What do data and a barking dog have in common? Consider this hypothetical contact center conversation. The agent receives a call. A dog barks in the background:
Agent: Hi, this is Dan at Blankenfield Stores. How may I help you?
Customer: (Wuff wuff wuff) Hi, I'm calling about a return. I'm extremely disappointed with my new (wuff) blouse.
Agent: I’m sorry to hear you’ve had a (wuff) problem. May I have your name?
Customer: Wuff. I'm Elizabeth (wuff) Watson.
Agent: Thank you, Ms. Watson. While I retrieve your (wuff) information, it sounds like you have an enthusiastic dog there. (He chuckles) What kind is it?
Customer: (She pauses, relaxes, and replies in a positive tone.) He's a mix, part beagle and terrier.
Agent: That’s nice. How (wuff) long have you had him, and what's his (wuff) name?
Customer: Rascal is three (wuff) years old.
Agent: I've got a four-year-old Spaniel. Belonged to my brother.
Customer: Without Rascal, I’d be completely mental. He's such a (wuff) friend. He helped me through Covid (wuff) lockdowns.
Agent: I know what you mean Ms. Watson. Tony does the same for me.
Collect. Analyze. Act.
Later, the call center collects and analyzes this hypothetical call using conversational AI tools. The insights noted that Ms. Watson was initially frustrated and annoyed. Yet, it also finds that - thanks to the agent's situational awareness - Ms. Watson's initial annoyance quickly de-escalated.
From this, the contact center senses an opportunity for dog-loving agents to kickstart similar small talk when interacting with customers surrounded by barking dogs. Finding this commonality builds rapport and increases the possibility of positive customer outcomes.
Such an example highlights the power of interaction data, which provides deep insights into sentiment and emotion. Better still, it’s free, waiting to be mined.
