Cutting-edge unsupervised machine learning powers fast time to insight and real-time action to provide a superior customer experience
HOBOKEN, N.J.--(BUSINESS WIRE)--NICE (Nasdaq: NICE) today announced that its analytics offering now includes cutting-edge AutoDiscovery capabilities. Leveraging AI-based unsupervised machine learning, these capabilities provide organizations with cross-channel insights on service anomalies and surfaces areas that are customer pain points. As a result, organizations can swiftly remedy issues as they emerge, improving customer experiences and loyalty.
Available as a cloud-based add-on module to version 12.2 of Nexidia Analytics, the innovative AutoDiscovery features bring to the forefront insights that are critically tied to the business and customer loyalty without time-consuming manual discovery and categorization processes. Ground-breaking unsupervised machine learning capabilities highlight phrases that indicate customer dissatisfaction via easy to visualize sentiment and volume indicators for each topic and phrase. AutoDiscovery automatically correlates topics and highlights trends in phrases and topics so that organizations can quickly, and with minimal effort, understand the full picture and take immediate corrective action to address anomalies and resolve issues. The result is improved customer experience.
NICE Nexidia’s AutoDiscovery capabilities deliver the following features to boost customer loyalty:
- Automatic Topic Identification suggests topics for a set of media based on all available data, without the need for human intervention. This ensures new, emerging and existing topics are consistently analyzed and always up-to-date Topics are automatically correlated and can be filtered by volume, sentiment, Average Handle Time, Non-talk Time, or Cross-talk Analysis, providing the ability to easily view topics by desired metrics and accelerating the time to insight.
- Anomaly Detection surfaces lower volume or newly trending issues that could be of great importance to the business but would otherwise not be detected due to their relatively small volumes. This helps businesses respond quickly to early warning signs of trending issues as well as unexpected anomalies.
- Query Coverage Analysis enables quick and easy identification of topics that are not currently covered by existing call topic query libraries. By discovering topic areas that should be included in the library, companies can continually gauge the robustness of their query library and use Automatic Topic Identification to update the library as needed.
The AutoDiscovery capabilities also empower managers and agents with timely and targeted feedback, aiding analytics-driven quality management programs in finding new coaching opportunities and calibrating performance metrics much faster than ever before.
“With NICE’s newly announced AutoDiscovery capabilities, organizations no longer need to look for the needle in a haystack of data when it comes to understanding how to best serve their customers”, Barry Cooper, President, NICE Enterprise Product Group, said. “Organizations can now rely on our analytics solutions to surface trending service areas and take quick action."
NICE (Nasdaq: NICE) is the world’s leading provider of both cloud and on-premises enterprise software solutions that empower organizations to make smarter decisions based on advanced analytics of structured and unstructured data. NICE helps organizations of all sizes deliver better customer service, ensure compliance, combat fraud and safeguard citizens. Over 25,000 organizations in more than 150 countries, including over 85 of the Fortune 100 companies, are using NICE solutions. www.nice.com.
Trademark Note: NICE and the NICE logo are trademarks or registered trademarks of NICE Ltd. All other marks are trademarks of their respective owners. For a full list of NICE’s marks, please see: www.nice.com/nice-trademarks.
This press release contains forward-looking statements as that term is defined in the Private Securities Litigation Reform Act of 1995. Such forward-looking statements, including the statements by Mr. Cooper, are based on the current beliefs, expectations and assumptions of the management of NICE Ltd. (the Company). In some cases, such forward-looking statements can be identified by terms such as believe, expect, may, will, intend, project, plan, estimate or similar words. Forward-looking statements are subject to a number of risks and uncertainties that could cause the actual results or performance of the Company to differ materially from those described herein, including but not limited to the impact of the global economic environment on the Company’s customer base (particularly financial services firms) potentially impacting our business and financial condition; competition; changes in technology and market requirements; decline in demand for the Company's products; inability to timely develop and introduce new technologies, products and applications; difficulties or delays in absorbing and integrating acquired operations, products, technologies and personnel; loss of market share; an inability to maintain certain marketing and distribution arrangements; and the effect of newly enacted or modified laws, regulation or standards on the Company and our products. For a more detailed description of the risk factors and uncertainties affecting the company, refer to the Company's reports filed from time to time with the Securities and Exchange Commission, including the Company’s Annual Report on Form 20-F. The forward-looking statements contained in this press release are made as of the date of this press release, and the Company undertakes no obligation to update or revise them, except as required by law.
Christopher Irwin-Dudek, 201-561-4442
Marty Cohen, +1 551 256 5354, ET
Yisca Erez +972 9 775 3798, CET