How to choose the best omnichannel AI customer service platform for chat, email, voice, and messaging
We explore what capabilities AI customer service platforms need to deliver the omnichannel experiences that your customers crave.
The need for omnichannel customer service has never been more urgent. Enterprises must meet diverse customer preferences across various channels and modalities.
But managing multiple channels while maintaining high-quality service is challenging. Often CX teams have to limit support channels, hours, or response times, leading to disjointed customer experiences.
It feels like there’s no winning: either your resources are spread too thin to provide great service or your great service is segmented. Regardless, your customer experience suffers.
But there is hope. AI customer experience (ACX) platforms enable consistent, high-quality service across all channels, driving customer loyalty and, ultimately, increased revenue.
Related reading: The ultimate guide to AI omnichannel customer service
What is omnichannel customer service (and how is it different from multichannel)?
Before diving into the specific platform capabilities, it’s important to level-set on what we mean by omnichannel and how it differs from multichannel. While the terms are sometimes used interchangeably, there are actually significantly different impacts on the customer experience and your bottom line.
Multichannel customer service means you’re using different systems to deliver customer support on more than one channel. Your human agents manually switch between them and pull insights from each system separately.
Omnichannel reduces effort and increases consistency by integrating all your different channels into one platform. All channels benefit from the same valuable AI capabilities, your human agents don’t repeat work, and all your insights live together in one place.
| Impact on... | Multichannel | Omnichannel |
|---|---|---|
| Customer experience | Support channels operate independently on the back-end, resulting in inconsistent or fragmented customer experiences across channels. | Support channels are integrated under one platform, providing users with a cohesive, consistent, personalized journey across all channels. |
| Channel management | Human agents manually switch between systems to manage each channel separately. | All channels have a single source of truth that can be managed from one platform. |
| Interaction continuity | Context is scattered across various tools. The CX team may have to switch CX platforms to gather context. | CX teams have access to all the context in one platform, enabling them to understand a customer’s entire history with the brand regardless of where the interactions took place. |
| Data sharing | Customer data is restricted to channels and dev resources are needed for API integrations. | Customer data is shared across all channels, with built-in connections that enable you to deliver personalized service at every touchpoint. |
| Customer service insights | Insights are surfaced only on independent channel level. | Insights are surfaced about the customer journey as a whole, and can be narrowed down to channel level. |
| Staff requirements | A separate AI agent is needed for each channel, and potentially channel-specific human agents as well. | One omnichannel AI agent and one AI Manager to extend its capabilities across all channels. |
| Opportunity to scale | Expanding to new channels requires a lot of upfront cost and labor to get the AI agent up and running—not to mention resources for ongoing maintenance. | Expanding to new channels is effortless. The AI agent uses the content and guidance it already has, and AI Managers can easily add channel-specific coaching. |
With this in mind, let’s dive into the key requirements to look for while assessing the omnichannel capabilities of ACX platforms.
1. How do we keep customer context when switching channels so customers don’t repeat themselves?
The short answer is: a unified omnichannel ACX platform. This is the most foundational requirement to look out for. The AI agent should be able to service your customers on all your support channels from within one unified platform.
| A unified platform ensures that… | Which leads to… |
|---|---|
| The AI agent is using the same knowledge bases, sources of truth, actions, coaching, etc, across all channels. | Consistent customer experience, easier AI agent management, and effortless expansion to new channels. |
| Interaction context and customer data from all channels are captured in the same platform. | Customers not having to repeat themselves if they switch channels, human agents not having to switch between software to get additional context, and more holistic customer data. |
| The same AI agent is able to service customers on all support channels. | The AI agent using multiple channels to optimize the customer experience—e.g. sending order details to a customer via SMS while servicing them on the phone. |
| Automated resolution analytics from all channels are captured in the same platform. | Better understanding of the success of the AI agent and ROI, and deeper insights surfaced by the AI agent. |
TLDR
None of the omnichannel benefits would be possible without strong integrated channels, and for that you need a unified platform. Not only does it save you time and money in developer, human agent, and AI agent resources, it also unlocks deeper insights and provides a more cohesive experience for your customers.
2. How do we do multilingual omnichannel support at enterprise scale?
Typically when you rollout an AI customer service agent on new channels, they will immediately handle 100% of the conversation volume. An ACX platform with staggered rollout capabilities means you can allocate a specific percentage of the volume to the AI agent instead.
