What is customer interaction analytics?

Customer interaction analytics involves capturing and analyzing data collected from interactions with customers via channels like email, phone calls and social media. The technology helps you understand customers’ behavior, expectations and preferences and make data-driven decisions based on those insights.

Customer interaction analytics lets you detect common user problems and behavior trends, enhance customer satisfaction and improve agent performance. Therefore, the technology can transform customer service and quality management by boosting loyalty and reducing customer churn

The components of interaction analytics

Interaction analytics uses tools and techniques, such as conversational AI, emotion detection, keyword spotting, machine learning, natural language processing, predictive analytics, root cause analysis, sentiment analysis, speech analytics and recognition and voice analytics to understand customer behavior and experience. For example, sentiment analysis determines the emotional tone of customer interactions; root cause analysis identifies the cause of customer frustrations; and, speech analytics extracts actionable insight from unstructured data like call recordings.

These advanced technologies enable you to monitor interactions across all channels. Armed with this data, you can gain real-time insights into customers’ needs, pain points, preferences and feelings about your brand.

Interaction analytics can also unearth emerging trends and valuable patterns in customer behavior that allow you to go above and beyond what users expect. For example, you can solve challenges raised on phone calls by analyzing a customer’s tone, pitch and voice speed or immediately answer a customer’s query through instant messaging platforms by monitoring keywords.

Why do contact centers need interaction analytics?

One failed interaction can cause the happiest customers to suddenly switch allegiances to a competitor, making it increasingly crucial for brands to perfect every interaction. However, many companies struggle to manage the mass of customer interaction analytics data they generate from conversations across multiple channels.

To solve this challenge, forward-thinking contact centers are turning to artificial intelligence. New technology like analytics powered by conversational AI is transforming customer experience and becoming a critical tool for organizations to master every user interaction.

Benefits of customer interaction analytics

Deploying customer interaction analytics across your contact center enables you to better understand your users and what they expect from your brand. A few examples of how customer interaction analytics drive contact centers include:

Improved understanding of customer needs and preferences

Interaction analytics technologies enable you to understand the products and services your customers want. They can also help you identify how and when customers want to be contacted and the approaches that encourage them to engage with your brand.

Enhanced personalization and targeting of customer interactions

Understanding customer preferences also allows you to develop a more personalized approach whenever you interact with them.

Increased customer satisfaction and loyalty

Getting customer interactions right every time ensures happy customers who are likely to continue shopping with your brand. Analyzing the nuances of every interaction helps you develop strategies that encourage loyalty.

Optimized operational efficiency and reduced costs

Historically, contact center agents had to spend hours trawling through calls to capture the key points discussed and track any agreed-upon actions. This was frustrating for agents and it cost companies huge amounts of time and money, as their prized assets were hindered by low-value administrative work. However, customer interaction analytics does the hard work for agents, enabling them to spend more time on the phone with customers and doing work that contributes greater business value.

Informed decision-making based on actionable insights

Customer interaction analytics technologies pool vast amounts of data from across your contact center. Making sense of this information manually would be almost impossible. However, the technology can analyze the information and provide immediate insights and actions that help you transform your CX approach.

Early identification and resolution of customer issues

Interaction analytics tools help you spot potential problems that customers are facing. You can then use automation to immediately remediate any issues or advise agents on how to address problems with callers.

Mitigating compliance and risk

Customer interaction analytics is critical to minimizing risks and managing regulatory compliance. It can help you detect potentially fraudulent activity, flag deviations from compliance policies and ensure sensitive data is automatically stored securely to prevent legal risks. Furthermore, a CX approach backed by analytics can help you swiftly resolve customer complaints, disputes or misunderstandings.

Important customer interaction analytics metrics to track

Customer interaction analytics can be deployed against various metrics that help monitor the performance of your contact center. For call centers navigating a customer experience transformation, the technology can help analyze key factors that impact critical metrics like:

First Contact Resolution (FCR)

FCR monitors the number of customer issues resolved at the first attempt to contact you. For example, an agent could resolve a user’s problem with one phone call, web chat or email response.

Average Handle Time (AHT)

AHT tracks the average time it takes to resolve a customer issue. This includes the time the agent spends interacting with the customer and the follow-up work required.

