AI Voice and Chat: When to Prioritize Each for Maximum Customer Engagement

As AI-powered interfaces become central to customer engagement, organizations face a critical strategic choice between voice-first and chat-first AI. While both leverage natural language processing, they differ in several important ways.

The question is not which approach is inherently superior, but rather which approach is better for your particular business, use case, and customer base. Examining the core differences between these customer engagement solutions can offer guidance on deciding which one to prioritize.

Modality of Interaction

AI-powered chat involves text-based interactions on websites, messaging apps, or integrated platforms. It allows users to ask complex questions, copy and paste information, easily share attachments such as relevant forms or screenshots, scroll up to revisit chat history, follow instructions, and so on.

Chat can be optimal for handling simple, straightforward inquiries or a single, process-driven task, such as changing a password, checking an account balance, or reporting a service outage.

However, some problems are too nuanced to type into a chat window. AI voice engages customers through the spoken word, often through smart speakers, call centers, and mobile assistants. This makes it excellent for customers who need to provide more context with their request, ask follow-up questions, or immediately clarify an issue.

Crucially, voice offers greater accessibility for visually impaired customers, while chat does the same for users with hearing and/or speech impairments.

Context Retention

Chat shines when maintaining context across multiple chat threads, keeping pace with users who switch between topics or revisit previous queries. Chat logs also enable both users and support teams to easily recover information needed for next steps.

This long-term context persistence facilitates informational flow and better follow-up chats, improving the experience of customers with multiple touchpoints.

While more advanced voice solutions are improving at more complex conversations, they can often challenge fluidity. The lack of visual references can make it difficult for customers to retain detailed information, which is all the more reason voice AI is currently best suited for real-time interactions.

Integration and Deployment

It is relatively simple to embed chat AI in websites, mobile apps, and messaging platforms. It also seamlessly integrates with most CRM solutions and customer portals and can be easily automated for various languages and regions.

Voice AI works by integrating with smart devices, voice platforms, and telecommunication systems for call centers. Scaling is more complex with voice, since different languages and vocal nuances like regional accents, dialects, and speech patterns have to be considered.

Tone Modulation

Perhaps the most important metric for customer engagement is how that engagement makes the customer feel. Getting that right depends not just on useful content, but also on tonal appropriateness.

Chat AI can adjust tone based on conversation type. For example, it might become more formal when troubleshooting a technical issue, or more conversational when responding to a general inquiry.

While chat AI can use sentiment analysis to detect signs of emotion in customer messages, it does not benefit from vocal inflections in output or input. In other words, not being able to hear or be heard by customers limits the ability of chat AI to convincingly simulate empathy.

Here, we come to a key advantage of voice AI: the ability to leverage vocal cues to achieve more humanlike and emotionally engaging customer interactions.

Detecting signs of frustration, excitement, confusion, or impatience in a customer’s voice is only the first step in this process. Advanced voice AI will use that information to modulate its tone, expressing empathy, positivity, or calm, depending on the context. Other nuances, like pausing or slowing down during explanations or instructions, can help make the customer feel heard and respected.

That said, misinterpretations can happen, leading to tone-deaf moments that can damage customer relations. This more complex emotional functionality requires more sophisticated optimization.

Choosing When to Utilize Chat or Voice for Customer Engagement

Given these differences, which should you prioritize? The answer depends on three key considerations: the interaction context, the device environment, and your business goals.

1. Customer Interaction Context

Your most frequent type of customer interaction can help indicate which solution will be the better fit. If your customers more often have short and simple requests, like setting a timer, checking status updates, or basic questions about their account, voice AI might be the way to go. By the same token, if your customer interactions are usually more involved, including tasks like troubleshooting and guidance through complex processes, a chat-first approach will probably be best.

Privacy is another element worth considering. Chat AI is often perceived as being more secure when sensitive information is exchanged. On the other hand, if the interaction is emotionally charged or time-sensitive, voice AI tends to be more effective.

2: Device Environment

The type of device your customers use most often should also influence this decision. For example, on mobile phones, both approaches can work well—voice for quick on-the-go tasks, and chat for detailed tasks and inquiries. Smart speakers and devices are designed to work with voice AI, while chat AI performs well on websites and apps calling for more complex interactions.

3: Business Goals

The AI approach you choose should help you achieve your primary business objectives. The goal of reducing average handling time points toward voice AI, while the goal of increasing self-service and scalability would likely be best achieved through a chat-first approach.

To deepen emotional connections with customers, consider going voice-first. If you want to improve service documentation and tracking, chat AI will likely be the most helpful.

All these goals will sound appealing, of course. This is not to say that chat AI can’t help reduce handling times, or that voice AI can’t help increase self-service. The key is to consider all these factors together and to decide which goals belong at the top of your list of priorities. 

The Right Decision Is to Make Ongoing Decisions

Customer engagement solutions powered by AI are evolving in leaps and bounds. The rate of change can make business leaders feel that they’re moving simultaneously too slowly (not adopting early enough) and too quickly (not giving the technology enough time to mature).

But a well-chosen solution—whether voice-first or chat-first—can have a significant impact on customer engagement in the short term.

Whatever approach you choose, it’s best to think of it as the first of many such choices as you implement the technology, learn from its performance, and stay alert as that technology improves.

Maik Hummel is head of artificial intelligence strategy at Parloa, providers of a platform for conversational AI. Prior to this role, Hummel was co-founder and chief technology officer of Neohelden, working on a digital assistant for business. With a background in business informatics and information technology, Hummel has a strong foundation in both technology and business.