We built CUE to accomplish two important goals. First, CUE is a real-time reporting, data visualization, and analytics tool which allows unprecedented insight to how customers use self-service applications. At its core, CUE collects and aggregates data that describes what is happening at every turn. This data is published to a secure web dashboard and native iOS application, providing immediate visibility to what is going on right now and what trends are emerging over time. By making applications less complex and surfacing only those data streams that are relevant for a specific user, CUE can be used by a wide range of stakeholders—customer experience managers, IT teams, designers, developers, and project managers—to make better-informed decisions in a more timely manner and adjust strategy more quickly when needed.
CUE is also a next generation application development framework designed to facilitate proactive, personalized service in one integrated solution, regardless of the communications platform(s) our customers choose. Over time, CUE-enabled applications grow smarter and can be optionally configured to tap into contextual recommendations proactively and automatically served by the CUE API.
No Channel Left Behind
While technology promises to simplify everyday life, today, when it comes to customer service, consumers have an ever-expanding and at times confusing range of options to choose from when they need to connect with their service providers. They might ask:
"Can I just get my answer on Slack? Where would I even start?"
"I wonder if Alexa can help? Or Siri?"
"Did I download an app for that? Where did I put it?"
"Maybe I can just Google my question and see what I find?"
Each of these channels are competing for attention and company resources and it can often be messy and a real challenge to manage experience across and between them in a consistent, channel-appropriate manner.
CUE Analytics is modular and extensible so that our customers can tackle this challenge head-on. CUE supports data sourced from multiple application types, interaction models, and data streams associated with different channels. By centralizing data about these interactions, work flows can be completed more quickly and more intelligently.