What Is Omnichannel AI? And What Makes It Different to Multichannel?

You reach out to a company via chat concerning a delayed order. After ten minutes of waiting, you call to ask instead, only to find that the customer service agent has no information on the status of your order. You have to retell the context of your initial inquiry from scratch. It may seem like a minor annoyance, but this serves as a subtle lesson to you as a customer: this company's systems are not integrated, and, by extension, you cannot trust this company to handle more critical matters.

Omnichannel AI exists to bridge this particular gap.

The Definition of Omnichannel AI

In short: omnichannel AI allows for preserving context across channels so that a customer is not forced to retell the same story several times over to different support mediums.

The critical difference between omnichannel and multichannel customer engagement lies in sharing context across support mediums.

Multichannel vs Omnichannel — The Real Difference

• Channels available. Multichannel: many (chat, email, voice, social). Omnichannel: many (chat, email, voice, social).
• Data and context. Multichannel: siloed per channel. Omnichannel: shared and carried across channels.
• Customer experience. Multichannel: starts over on every channel switch. