Artificial intelligence (AI) delivers powerful insights to organizations in many ways. One of the most critical applications is the ability to label data and decipher unstructured data like text and images.
Conversational data represents untapped potential for many businesses. This data unlocks content and its context, and savvy businesses can act on this intelligence and improve customer experiences (CX). The aspect of AI at work is natural language processing (NLP), and the UiPath Automation Suite has these capabilities with the Re:infer tool kit.
One of the key processes required to gain this understanding and insight is communication mining. Let’s look at how it works and the value it can deliver to your company.
What Is Communication Mining, and Why Does It Matter?
Communication mining is an application of conversational data intelligence. It focuses on understanding and extracting value from your communication processes. This form of mining converts unstructured data in these channels to structured, machine-readable data, leveraging machine learning and NLP. When this process is in place, your organization can have complete visibility into all communication data.
Mining communications from customer interactions provides vital insights into how they feel about your brand, products, and service. If you can understand these expectations, you’re more likely to retain them long-term. In fact, 66 percent of customers expect companies to understand their needs. If they don’t feel understood, they are likely to leave.
Today’s buyers aren’t as forgiving as they once were. A survey showed that 49 percent of consumers left a brand in 2021 due to poor experiences. How many chances does a brand get? The report also found that 86 percent of people drop a company after only two negative experiences.
You no longer have to guess what matters to customers, and you can use what you learn to drive improvements. You can uncover the intent and sentiment of customer feedback at scale across the user journey.
Communication mining usable in contact center automation, case management, or other query-based work. AI automatically categorizes, prioritizes, extracts, and transmits incoming messages. With automation, your employees can focus on more critical tasks and eliminate much of the repetitive work.
So how does Re:infer enable communication mining?
What is Re:infer, and What Automation Problems Does It Solve?
Re:infer is a no-code technology developed at MIT. Businesses deploy it to analyze multiple communication channels, including shared inboxes, chat rooms, and other customer feedback vehicles. With these insights, you can deliver the customer experience your audience expects. A clear understanding of the intent of the feedback is the difference maker that Re:infer provides.
The problem Re:infer aims to solve around unstructured data and gleaning intelligence from it is complex. Unstructured data accounts for as much as 90 percent of the total data generated by an organization. Formats include text to images, server logs, and customer support emails.
You can derive many insights by tapping into this data and transforming it into structured data. For example, you can gauge overall customer satisfaction by product or service. This valuable information can impact product roadmaps, marketing, sales, and customer service. Without the help of AI technology, the process of interpreting and making use of this unstructured data would be completely manual.
The Re:infer tool mines context from communication and turns it into actionable data with robotic process automation (RPA) workflows. Users have a low-code interface to label data more effectively and efficiently.
How Re:infer Improves Customer Experience with Communications Mining
With optimized data models that are easy to train and deploy, you can realize benefits around enhanced CX and operational stability. The NLP low-code software includes customizable dashboards to monitor and analyze business communications data and workflows. It does so at a granular level for each message. This feature allows you to review historical and real-time reporting to track communications trends.
The technology also helps identify events within ERP application system logs and label them for process mining. As a result, you can run process intelligence in new areas to tap into the communications between agents and customers.
Re:infer, as part of the UiPath Automation Suite, strategically and tactically supports automation evolving to be more intelligent. Advanced data labeling and context recognition for unstructured data can be a game changer across the enterprise, welcoming the voice of the customer into all areas.
Want to learn more about the UiPath Automation Suite and Re:infer tools? Contact us today to get started.
