What is an ‘Metric’ in OI?
Metrics in the Operative Intelligence platform (OI) refers to quantitative measures which can be used to compare performance or productivity. Depending on the data available for your organization, the metrics you can view include those generated by various sources:
OI machine learning algorithms. Example: Sentiment, Predicted Resolution, Predicted Satisfaction
Metrics provided in your contact data: Telephony systems (or CCaaS) or customer relationship management systems (CRMs). Example: Average handle time, Average interaction cost, Cycle time.
Customer surveys. Example: Survey Satisfaction, Survey Resolution, NPS.
We can combine these metrics with our interaction classification capability to provide you with powerful insights into how these metrics vary based on the different customer contact reasons (root cause and inquiry).
Access the Metrics page
Go to the OI dashboard (get to the dashboard from any page by clicking the “OI” icon in the top right corner of any page)
Click ‘Metrics’ at the top of the dashboard
Metrics shows the inquiry performance by metric for your organization ranked by average metric score in descending (high to low) order from left to right.
Choose a metric of interest by switching the metric shown using the carousel underneath the metric name:
Hover over a data point in the chart to view the metric score for the inquiry:
Dig deeper into the Metrics page
Inquiries by metric - detailed view
From the overview page you can switch between the summarized and detailed view using the toggle in the side menu on the left of the screen.
The detailed view will provide the following information:
Top / Bottom inquiries for the selected metric and by volume
This panel shows you the top and bottom inquiries by the selected metric and by volume for the date range and model(s) selected.
Tip: Use filters to change between metrics.
Inquiry impact on metric
This panel shows you the impact of a given inquiry on the metric of interest for the date range and model(s) selected, factoring both the volume of interactions and performance against the selected metric for the chosen inquiry type.
Imagine what would happen to the chosen if you got rid of an inquiry type all together. Would the average metric go up or down?!
It's not so straightforward to understand, because most metrics are reported as averages. This chart shows you which inquiry types 'drag' the metric higher or lower, so you know where to focus.
Improving the biggest positive / negative driver by even a small amount will have a flow on impact to your contact center's overall performance!
Tip: Use filters to change between metrics.
Metric and volume by inquiry
This chart ranks your inquiries by volume and shows you how they perform by metric on the secondary (right) Y-axis.
This can be used to see which high volume enquiries could be targeted for improvement for a chose metric.
Tip: Use filters to change between metrics.
Metrics over time
This chart shows how your volume of interactions and performance for a chosen metric is changing over time.
This can be used to detect if changes in volume of interactions is correlated with a change in performance for the chosen metric.
For example: when interaction volume increases does this also make your handle time increase? Does customer satisfaction go up or down when you are busier?
Tip: Use filters to change between metrics.
Inquiries over time
This chart shows how the volume of interactions for your most common inquiries changes over time. Hover over a data point to see how performance against metrics is changing over time also.
