Using Speech Analytics for Agent-Customer Personality Matches
In previous blogs we have discussed how speech analytics makes it easier for contact centers to route calls to the agents best suited to handle them, based on the nature of the customer’s inquiry. Some agents are better at dealing with returns, for instance, or explaining how a product works, or leveraging an upsell opportunity.
But there is another benefit to speech analytics that can also improve customer engagements, and that is to match calls to agents based on personality.
We all have different traits as people and usually we gravitate toward others who share those traits. This works in business as well. People who are more quiet and contemplative are not going to be as receptive to a loud, aggressive salesperson. Such traits are obvious in a retail environment, but over the phone finding the right match requires the type of insight that only speech analytics can provide.
Before we even get to that step, however, you need to know what types of personalities you have available to you on each agent shift. Hopefully, a good mix will occur naturally – some will be more outgoing and friendly; others will be more reserved and “all-business.” You don’t want to have too many gradations here – start with simple introvert and extrovert classifications.
Now you’ll need to route calls appropriately based on the customer’s personality. With call recording you can review past engagements and gather enough insight into each customer to place them in one of these behavioral categories. Then, the next time he or she calls, you’ll know which agents have a better chance of making them happy.
Why is this important? The improved likelihood of a rapport between agent and customer may result in faster calls, high call resolution and more sales.
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