Omnichannel conversational analytics is a tool of business intelligence that automatically captures, transcribes, and analyzes conversations to extract insight. Using natural language processing (NLP), artificial intelligence (AI), and machine learning (ML), conversation analytics determines the meaning and intent of a person’s written or spoken words and the emotion and sentiment behind the communication. Omnichannel analytics can glean intelligence from conversations on any audio or text-based channel – phone, email, web, chat, SMS text, social, and more. By analyzing 100% of conversations with customers, employees, patients, and other audiences, omnichannel conversational analytics provides businesses with insight that can drive business improvement, enhance customer experiences, ensure compliance, and accelerate product innovation.
What is omnichannel conversational analytics vs. speech and text analytics?
Speech analytics captures and analyzes spoken conversations, such as calls to a contact center or voice commands to a digital assistant. Text analytics captures and analyzes written conversations like those in email or social media. Because these technologies focus only on one type of communication – written or spoken language – they can’t provide as comprehensive a view into the customer mindset as omnichannel analytics does.
How does omnichannel conversational analytics work?
Omnichannel conversational analytics relies on several conversational intelligence technologies to transform unstructured information in written and spoken conversations into structured, machine-readable data that can be easily searched and analyzed to identify trends and opportunities. Omnichannel conversational analytics uses NLP, AI, and ML-powered technologies to transcribe written and spoken communication and determine the meaning and intent of the language. Acoustic technology measures characteristics like tempo, agitation, and silence to identify the emotion and sentiment within the language. Algorithms applied to conversational data reveal patterns, produce insight, and make predictions about customers’ wants, needs, behavior, and expectations.
What are the benefits of omnichannel conversational analytics?
Omnichannel conversational analytics enable businesses to:
- See the entire customer journey. Omnichannel analytics delivers intelligence about every touchpoint on every channel, allowing businesses to take steps to improve customer experiences throughout their entire journey. Omnichannel analytics also provides contact center agents with a complete picture of each customer’s interactions with the business.
- Make better data-driven decisions. Because omnichannel analytics captures 100% of customer conversations, it produces more accurate and comprehensive insight. As a result, leaders throughout a business have better data on which to make decisions.
- Automate collection of customer feedback. Focus groups, manual call reviews, and other traditional methods for gathering customer feedback are time-intensive and error-prone processes. By automating tasks, omnichannel conversational analytics eliminates an enormous burden from marketing, product, sales, and customer experience teams.
- Gain insight into the customer mindset. Omnichannel analytics provides a clear picture of what the customers want and how they feel about a business and its competitors, providing intelligence that companies can use to identify new opportunities and build competitive advantage.
What are use cases for omnichannel conversational analytics?
Omnichannel conversational analytics have a broad range of uses across many departments.
- Customer experience teams rely on omnichannel conversational analytics to personalize experiences with a deeper understanding of what does and doesn’t resonate with customers.
- Product teams use omnichannel analytics to gather feedback about customers’ product experiences that can ultimately enhance product development, accelerate product innovation, increase quality control, and achieve competitive differentiation.
- Contact centers use conversational analytics in conversation intelligence platforms to improve the outcomes of customer interactions with insight into the root cause of customer issues and how they can be swiftly resolved. Real-time conversation analytics provides agents with alerts and next-best-action guidance to resolve calls positively and to turn around potentially negative interactions.
- Finance departments leverage omnichannel conversational analytics to identify friction in the payment process and take action that makes it easier for customers to complete payments.
- Compliance teams use omnichannel conversational analytics to monitor every conversation for compliance with regulations and internal standards, ensuring that agents use required language and avoid sharing sensitive data or personally identifiable information (PII).
