Just as contact center teams have begun to adapt to remote and hybrid environments, they are confronting a new set of challenges among them: economic uncertainty, inflation, and heightened consumer anxiety.
As a result, maintaining customer relationships and trust has become more important than ever. Customer success teams must now learn to rely on tech, notably artificial intelligence (AI)-powered tools like Conversational AI, to help provide the highest quality service to retain and grow business.
When associating AI and customer service, most people imagine an automated voice that will eventually, after jumping through several hoops, connect them with a human representative. It can be frustrating to say the least. We know that customers prefer human interaction; this can be boiled down to three things: efficiency, empathy, and trust.
…maintaining customer relationships and trust has become more important than ever.
These days, customers are seeking greater value from vendor relationships; they want seamless, efficient customer support at their fingertips or at the points of quick phone conversations.
If a customer knows that they will get a human on the other end of a call, someone who’s empathetic and personalized in their responses, it not only provides efficiency, but it elicits a sense of personalization and builds loyalty and confidence in a brand.
However, with constrained budgets and smaller headcounts, contact centers are being challenged to do more with less. Facing the need to optimize time and human-to-human conversations, this is where AI solutions with real-time transcription and conversational analysis come into play.
AI can empower reps to consistently engage in more meaningful customer interactions. Today, and tomorrow, the most successful organizations will utilize AI insights to augment the value of service provided by reps, fuel better conversational outcomes, and drive customer retention and growth.
Yes, to many contact centers, the thought of AI seems to be in the distant future. However, recent data demonstrates that nearly nine in 10 people (88%) prefer speaking to a live representative over a phone menu or chatbot.
Here’s how best to make AI an asset in your contact center.
The key differentiator of customer-facing conversations guided by AI, versus scripted conversations and automated service providers, is the use of natural language.
Rather than requiring reps to follow robotic scripts full of buzzwords and complicated industry-specific acronyms, AI empowers them to establish authentic rapport with customers while personalizing those conversations directly to those individuals.
The value in Conversational AI is that reps are guided, not scripted from A to Z. Preserving human elements of the interaction…
When a rep is speaking to a customer with AI guiding the conversation, the rep is interacting with the customer with their organic voice and natural language.
For example, Conversational AI analyzes voice data and prompts reps in real-time based on what the customer says in a conversation.
The value in Conversational AI is that reps are guided, not scripted from A to Z. Preserving human elements of the interaction while providing guidance on where to take the conversation, not how to have it word-by-word, generates a more personalized approach with better connections and more productive customer interactions.
2. Empathy and Sentiment Analysis
It is only natural that when a rep is scrambling to take notes or read from a script, they will inevitably disengage from a conversation. But with the power of tech behind them, reps can better focus on an interaction and engage with the customer.
The use of a voice-generated AI or transcription service with sentiment analysis can generate personalized reports based on what reps say and based on the words that resonate with the customers. AI can analyze empathy and voice in real-time to automate note taking and guide agents, allowing for more organic interaction and empathetic sentiment across conversations.
The reality is that people don’t always think in an A-to-Z fashion in the way a script is constructed. When a conversation is guided, rather than scripted, there’s a more natural flow and a mutual understanding that both the rep and customer are on the same page. In just five or 10 minutes, an organic conversation can elicit that much more trust from a customer.
For management, automated call flagging, using techniques like text matching or utterances, identify more than just keywords and phrases for coaching purposes. Tone and voice inflection, gaps of silence, and pauses between phrases are elements of conversations that managers can’t gain insight into with a visual performance dashboard.
When you compare a person and an automated experience, the challenge is handling the nuance, sentiment, and ambiguity…
When it comes to understanding the quality of a conversation, it’s just as valuable to understand these nuances as the words themselves.
Consider the natural pause between a question and an answer; if you look at Alexa or Siri it’s interesting to see where technology is going, but nuance and natural pause is something so subtle and human-specific that technology doesn’t quite replicate. That pause, that hesitation, and how a question is raised creates rapport and that can be magical.
