Providing excellent customer service is a must for any business, especially those looking to grow. Maintaining excellent relations with customers is, in many ways, a science – one that benefits from data and continuous learning. This is where conversational intelligence comes into play.
Using machine learning and artificial intelligence, Conversation Analytics decodes what happens during every phone call. With natural speech recognition technology, users of this software can go beyond who is calling and where they’re calling from to identify what callers want and how to best serve them. Using this technology, businesses can improve various aspects of their operations, including sales and customer service performance.
Customer service professionals in particular can benefit from call recording and analytics technology by seeing exactly where they are exceeding and where they may be falling short. Here are seven data points that customer service professionals who use Conversation Analytics technology can regularly monitor to improve performance and keep customers happy.
1. Agent Politeness
Unsurprisingly, politeness is a critical aspect of customer service. Maintaining a positive, cordial relationship with each customer is a must for any successful customer service representative, regardless of the industry or type of business.
Call recording and analytics software can assess the degree to which a customer service representative is polite with a customer by ranking a confidence level of Agent Politeness on a scale from 0-100. Because agent politeness is critical, the higher the score, the better. The software measures this by looking for changes in voice, rate of speech, presence or lack of voice tremors, lack of agitation, and specific phrases or words. All of these elements are ‘cues’ that Conversation Analytics uses to determine if an agent was polite with a customer on the phone.
There are more than 700 phrases Listenforce’s Conversation Analytics software listens for to determine Agent Politeness. These include:
- “Beg your pardon” / “pardon me”
- “Please” / “thank you”
- “I can help with” / “Glad/happy to help”
- “Have a great day” / “have an awesome day” / “have a wonderful day”
- “I’m sorry” / “I apologize”
2. Agitation Levels
Speech recognition technology, such as Conversation Analytics, listens for acoustic signals that measure emotion based on characteristics of speech, including tempo, pitch, and volume. Changes in these attributes can indicate a decrease in caller satisfaction.
When a customer raises their voice or begins to yell, such software picks up on this and flags it in the call recording, allowing customer service representatives to identify where, when, and – most importantly – why a customer became agitated. This data can then be used by reps and teams to understand phrases and topics that are more likely to upset customers, and how to position difficult conversations in a way that doesn’t agitate callers.
3. Complaints vs. Compliments
How often is a customer saying something positive about your business, product, or service, and how does that compare against how frequently they’re making a complaint? AI-driven Conversation Analytics software automatically picks up on words and phrases that are representative of either a compliment or a complaint, allowing your reps to see if customers on calls are more complimentary or dissatisfied with something about the service they are receiving. This data can be analyzed over time to detect trends in the overall opinion of your products or services.
4. Agent Empathy
When people contact customer service teams, it’s almost always because they’ve experienced an issue or frustration. As a customer service representative, it’s critical to demonstrate empathy in order to ensure that customers feel heard. Even small phrases such as “sorry to hear that” and “must be difficult” can make a huge difference in how the customer feels during their time interacting with a representative of your business.
Conversation Analytics software picks up on phrases demonstrating agent empathy and then provides a score on how empathetic the agent was in their interactions. Agents can consistently monitor their empathy score to see how it trends over time, ensuring that they consistently convey understanding in order to improve and maintain strong relationships with customers.
5. Ownership Language
Customers facing issues with a product or service want to know that someone is taking accountability for solving their problem. Even if you, as a customer service rep, weren’t responsible for their problem, they need to know you are taking ownership of finding the solution.
Conversation Analytics uses speech recognition technology to monitor phrases indicating that agents are taking ownership for caller requests. Phrases such as “I can help you with that” and “What I can do is…” are indicative that an agent is taking ownership. Using this feature, customer service representatives can see how their usage of ownership language trends over time.
6. Percent of Silence (Dead Air)
Percent of silence is calculated by taking the absence of speech on a call measured against the total duration of the call. While it’s normal for people – both customer service representatives and customers alike – to take some time to think on calls, silence generally should not take up more than 20% of the call. Think about it this way: if you’re on a 5 minute call and 20% of that call is spent in silence, that’s a whole minute of valuable conversation lost.
Why does dead air occur on phone calls? One common reason is that the customer may have posed an issue or question that the agent on the call has never dealt with before. By reviewing these types of questions/concerns and identifying common themes among them, customer service teams can prepare each agent for future instances, ensuring that agents don’t find themselves stumped while on the phone with a customer.
7. Longest Monologue
Are you giving your customers enough opportunities to speak? While it’s important to ensure you answer all of their questions, talking for too long at once, without stopping to ask if your customers have questions, can be cause for concern. Data from sales calls demonstrates that top-performing sales reps, on average, speak 43% of the time on phone calls, which allows prospective customers to speak 57% of the time on average. While customer service isn’t selling a product in the same way that sales is, you’re still representing your company and helping customers find a solution – thus making this data applicable to customer service calls as well.
As you can see, there are a number of ways that AI-driven Conversation Analytics can bolster your customer service performance by providing valuable intelligence and data at scale. If you are interested in seeing these indicators in action, reach out today to schedule a demo or sign up for a free 21-day trial of Conversation Analytics.