Analytics Engines continuously analyse Agent data and lay down Perceptual Quality results for (near) real-time and historical viewing. Quantification of Perceptual Quality and identification of sources of Perceptual Quality impairment are done entirely automatically (i.e. ‘Auto-Prof’).
We understand that there are many stakeholders in customer service and user experience, so we have constructed the Perceptual Quality (PQ) Dashboard to be easy to use by anyone that needs to understand the Perceptual Quality of users or customers. They can:
- Rapidly construct PQ Views tailored to their roles (sales, customer service, operations, engineering, executives, grass-roots)
- Zoom in and out to see the application-specific Perceptual Quality for individual users, individual locations, groups of users or locations, countries, territories or globally (there is a great deal of flexibility here)
- Monitor five continuously updated Dashboard Views at any one time (an unlimited number can be saved and restored to the Dashboard as required)
- Instantly compare long-term, short-term and near real-time Perceptual Quality for each View
- Set alerting thresholds for each View
From the Agent Explorer, Analytics for individual Agents can be viewed in more detail:
- Understand what the Perceptual Quality would be if everything was working perfectly (Max PQ), i.e. if there were no impairments anywhere in the compute and network infrastructure
- Compare Max PQ with actual experience (Mean PQ) to see where improvements should be made
- Understand where in the IT supply-chain impairment to human experience is coming from, i.e. LAN vs MSP vs Internet vs Data Centre vs Server (engineering detail in Diagnosis Explorer)
From any tailored PQ View, Analytics can be explored for each Agent that contributes measurements to your View. For each Agent:
- Incredibly informative 24 hour clock shows 30 days of Perceptual Quality history, revealing the true picture of service quality
- Understand what reduces the experience for this Agent, i.e. LAN vs MSP vs Internet vs Data Centre vs Server
- Watch results update in near real-time
From any tailored PQ View, Perceptual Quality history can be explored in detail:
- Select graph styles
- Granularity, start time, length of history
- Filter by work, play or sleep periods
- Compare history against other PQ Views
For roles with responsibility to improve performance, sources of Perceptual Quality impairment can be listed for any, specific tailored PQ View, can be explored:
- Impairment sources listed in order of dominance
- Sources contribution to impairment trend over time
- Specific behaviour of source that contributes to impairment to Perceptual Quality