3. Timeliness of Conversation
If I call a store and a rep answers my call I will be greeted by the rep, respond with the reason for my call, and either have my question answered by the rep or be directed to the right department to handle my request. It’s a two-to-three-step process.
On the other hand, if I call a company and ask for help through a machine, I will be prompted to state the purpose of my call, listen to a list of automated, number-assigned options that may or may not fit my question, and choose the best option.
A machine will then read me more options, including the option to ask for a rep. At this point, if I haven’t gotten the information I’m looking for, I would be placed in a queue to wait my turn to speak with a rep.
By the time I’m connected with a rep, they might answer my question, or transfer my call to another department with another queue…and the process goes on.
When you compare a person and an automated experience, the challenge is handling the nuance, sentiment, and ambiguity that surround in-the-moment customer requests that a machine does not have the capability to process.
With the power of AI, a customer success rep will be guided to best handle my request. But unlike a machine, they will answer verbally and guide me to an answer with recognition of my tone: hopefully within no more than a two-or-three-minute turn around.
4. Digital audit trail for regulatory compliance and data privacy
As more teams are working remotely, having a central source of automated call records provides an essential layer of data protection for organizations.
With the restructuring of the traditional workforce, now’s the time for contact center leaders and executive teams to take the following action. They should automate voice capture to optimize visibility and the audit process: while ensuring end-to-end voice capture remains compliant with U.S. state and federal regulations.
Whether you’re a healthcare, insurance, or financial services organization, the language you use in customer-facing conversations is industry-specific.
Telephony solutions with AI are particularly well-suited to these types of heavily regulated industries. Automated redaction functionality ensures that sensitive information identified by conversational analysis is removed from post-call recordings and transcripts.
For healthcare organizations, consider HIPAA; when it comes to an audit for your company or CRM, it’s much easier to audit your customer service team using call records.
AI gets in the path of all calls agents make from any phone, anywhere, flagging sensitive data and making it easy for regulatory managers to understand how PII (personalized information) is handled to ensure that it isn’t explicitly shared.
This automation prevents the need for corrective action. Without having to manually audit call recordings, the amount of time a regulatory manager gets back in their day is threefold, something organizations will find especially valuable with limited budgets requiring teams to do more with less.
With workforce restructuring, agents and managers alike must better align user expectations, all the while doing more with less time and less overhead. For enterprise organizations, AI insights into the complete prospect experience enables customer service teams to serve customers more efficiently and close support cases faster.
The advantage is that the AI data trail captures natural language in an organic way, analyzing data down to specific nuances and phrases in a conversation.
Beginning with the call a rep handles from a consumer, AI insights allows them to learn and, moving forward on each call, come more prepared to the conversation. This way, reps can better align themselves with customer expectations, have more productive conversations with optimal outcomes, improve CSAT scores, and reduce customer queue times.
AI saves reps the time they would have previously spent digging through notes and prepares them to best serve the customers…
Before and after conversations, customer service reps can rest easy knowing that with AI automation, they will be able to access automated voice records of every call.
Also, when handling repeat customers, reps often have no more than a few seconds to refresh themselves on previous conversations. Not to mention that many organizations currently have smaller headcounts tasked with handling the same volume of customer service calls.
AI saves reps the time they would have previously spent digging through notes and prepares them to best serve the customers, optimizing their time as well.
Additionally, having a platform with a voice-generated data trail can be valuable for customer retention. AI can alert a rep how many times a customer has previously called, if there were any tickets from their previous conversation, or if the customer has referenced canceling their account.
AI in the Contact Center
At the end of the day, AI isn’t going to threaten anybody’s job. If anything, using the technology in the right way enables teams to maintain better customer satisfaction and retain the profitability of their call center.
To mitigate the challenges of handling a higher volume of customer interactions with lower budgets and headcounts, customer service organizations can utilize AI to streamline workflows, boost efficiency, and optimize conversations to provide greater value and meaningful customer interactions.
With only so many hours in a day, customer navigation should begin with voice whenever possible. That’s a number one priority for seamless customer experiences.