RingSense QM Report - Interaction Arrival AI Analytics
Provide QM Reporting on RS4RCX that provides details of incoming Interactions, compiled with API Data from RingCX on Abandoned Calls and marry the abandoned with Sentiment and the number of available agents in the timeline.
Useful information to have in the report based on Hourly (with a date/range selected), daily, weekly and monthly.
The number of interactions could show peaks and valleys, when abandoned interactions occurred, what the average sentiment was of the handled interactions at the time, average wait time, average handle time, number of agents logged in, number of agents available, number of agents busy and number of agent Ring No Answer (an agent refused to answer and was placed in RNA unavailable), and number of unavailable agents. It would be extremely useful to also pull in the callback in queue data from the RingCX APIs to show when callbacks were engaged as well. We want to highlight activity stress points for the queues, showing when activity versus staffing were off balance i.e. too may interactions for active agent. AI could then generate light forecasting for future staffing requirements.
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Dashboard will be controlled by Filter to include at least selectable date, team(s) and specific agents
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open the file to view the framework, each data point will provide click through to open the data being observed
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Contact Center focused dashboard in RS4RCX providing critical trending analysis using collected data points. Highlighting major aspects and components, CC managers will find most helpful in managing QM teams.
Interactions collecting data on Screen Recording, detailing voice and digital channels.
Coaching insights with trending. Sentiment broken out by Negative, Neutral and Positive with trending. Topics Causing Frustration.
Selectable scorecards review showing leaderboard along with Power Skills and Trackers data
RingSense Agent Assist showing usage by agents, top responses etc
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See attachment for more details