Contact center interaction analytics - Optimize Your CX

{"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"How does Interaction Analytics help businesses improve CX?","acceptedAnswer":{"@type":"Answer","text":"\u003cp\u003eNICE Interaction Analytics makes it possible for businesses to better understand their customers, why they are contacting you, and to identify business trends and make informed data-driven decisions. By analyzing data from every type of customer interaction, businesses can deliver consistently smooth and personalized customer experiences, increase customer satisfaction, enhance agent performance, and improve operational effectiveness.\u003c/p\u003e\n\u003cp\u003eUsing NICE\u0026rsquo;s proprietary, industry specific, purpose-built CX AI models and generative AI technology, Interaction Analytics measures and gathers insights on customer sentiment, identifies churn risk, and unknown product, process or skill issues that were otherwise previously unknown.\u003c/p\u003e\n\u003cp\u003eInteraction Analytics helps drive CX improvement across every customer touchpoint while also improving agent performance and reducing the cost to serve. The solution provides a single interface for organizing, analyzing, and operationalizing data from multiple interaction channels, creating a unified view of the customer journey.\u003c/p\u003e"}},{"@type":"Question","name":"What types of interactions will I be able to analyze?","acceptedAnswer":{"@type":"Answer","text":"\u003cp\u003eNICE Interaction Analytics applies the power of data analysis across every type of customer interaction from voice to text to digital, including social. Today\u0026rsquo;s customers expect to be able to engage with brands on any channel, at any time. Interaction analytics makes it possible to do this by applying advanced analysis such as automatic speech recognition (ASR), natural language processing (NLP), machine learning (ML), transcription, sentiment analysis, and industry-specific algorithms to every customer interaction across any channel of preference.\u003c/p\u003e"}},{"@type":"Question","name":"What are some of the metrics measured or analyzed in NICE Interaction Analytics?","acceptedAnswer":{"@type":"Answer","text":"\u003cp\u003eInteraction Analytics captures all of the data most relevant to creating optimal customer experiences by measuring agent performance, customer sentiment, and monitoring the entire customer journey.\u003c/p\u003e\n\u003cp\u003eInteraction Analytics infuses NICE\u0026rsquo;s purpose-built CX AI models, such as Enlighten AI for Customer Satisfaction, which analyzes agent soft skill behaviors proven to influence positive sentiment. The agent soft skills, such as showing empathy, acknowledging loyalty, demonstrating ownership, asking effective questions, and others can be aggregated by agent, team, location and correlated with other KPIs.\u003c/p\u003e\n\u003cp\u003eUsers can filter, analyze, and correlate data by metrics including everything from timeline (day/time of interaction); agent team; likelihood to buy, sentiment, etc. Some of the pre-built Interaction Analytics metrics include the following:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eFirst Call Resolution\u003c/em\u003e assesses whether or not the customer interaction was successful in providing a solution during the first customer contact, thereby reducing the need for repeat calls or further follow-up.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eFrustration \u003c/em\u003egauges if the customer expressed frustration through specific phrases and keywords.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eSilence\u003c/em\u003e measures the duration of non-engagement between the customer and the agent.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eSentiment \u003c/em\u003eevaluates how positive or negative an interaction was, for both the agent and the customer.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eFinally, AutoDiscovery, a feature within Interaction Analytics, provides another way to view metrics, by identifying and categorizing clusters of unknown topics and displaying their relationship within a given set of interactions.\u003c/p\u003e"}},{"@type":"Question","name":"How easy is it to view or manipulate CX data in Interaction Analytics?","acceptedAnswer":{"@type":"Answer","text":"\u003cp\u003eInteraction Analytics offers a unified view of your CX data, all in one customizable user-friendly dashboard. Users are able to apply various widgets and filters to access Interaction metrics and find relationships within the data. For example, the intent analysis widget allows users to view metrics associated with the intents of calls, such as Total Interactions, Average Duration, Average Silence, Total Interactions %, Positive Client Sentiment, Negative Client Sentiment, Outcomes, etc.