Learn everything about conversation analytics – definition, significance, benefits, and applications – and level up your overall support strategy.
Conversation analytics is the process of assessing customers’ conversations to gather insights about their behavior. The aim is to leverage this gathered customer intelligence to personalize future conversations, improving both customer satisfaction and engagement. From a contact center’s perspective, using conversation analytics is the best way to collect unsolicited feedback about your business — by allowing you to read and analyze your customers’ intent, emotions, and actions.
Conversation analytics does more than scrutinize phone calls, emails, texts, and other customer content. It analyzes two-way casual communication between your customer and agent, accounting for subjective factors — like socio-linguistic diversity, colloquial language, and context — to give you an accurate picture of the conversation in real time.
Artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) algorithms help to analyze conversational data from the many channels that your customers use to reach you — including voice calls, SMS, email, live chat, and social media. Then they assimilate all that data to find hidden patterns that can help you better understand and predict customer behavior.
NLP and ML help transcribe customer conversations into machine-friendly language. AI algorithms then assimilate that data, unlocking patterns unique to each customer, and convert them into actionable insights for your customer-facing teams.
Modern customers are more discerning than ever. They expect proactive, personalized interactions with businesses of all types and sizes. They also reveal their perspectives, preferences, and intentions while interacting with customer support agents and chatbots.
Even when they know they are interacting with a bot or automated engagement platform, 74% of users expect to be treated like a human — not just another ticket number.
To understand each customer’s unique needs, motivations, and behavioral patterns, businesses need to analyze each customer’s journey from end to end. That’s where conversation analytics plays a crucial role.
There are four main advantages of using conversation analysis for your business. They are:
Conversation analytics eliminates the need to extract data using manual processes and tools (like surveys) that are not only time consuming, but also prone to errors and inaccuracies. With an analytics solution like this, you can collect data while simultaneously having a customer service conversation, without disrupting the customer’s user experience or wasting time.
Evaluating customer conversations as they occur helps you unlock their behavioral patterns in real time. This provides agents with a 360° view of each customer, including their historical data, journey insights, and notable trends. Agents can then use these insights to tailor their conversations and enhance the customer experience.
When you directly solicit feedback from customers, there’s a good chance that it will be skewed, since people are not always objective or transparent with self-reported evaluations.
Conversation analytics solutions, on the other hand, rely on technologies (like NLP) that are data-driven and objective. And they leverage AI and ML technologies, which minimize human error in data capturing and analysis, because they are programmed to scrutinize and organize data according to certain predefined requirements. The end result is highly precise and accurate data analysis.
AI-powered conversation analytics allows anyone and everyone to gather, extract, and understand data while also breaking down barriers around language, geography, and skill. Even if you aren’t fluent with conversation analytics tools, you can interact with data and interpret it, no matter what language you speak or where you are located.
Conversation analytics helps you read between the lines of customer interactions and uncover hidden insights. You can use this data to identify inefficacies, improve metrics and KPIs, and drive more revenue.
Here’s how you can harness the power of conversational intelligence for your business.
Conversation analytics captures your customers’ end-to-end interactions with your company, treating all the parts as a single seamless experience. And it empowers your support agents with important information about each customer before they even start a conversation. Using conversation analytics, your agent will know what channel a customer prefers, which campaign or content drove the conversation, how to best support the customer, what each customer needs from your product or services, and more.
If your analytics solution is powered by AI, you can even predict customer satisfaction scores with accuracy. When you understand how your customers are likely to respond to an action on your part, you’ll have better control over the conversation and its outcome.
With conversation analytics, you have visibility into the quality of customer interactions for each agent and case — making it easy to identify red flags such as missed SLAs, interactions with low predicted CSAT scores, and low agent productivity.
By spotting areas of improvement in need of attention, you can build a customized training program for each agent. And you can equip them with AI-powered knowledge base recommendations, brand-compliant responses, and escalation alerts to keep them at the top of their game.
Communication between customer service agents becomes smoother when everyone has the same comprehensive customer view. Using the same platform, and sharing ownership of tickets, facilitates easy team collaboration. By providing full, shared context with interaction-specific collaboration history through call recordings and call tracking, you ensure that your contact center agents can always pick up wherever the conversation left off.
Conversation analytics gives insights into the top reasons your customers are contacting you — by identifying their intent. You can then utilize AI to direct customers to the agents who have the right skill set and expertise for the case, reducing the likelihood of escalations and customer churn.
You can identify keyword topics, hidden friction points, and upsell opportunities by monitoring customer service interactions. Sharing that information with your product, marketing, or engineering teams will help them understand customer sentiment and learn what people like or dislike about your product or services — enabling them to improvise and optimize their blueprints, designs, and tactics.
Conversation analytics relies heavily on data accuracy and completeness. When your customer data is scattered and unstructured, it’s imperative that you use an integrated analytics solution to harmonize and streamline it all. That’s where Sprinklr comes in. As the world’s only unified customer experience management (Unified-CXM) platform, Sprinklr integrates 30+ traditional and digital channels and brings data from all channels under one roof. Sprinklr’s Modern Care solution offers many features and functionalities to enable conversation analytics, including:
Best-in-breed AI engine that provides a single source of truth for data analysts
AI-led Speech Analytics to detect customer emotions and sentiments from voice calls and then score each interaction against custom quality metrics
Contact Center Intelligence to monitor your agents’ performance and guide them toward success with performance analytics, AI-based scores, and automatic alerts in real time
Agent Desktop to unify your care strategy with out-of-the-box CRM integrations and robust APIs that provide agents with a consolidated picture of customer information
Live Chat to strengthen your care strategy and help customers address their issues by initiating conversations across your website, apps, and forums
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