This is especially important when you want to strategically expand support channels without overwhelming your resources or compromising quality.
By adopting an experimental mindset when launching new support channels, you can start small, identify opportunities for increased customer engagement, test these initiatives in a controlled environment, gather data and monitor the AI agent’s performance, and address any hiccups before committing to a full-scale rollout.
“Customers are interacting with us 24/7, and we wanted to be able to provide the same prompt answers and level of service around the clock. But we’re also dealing with people’s funds and we take that very seriously.
A gradual rollout helped us keep a close eye on the AI agent during the day and optimize it until we were confident enough to let it service customers unsupervised during off-hours.”
TLDR
A staggered rollout not only fosters innovation but also minimizes risk, enabling faster and more sustainable growth. It also helps you gradually build confidence in the AI agent's capabilities and ensures that each new channel is fully optimized before being made widely available to customers, maintaining high service quality across the board.
3. What are some channel-specific customization we need to think about?
AI customer service agents need to adapt to each channel’s strengths and limitations without losing consistency. That’s only possible with a platform that lets you coach your AI agent’s behavior across channels.
- Customer expectations: Short messages and a casual, conversational tone.
- Channel opportunity: Breaking up long messages and letting your brand personality shine.
- Customer expectations: Communication that is concise and straight to the point.
- Channel opportunity: Sending short, transactional messages such as appointment reminders, addresses, numbers, or other information the customer needs to remember.
- Customer expectations: Higher volume of back-and-forth interaction, but they don’t want to scroll through chat to find their place in the conversation if they had to switch between apps or temporarily close the chat.
- Channel opportunity: Creating step-by-step guidance in small chunks that is easy to follow. If a task involves more than three steps, the AI agent could deliver the first three, then ask if the customer is ready to proceed before continuing.
- Customer expectations: Seamless self-service and more chat functionality.
- Channel opportunity: Taking advantage of the platform’s capabilities to provide a deeper, more interactive level of support. Guiding users through complex processes with rich media (images, videos, etc) and bulleted step-by-step instructions.
- Customer expectations: Sterile, templated interactions and longer response times for non-automated replies.
- Channel opportunity: Ditching the templates and making the experience feel more personal with fluid and natural dialogue, either by using more conversational language or personalizing responses based on guidance. Adjusting the AI agent’s response time so that it’s prompt while still giving enough buffer for customers to know it’s not just an “auto-response”.
- Customer expectations: Natural conversations that are human-like, speaking in the language they’re most used to, and pauses to allow information retrieval when necessary.
- Channel opportunity: Managing the AI agent’s tone and pace to strike a balance between speed and clarity, representing the brand with the AI agent’s voice, using the ACX platform's multilingual capabilities, and sending information that needs to be noted down or remembered via SMS to reduce effort for customers.
TLDR
Despite the differences between channels, the ultimate objective is to provide the same high level of service and make your customers feel supported no matter how they choose to connect. Having the tools needed to adapt the AI agent’s behavior to the specific requirements of each channel allows you to meet that objective and scale customer service operations without being limited by channel constraints.
4. What are useful AI customer service agent capabilities for omnichannel CX?
There are a few other AI agent skills to look out for that can make the omnichannel experience even better. These are the top two.
When customers connect with you, they often write multiple questions in the same message instead of separating them out. While this is a skill you should be looking for in AI agents anyway, it becomes particularly important when you want to optimize the omnichannel experience. For example:
- Email: This is a long-copy channel. Customers typically write longer messages that may include more than one request.
- Phone: In a phone conversation, customers are more likely to ask more than one question before pausing to get an answer.
If the AI agent can’t parse out and handle multiple intents, it’ll create an increased back-and-forth that leads to a poor experience.
Similarly to how you should service customers on the channels they want, you should also be servicing them in the languages they prefer.
Using an ACX platform that can communicate in multiple channels improves the customer experience and makes it easier to scale support across different markets or user segments.
“Make sure that you're getting the right solution, one that integrates seamlessly across not only your tech stack on the back end but also across different channels, and that it handles a wide range of customer interactions. [And you should understand] the data on the different communication channels and what ROI you could get from handing them to the AI agent.”
Non-negotiables for the best omnichannel customer experience
Now that you know what you're looking for, it's time to go out and find it. Click the "Download companion templates" button to get a handy checklist you can use while evaluating omnichannel AI for customer experience.
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