Interaction analytics

NICE Interaction Analytics makes it possible for businesses to better understand their customers, why they are contacting the company, as well as 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.

Using NICE’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 uncovers product, process or skill issues that were previously unknown.

Native to the CXone Mpower unified platform, Interaction Analytics helps drive CX improvement across every customer touchpoint while 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 holistic view of the customer journey.

NICE Interaction Analytics applies the power of data analysis across 100% of customer interactions from voice to text to digital, including social. Today’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), Large Language Models (LLMs), transcription, sentiment analysis, and industry-specific purpose-built AI models to every customer interaction across any channel of preference.

Interaction Analytics captures all the data most relevant to creating optimal customer experiences by measuring agent performance, customer sentiment, and monitoring the entire customer journey.

Interaction Analytics is infused with NICE’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.

Users can filter, analyze, and correlate data by metrics including everything from timeline (day/time of interaction); agent team; likelihood to buy, sentiment, and more. Some of the pre-built Interaction Analytics metrics include the following:

• First Contact Resolution assesses whether 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.
• Frustration gauges if the customer expressed frustration through specific phrases and keywords.
• Silence measures the duration of non-engagement between the customer and the agent.
• Sentiment evaluates how positive or negative an interaction was, for both the agent and the customer.

Finally, AutoDiscovery—a feature within Interaction Analytics Advanced—provides another way to view metrics, by identifying and categorizing clusters of unknown topics and displaying their relationship within a given set of interactions.

Interaction Analytics offers a unified view of your CX data, in a customizable user-friendly dashboard. Users can 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, and more.

CXone Mpower Interaction Analytics Advanced users can also use Topic AI to analyze and filter by intents, events, and outcomes, and then correlate those results with CSAT, handle time, or specific behaviors.

These 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, with the flexibility to fine-tune it to suit your specific business needs.

Combining the latest generative AI LLM (Large Language Models) technologies with industry-specific proprietary models, Interaction Analytics makes it possible to analyze more data at scale and provide richer analysis of the overall customer experience.

Topic AI consists of 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, events and outcomes and then categorize the data into topics. These models can be customized to align with a contact center’s process or terminology with easy-to-use visual tools. Using gen AI that automatically categorizes interactions provides higher quality and faster time to insights for CX and reduces what was previously a manual effort.

Interaction Analytics uncovers valuable insights that help organizations upskill agents. When powered by Enlighten AI for CSAT or Sales Effectiveness and used as part of an automated quality program, it enables agents to enhance their performance through personalized feedback and coaching.

User-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.

With 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.

Key features include:

• Tracking key metrics across voice and digital channels for an omnichannel perspective of your operations.
• Providing real-time information and analysis for a quick response to CX needs or issues.
• Analyzing historical data for early insights into performance trends.
• Addressing complex business challenges with interactive drill-downs for a root-cause analysis.

There are two versions of Interaction Analytics.

CXone Mpower Interactions Analytics and CXone Mpower IA Advanced.

CXone Mpower Interaction Analytics provides continuous insights into the content of interactions using out-of-the box entity detection and topic classification as well as the ability to score interactions on array of meaningful outcomes like sentiment, frustration and resolution.

CXone Mpower Interaction Analytics Advanced includes additional features: AutoDiscovery and the ability to analyze and customize data using Topic AI Editor. You can optionally level up and add Enlighten AI for Customer Satisfaction and Sales Effectiveness.