Customer Satisfaction Score (CSAT)

CSAT monitors how happy your customers are at every stage of the customer journey. However, surveys are typically only completed by very happy or very angry customers, which can lead to results that do not represent the feelings of your entire user base.

Customer Effort Score (CES)

CES measures the time and effort customers must make to resolve a problem. A good CES score suggests your brand has good CX performance and a simple customer journey.

Sentiment analysis outcomes

Measuring sentiment analysis tracks how customers’ positive or negative perception of your brand changes over time

Call abandonment rates

Customers abandoning calls is a telltale sign of a poor CX process. The call abandonment rate tracks how many customers give up on contacting your brand, which may indicate a heightening turnover risk.

Social media share of voice

Also known as social media mentions, this metric tracks how frequently your brand is mentioned on social channels. It can also monitor whether mentions are made in relation to competitors and measure brand awareness and customer sentiment.

9 best practices for using interaction analytics to your advantage

Customer interaction analytics can help brands transform their CX journeys and enhance customer loyalty. However, reaping the benefits relies on doing the groundwork and developing a solid strategy. Essential capabilities you need for interaction analytics include:

Define specific analytics goals

The first step to reaping the benefits of customer interaction analytics is to define the goals you want the technology to address. Assess your specific CX challenges and use existing customer feedback to shape your objectives.

Prioritize data quality and integration

Customer interaction analytics can generate vast volumes of information, so it’s vital to work only with high-quality data. Prioritizing data quality and integrating all customer channels into the tool before deployment will ensure the best future results.

Utilize advanced analytical tools

Advanced analytical tools, such as conversational AI, emotion detection, keyword spotting, machine learning, natural language processing, sentiment analysis and speech recognition, will help you yield the best insights from the data you generate. Using these tools will help you resolve issues immediately, gain real-time insights into user challenges, boost customer satisfaction and help agents work as effectively as possible.

Act on actionable insights

It’s no use simply collecting the data that customer interaction analytics can generate. You must be able to act on that data. Using tools to analyze the information and discover key trends can help you gain actionable insights you can apply throughout the customer experience

Empower frontline employees with insights

Armed with data-driven actionable insights, you can empower your contact center agents to solve customers’ biggest challenges quicker than ever. Using a unified AI and data platform that combines conversational AI, generative AI and emotion AI can help call agents understand what customers need and resolve their queries the first time, every time

Uphold strict data privacy standards

Strict data privacy standards are critical when dealing with vast quantities of data. You must implement robust strategies and processes to capture real-time customer interactions and ensure the data is securely stored and easily accessible. Strict data governance policies and protocols ensure you comply with the requirements set out by increasingly stringent federal, industry and international data regulations.

Cultivate a continuous improvement mindset

Another vital consideration is to never stand still and to continually improve your CX processes. A continuous improvement mindset involves assessing your approach to identify when changes occur, assess the potential effects and capitalize on them. Monitoring your customer interaction analytics solution can identify opportunities for improvement and new approaches to elevate your CX experience.

Prioritize agent training and performance

Customer interaction analytics allow you to constantly monitor agents’ conversations with customers. You can then identify each agent’s areas for improvement and tailor programs that help them develop specific skills. As a result, agents should be more productive, perform to a higher standard, resolve interactions more quickly and take greater enjoyment in their work.

Target cross-selling and upselling

Supplying agents with data-driven real-time insight enhances their ability to cross-sell and upsell to customers. Customer interaction analytics allow you to understand customer needs, allowing agents to point them toward products and services that would solve their issues. Additionally, analyzing this data can identify opportunities to develop new offerings tailored to customers’ requirements.

Amplify engagement and gain deeper insights with Uniphore

Uniphore’s robust AI-powered analytics solution enables you to monitor, analyze and understand every interaction your agents have with customers. Our technology provides an integrated view of customers across every channel, including chat, email and voice. This helps you to understand the emotion, intent and sentiment driving every conversation and resolve customer challenges as quickly as possible.

Uniphore’s technology helps you better understand your customers’ needs and enables contact centers to have more impactful conversations. Our technology ensures your agents always communicate with customers through their preferred channel, recognize their frustrations in real time and respond in a manner that keeps them engaged and eager to do business with your brand.

Discover how to transform your contact center performance with our powerful speech analytics software.