Get to grips with the basics of interaction analytics in this introductory guide
Every customer interaction is an opportunity. But nowadays, it’s not only about selling more, selling up, or solving a customer issue. It’s all that, of course. And it’s much more.
It’s also the story behind the interaction. It’s the story buried in your data.
Modern contact centers offer up a treasure trove of data that could lead to untapped revenue and increased efficiencies.
Capture it. Measure it. Put it in context. With interaction analytics, businesses can shape an in-depth picture of their customers: a picture that presents meaning.
Moreover, companies can delve deeper into the motivation and feelings of their customer. With meaningful data in hand – in real-time – the call center team can accelerate transactions, suggest new products, and build stronger brand loyalty while delivering personalized solutions.
Indeed, interaction analytics tools have become a strategic, revenue-generation tool to get more efficiency out of the call center. Companies that fail to recognize and harness their potential will miss valuable opportunities.
Interaction analytics transforms raw customer data collected across multi-channel customer interactions into structured data.
To do so, the solution analyzes, filters, searches, and archives the data to offer insights into the customer – their personality, product and service needs, and brand expectations.
Indeed, with interaction analytics, businesses can evaluate multi-channel interaction data and explore specific aspects of the customer experience.
The benefits of interaction analytics include:
Interaction analytics has gained significant traction in today’s omnichannel world. In fact, the global speech analytics market alone is forecasted to be worth $5.04BN by 2026.
First, consider a contact center’s channel mix. These provide the data source.
Across voice, there is a machine learning and NLP-powered speech-to-text element, which transcribes the conversation. From there, an analysis engine – driven by NLU and other AI – looks for trends, as it does on written channels.
However, interaction analytics not only transcribes and transforms voice, but it also picks up on stress levels within the customer’s voice to add further insight and enable sentiment analysis.
In addition to connecting and transforming conversational data, interaction analytics tools offer a BI dashboard to capture, process, and highlight critical insights.
Finally, further AI tools will help make predictions and recommend future actions based on conversational data, transforming it into powerful visuals.
Interaction analytics can significantly improve contact center performance and reveal hidden efficiencies and opportunities such as:
Indeed, interaction analytics opens tremendous possibilities – whether trying to improve internal performance or analyzing CX characteristics to make better business decisions.
Yet, this is only scratching the surface. Check out the interview below, where we discuss even more use cases with the prominent interaction analytics provider Contexta360.
In recent years, the most prominent CCaaS players have added interaction analytics capabilities to their solutions. As such, vendors such as NICE, Genesys, and Talkdesk will offer interaction analytics platforms, embedding the technology within various other elements of their portfolios.
For instance, many quality management tools will now include interaction analytics to automate quality scoring. Some will even check for employee and customer sentiment.
However, as standalone solutions, some are better than others. As a result, many independent vendors are still out there, offering third-party integrations through the marketplace of many notable CCaaS providers. Some of the most notable include:
Want a deep dive into some of the most innovative interaction analytics providers? If so, check out our article: Top Speech Analytics Providers for 2022
