nothing to shrug off. But Contact Lens can help out here as well. Using automated contact categorization, you can create Amazon Connect Tasks to help you deliver on customer follow-up promises such as callbacks and refunds. A prompt follow-up call can turn a sour experience into a sweet one for a disgruntled customer. 

Real-time capabilities allow supervisors are immediately alerted to issues during live calls and can use a fast-text search on call transcripts to highlight recurring issues so they can be solved. The ML features of Contact Lens give you a better understanding of both your customers and agents. Agents get the retraining they need, agent onboarding is improved, and customers receive a higher level of care.

ML-Powered Contact Lens Has All The Tools You Need

In concert with natural language processing and speech-to-text analytics, ML makes customer sentiment analysis easy. Just a few clicks reveal dissected call transcripts, conversational characteristics, and sentiments, as well as issues and trends that inform agent coaching. Other tools include:

  • Simple conversational search. You can use keywords, customer and agent sentiment scores, and non-talk time to identify the calls that offer the best insight into the customer experience.
  • Real-time alerts. The value of alerts in real-time can’t be overstated. You can create rules that tag customer experience issues when they match keywords and phrases. Supervisors then are alerted to assist an agent on a live call. Assistance can be provided via chat, or the agent can be asked to transfer the call. 
  • Instant transcripts for call transfers. There’s almost nothing more irritating to your customers than having to repeat the same information repeatedly to different agents. This feature means a transferred call is passed to another agent with a real-time transcript and conversational details. Not only do customers not have to repeat their information, but they also aren’t put on hold while the new agent searches for their information. 
  • Redacted data control. Privacy is a huge issue for today’s online buyer. You control this access by enabling user-defined permission groups. Contact Lens finds and automatically redacts sensitive information from recordings and transcripts to protect customer privacy. 
  • Categorization powered by ML. ML makes it easy to track conversations for company policy and regulatory adherence–not just by spoken phrases but also by intent and context. Supervisors can use category labels to set up scorecards that evaluate compliance.
  • Contact trace records. Supervisors can see the details of any customer interaction using the Lens dashboard’s Contact Search page. These include ID, queue name, phone number, agent name, and call recording. Supervisors can listen to the call and view a video illustration of the interaction to identify interruptions, sentiment, and non-talk time. 

These tools give contact center managers actionable insights they can’t get by sporadically listening to calls. ML-powered Contact Lens gives supervisors everything they need to improve agent skills to provide an industry-leading customer experience that powers business success. But the ML features in Amazon Web Services don’t stop there. For every $1 of fraud, the cost to the business is $3.75. There’s a solution for that, too.

Fraud Risk Detection

With Amazon Fraud Detector, a complement to Amazon Connect powered by ML, you can use your historical data, in conjunction with Amazon’s own experience, to create your own fraud detection model. Building your model requires no ML experience, and you can start immediately detecting fraud by:

  • Identifying suspicious online transactions before you process the payment and fulfill the order.
  • Detecting fraud in new accounts. You’ll be able to identify high-risk account registrations and perform additional verification checks.
  • Preventing abuse of trial and loyalty programs. Minimize your risk by finding accounts likely to abuse your online services, and then set offer value limits.
  • Detecting account takeovers. Embed real-time account login flow that detects compromised accounts and minimizes friction for legitimate users.

With ML, the fraud risk detection model you create continuously learns, distinguishing between your trusted customers’ repeat transactions and continuous fraud attempts. You also get insights into your model’s performance, create rules based on your model’s predictions, and use the Amazon Fraud Detector API for real-time fraud predictions and to evaluate online activities as they happen. 

The real-time insights from ML provided by Contact Lens for Amazon Connect and Amazon Fraud Detector can improve business processes, boost agent performance, create happy customers, prevent loss, and increase profits. 

CloudHesive is a cloud solutions consulting and managed service provider with expertise in all things Amazon Web Services. We have the knowledge and experience to help your business realize all the benefits of AWS cloud, AWS customer service solutions, and Amazon Risk Detection. We have eight AWS Competencies, over 50 AWS Certifications, and membership in nine Partner Programs.

With more than 30 years of experience, we leverage cloud-based technology to its full potential. We’ve helped more than 100 companies reduce their operating costs and increase productivity with our focus on security, reliability, availability, and scalability. Contact the CloudHesive team today.