Service Intelligence components provide a key contact center performance metric that can easily be embedded where you need it.
Required Editions
| View supported editions. |
Determine whether you're meeting your customer service goals with an easy-to-understand metric in the Service Intelligence insights. The combination of customer data, key performance indicators (KPIs), and artificial intelligence (AI) help your service team improve operations and reduce costs.
- Enable the Propensity to Escalate Insight Component
For the Propensity to Escalate model to work as expected, you must modify the associated batch data transformation to integrate the Einstein predictive model. - Use the Propensity to Escalate Insight Component
While working on cases, see AI-powered insights that estimate the likelihood customers will escalate their cases. Propensity to Escalate is a machine learning model built using Einstein Studio No Code Builder. - Use the Customer Effort Score Insight Component
Add the Customer Effort Score insight component to your case page layouts so your support reps can see how much effort the customer is putting into the case, at a glance. Customer effort directly impacts customer satisfaction, so understanding this score helps level up your customer service. - Use the Time to Resolve Insight Component
Give support reps AI-powered insights that estimate how much time it takes to resolve cases so they can better manage SLAs or reassign work to teammates. Time to Resolve is a machine learning model built using Einstein Studio No Code Builder.