Should agents try to build a relationship with customers they’re serving? We used our AI platform to analyze conversations to get a definitive answer.
Recently, one of our customers noticed a strange pattern when auditing some of their customer contact center conversation transcripts. In the conversation, an agent casually mentioned to the customer that it was his birthday. When they took another look, they found the same agent telling other customers about his birthday, too. A lot of them- – and on more than one day.
It piqued our customer’s curiosity. So they ran a query through our system and found out it wasn’t just one agent. The activity seemed to spread throughout a call center, as if one agent thought the behavior might be helping boost his or her scores and spreading the theory to coworkers.
They found that the odd comments weren’t limited to agents announcing that it was their birthday. They also found strange, hokey phrases repeated verbatim, customer after customer, agent after agent.
“Stay happy and positive”
“It was a plum pleasure to help you today”
“You’re the best customer I have talked to all day, very patient and kind”
“Please smile throughout the day”
“May every day glow with good cheer.”
They were even more surprised when they found these interactions had better CSAT survey results than the average. Do customers actually care if it's an agent’s birthday? Do they want to be told to smile or to spread positivity?
We came in to help them determine what exactly was happening - and if it had any impact on how the customers reacted during calls. Were these unusual phrases actually working and did they build rapport with customers?
What happens when agents try to build rapport with customers
The question was - How do customers react? We used Tethr’s AI analysis to see.
Here’s how we did it: In Tethr, we created a way for our AI-powered conversation intelligence platform to recognize this type of conversational “over the top” language.
That way, Tethr would catch every time it occurred in a conversation. Once we could identify which conversations it occurred in, we could then measure how it affected the customers’ experience.
What we found: Do customers want agents that built rapport with them?
We knew these customer interactions scored well, but we wanted to know whether the “over the top language” actually caused those scores to climb higher.
When we used our Root Cause AI capability, which used statistical analysis to determine if one event has a direct effect on increased CSAT scores. We found that while some conversations with the “over the top” language did score well, it wasn’t the whimsical addition of “plum pleasure” that did it.
We concluded this: The agents who were using the unusual phrases were trying, (and in some cases trying really hard), to meet a customers’ needs.
That agent effort made the difference - not the strange language.
What agent behaviors make a difference to CSAT scores
These “over the top” conversations had above-average scores, but they also had higher incidence of the other agent behaviors that Tethr measures and encourages.
- Agents used action-focused advocacy statements such as “I’m going to look into this right now,” instead of offering explanations or apologies
- Conversations had above-average incidents of expectation setting, the behavior where an agent tells customers what they can expect to happen less. When agents do this, customers are less likely to repeatedly contact you or get frustrated.
These calls also had fewer behaviors that we discourage, including:
- Fewer powerless to help statements such as telling a customer about a policy that prevents them from solving a problem.
- Fewer cases of issue misdiagnosis, which is when customers actually tell the agent they were misdiagnosing what the problem was.
Combined, these behaviors (and not any fake birthdays) made the real difference to customers.
Want to learn more about the language that makes a difference to customers - and the surprising behaviors that may damage your overall customers’ experience? Download our ebook, “The end of empathy” to learn more about in-depth analysis of why customers want action-focused advocacy language instead.