\u003c/p\u003e\n\u003cp\u003eCXone IA Advanced users have the ability to also analyze and filter by Intents, Actions, and Outcomes, and then correlate those results with CSAT, handle time, or specific behaviors.\u003c/p\u003e\n\u003cp\u003eThese metrics can be highly relevant to your business and overall level of CX. For instance, certain types of interactions might naturally involve prolonged periods of silence, or specific language used in calls might be more indicative of successful resolutions than currently recognized. Consider the important metrics in your business and how these new metrics align or contrast with them. Best practice out-of-the-box templates can help you get started and it is possible to fine-tune it to suit your specific business needs.\u003c/p\u003e"}},{"@type":"Question","name":"How are AI/LLMs (large language models) used in Interaction Analytics?","acceptedAnswer":{"@type":"Answer","text":"\u003cp\u003eCombining the latest generative AI LLM (Large Language Models) technologies with industry-specific Enlighten models, Interaction Analytics makes it possible to analyze more data at scale and provide richer analysis of the overall customer experience.\u003c/p\u003e\n\u003cp\u003eEnlighten AI Intent and Activity Ontology Models are pre-built, out-of-the-box AI models, that are part of Interaction Analytics Advanced. They include thousands of models that analyze every interaction for intents, actions and outcomes and then categorize the data into topics. Models that automatically categorize interactions provide higher quality and faster time to insights for CX and reduce what was previously a manual effort.\u003c/p\u003e"}},{"@type":"Question","name":"What sort of reporting is available with NICE Interaction Analytics?","acceptedAnswer":{"@type":"Answer","text":"\u003cp\u003eUser-friendly visual reporting and role-based, customizable dashboards are available offering a unified view of key business metrics from executives to managers to front line agents. Easily configure analytics dashboard widgets and filters to gain continuous insights by individual interactions, specific dates, and/or time frames, or at the individual agent level.\u003c/p\u003e\n\u003cp\u003eWith an intuitive drag-and-drop interface, you can select from a wide range of metrics and attributes to display. These dashboards provide a comprehensive view of your contact center, enabling the right people to take timely action.\u003c/p\u003e\n\u003cp\u003eKey features include:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eTracking key metrics across voice and digital channels for an omnichannel perspective of your operations.\u003c/li\u003e\n \u003cli\u003eProviding real-time information and analysis for a quick response to CX needs or issues.\u003c/li\u003e\n \u003cli\u003eAnalyzing historical data for early insights into performance trends.\u003c/li\u003e\n \u003cli\u003eAddressing complex business challenges with interactive drill-downs for a root-cause analysis.\u003c/li\u003e\n\u003c/ul\u003e"}},{"@type":"Question","name":"How do I purchase Interaction Analytics?","acceptedAnswer":{"@type":"Answer","text":"\u003cp\u003eThere are two pricing tiers which to purchase Interaction Analytics.\u003c/p\u003e\n\u003cp\u003eCXone Interactions Analytics and CXone IA Advanced.\u003c/p\u003e\n\u003cp\u003eCXone Interactions Analytics provides continuous insights into the content of interactions using out-of-the box entity detection and topic classification; ability to score interactions on array of meaningful outcomes like sentiment, frustration and resolution.\u003c/p\u003e\n\u003cp\u003eCXone Interaction Analytics Advanced includes additional features: AutoDiscovery, and the ability to analyze data using Enlighten Intent and Activity models. You can optionally level up and add Enlighten AI models for Customer Satisfaction and Sales Effectiveness.\u003c/p\u003e\n\u003cp\u003eCXone Interaction Analytics can also be purchased as part of the CXone complete suite.\u003c/p\u003e\n\u003cp\u003eLimited time packages are also available, offering a substantial discount compared to when purchased by individual solution.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNICE\u0026rsquo;s Enlighten AI CSAT\u003c/em\u003e promotion includes:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eNICE\u0026rsquo;s Enlighten AI CSAT\u003c/em\u003e promotion includes:\u003c/li\u003e\n \u003cli\u003eInteraction Analytics (Advanced)\u003c/li\u003e\n \u003cli\u003eEnlighten AI for CSAT \u0026ldquo;Agent Behaviors\u0026rdquo;\u003c/li\u003e\n \u003cli\u003eReal-time Interaction Guidance\u003c/li\u003e\n \u003cli\u003eQuality Management (Premium)\u003c/li\u003e\n\u003c/ul\u003e"}}]}