A few years ago, only 15% of customer interactions relied on emerging technologies such as artificial intelligence (AI)-enabled chatbots, automated emails, and virtual agents, reported Gartner. In 2022, that number rose to more than 70%.
Customer preferences and tools that can effectively execute the promise of voice-of-the-customer (VoC) strategies have contributed to the exponential spike.
For background, VoC is the cumulative feedback a brand receives from customers at different touchpoints in their journeys. These touchpoints span various channels and interaction modes to accurately illustrate customer expectations, needs, preferences, and demographic.
VoC also includes customers’ thoughts on product improvements. Through grasping a solid understanding of them, organizations can more easily spot emerging trends and implement necessary upgrades.
How Businesses Capture VoC Data
Surveys and webforms are common ways that businesses gain feedback from customers. However, with modern tools such as AI-enabled virtual contact center agents, companies can secure VoC data in natural, voice-and text-based conversations.
One example is online chat tools. A live chatbot on your website is a great way to collect real-time customer feedback. It also reduces the possibility of customers feeling unsatisfied with the service and offers them real-time support.
These chat services offer text analytics and sentiment analysis to help businesses track and review interactions to understand VoC better. These tools work together to help companies find actionable meaning.
However, these AI-enabled tools are only effective in delivering VoC strategies if they’re well designed.
For when poorly designed, these tools can miss the mark. They can annoy customers and employees, prove unproductive, and ultimately be ticking time bombs if they’re not enabling brands to proactively respond to changing customer preferences.
Defining Conversational Design
Businesses can ensure their AI-using tools effectively capture VoC data through Conversational Design.
Conversational Design examines human conversations and works to ensure that these communication tools are intuitive and match customer personas.
Conversational Design aims to make AI-enabled interactions with digital systems feel more natural. It can greatly improve Conversational AI, a form of intelligence that facilitates real-time, human-like communication between a person and a computer (e.g., a customer and a virtual contact center agent).
A live chatbot...is a great way to collect real-time customer feedback...and offers them real-time support.
Conversational AI can “learn” human nuance, but it needs to be programmed to effectively respond in a way that resonates with customers. Because of this, strong Conversational Design is vital to successful VoC strategies and to broader customer experience (CX) approaches.
Businesses can implement Conversational Design in their contact center solutions to ensure chatbots, automated emails, and other virtual agents can handle customer interactions.
For example, let’s compare an AI-enabled virtual agent with and without Conversational Design.
Without Conversational Design
Let’s say a customer calls a contact center to check their account balance. At the end of the call, the virtual agent asks the customer, “Are you satisfied with your service?” The customer replies, “No.”
This virtual agent might then say, “Thank you for your feedback! We will route you to customer support.” Though this response is not technically wrong, it doesn’t mimic a real conversation and doesn’t meet the customer’s needs.
With Conversational Design
A virtual agent with Conversational Design handles this scenario differently. At the end of the call with the customer, the virtual agent might ask, “Are you satisfied with your service?” and the customer says, “No.”
By leveraging Conversational Design, companies can ensure that AI-based tools are built to facilitate human-like conversations with customers.
This virtual agent might ask additional questions to understand why the customer was dissatisfied. For example, it might say, “I’m sorry I couldn’t meet your needs. I will route you to a human agent who can offer you a discount.”
The information the customer provides to the virtual agent can then be reported to the business and used to improve service in the future. The data might also inform an automated email to follow up with the customer about their experience and future service.
By leveraging Conversational Design, companies can ensure that AI-based tools are built to facilitate human-like conversations with customers.
Conversational Design also helps inform simple interactions to ensure the chatbot or virtual agent uses the correct terminology based on the industry or a specific customer’s communication preferences.
Companies can also ensure these tools match customer personas and are an extension of the brand’s identity. For without a thought-out persona, a virtual agent can seem hollow and unengaging. Creating an identity modeled after your brand engenders user empathy and reflects the personalized engagement customers might receive from human support agents.
When AI-based tools are designed to interpret and respond using dialog that’s consistent with a brand’s identity and a customer’s persona, the data can lead to a more robust VoC strategy.
Three Ways Conversational Design Improves CX
Conversational AI is raising the bar for CX by transforming how humans interact with digital systems. Outlined below are three ways Conversational Design can improve it.
1. Self-Service Capabilities
Conversational Design helps brands enhance self-service resources and allows companies to serve customer needs better. Data reveals that 65% of customers prefer to solve issues independently.
Contact centers can deliver round-the-clock customer support using well-designed, AI-enabled virtual agents. Customers can resolve issues, find answers to questions and/or complete routine transactions without having to wait on hold or talk to a human agent.
2. Contextual and Streamlined Interactions
By leveraging intelligence from AI-enabled tools, brands can deliver contextually aware CXs.
For example, an intelligent virtual agent can predict a caller’s identity using the phone number used to initiate the call.
Once the caller’s identity is confirmed, the virtual agent can utilize data from past interactions to understand why the customer might be calling. This contextual information can improve the CX by making it personalized.
AI tools that are equipped with Conversational Design can interpret customer requests and conversations easily. As a result, customers may experience less frustration having to repeat their questions and find resolutions faster.
3. Understanding Customer Intent
Conversationally designed virtual agents understand what callers say and how they say it.
Identifying tone and deciphering between a happy or frustrated caller enables the virtual agent to offer unique and personalized support. If they sense a customer is frustrated, the virtual agent can pivot their approach to ask questions and provide solutions to mitigate further frustration.
Businesses can design these tools with machine learning and natural language processing to enable them to learn with every customer interaction.
Understanding a customer’s intent during a call can help identify the specific issue that needs to be solved and how best to approach it. This insight can also inform future employee training.
VoC strategies are increasingly valuable as brands look to respond to customer preferences and demands.
Conversational Design should be a roadmap that guides businesses’ VoC CX strategies. Without Conversational Design, organizations miss opportunities to strengthen customer relationships, streamline communications, improve service, track feedback, and build stronger brand loyalty.
Understanding a customer’s intent during a call can help identify the specific issue that needs to be solved...
With a deep understanding of customers’ opinions of the company, decision-makers can hone other business areas to meet customer needs. Satisfied customers will become enthusiastic ambassadors for the brand, which will lead to better brand perceptions and, likely, more customers.