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Predictive routing uses machine learning to rank each agent in your target agent pool for how well that agent is predicted to handle a specific interaction. In its simplest form, predictive routing identifies the agent-interaction match most likely to result in an optimal key performance indicator (KPI) value.
There are three phases to activate predictive routing and take full advantage of all the benefits it can offer. The documentation for predictive routing fully explains each of these phases, listed below:
To start using predictive routing, see the Use predictive routing section of Create and configure queues for instructions.
The following table lists the KPIs currently available for use in predictive routing. If a KPI you are looking to use is listed as Beta, contact your Genesys representative for assistance.
To submit a request for a new KPI, add it in the Genesys Cloud Product Ideas Lab, available to logged-in users from the Genesys Knowledge Network.
| KPI | Availability |
| Average Handle Time (AHT) | Generally available |
| Revenue KPI | Generally available |
| Next contact avoidance | Generally available |
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