UX Awards

The Premier Awards for Exceptional Digital Experience

Sonar Insights: Designing an Interface with Unprecedented Visibility Details


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Empowering support specialists to proactively prevent Wi-Fi connectivity issues before they occur

Sonar Insights is one of the Artificial Intelligence (AI) products that enterprise companies and Internet Service Providers (ISPs) use to diagnose Wi-Fi connectivity issues. Their product’s initial UI was visually overwhelming and counterintuitive, displaying unprocessed data with virtually no hierarchy. Sonar Insights needed an interface with a consistent, natural User Experience (UX) to aid a variety of audiences responsible for resolving connectivity issues. It also had to integrate with the various systems ISPs use to monitor, track and remediate issues reported by end-users.

Armed with insights from several interviews with ISPs and support specialists, we mapped out user roles, user flows and customer journeys. We learned which tasks users had to complete and what information was crucial at each stage of the journey. From there, we paired contextually relevant information (graphs, charts and visualizations) with specific user roles and their objectives. Then we developed information hierarchy which put the most important content front and center, with task-oriented navigation.

For the first time, ISPs and enterprise support agents could see what was happening with the end-user and act on it. ISP analysts could access aggregate, geo-specific usage stats, allowing them to identify patterns in Wi-Fi speeds, network outages and issue-resolution volume. It gave them a high-level overview of the network, but also allowed them to drill down and triage issues that could impact it as a whole. Additionally, support agents actively responding to support calls could view historical data (last speed test, tech connected to the internet) and real-time contextual information (type of router, whether they were at home or work) by entering a unique ID associated with the caller requesting support. The final interface enabled Sonar Insights to do what they promised: solve connectivity issues before a user contacts the help desk, or reduce support resolution time.

Why this project is worthy of a UX Award:

As the Internet of Things (IoT) becomes the Internet of Everything, solutions like Sonar Insights become critical to the businesses that deploy them. IoT products have the potential to transform business productivity and performance, but they can’t utilize its potential if the insights they extract, share and analyze do not improve subsequent interactions. UX is evolving from a focus on improving the presentation of information and navigation to designing frictionless experiences that improve with every use.

Sonar Insights is a game changer for both enterprise support and ISPs, replacing the self-reporting diagnostic phase required to identify connectivity issues. By giving enterprise support specialists unprecedented visibility into historical and predictive information about the end-user experience they are able to bypass the exhaustive questionnaire that has become the cornerstone of Wi-Fi/connectivity troubleshooting. As more users interact with support specialists armed with Sonar Insights, they are able to resolve connectivity issues faster and more precisely, improving future interactions.

Machine learning compiles different data points of user connectivity and network configuration. Each time a user reports a problem, a support specialist armed with dynamic learnings from the dashboard will be empowered to resolve connectivity issues and proactively prevent them from reoccurring. They are also able to greatly reduce the time required to repair those connectivity issues. For businesses that rely on remote workers, virtual meetings and ISPs (who receive the blame when there’s an issue even if they are not the source), Sonar Insights’ UI is poised to usher in a new era of enterprise productivity and customer satisfaction.

Submitted By: SocioFabrica

Client Name: Catalina Labs

4.6/5 (27)

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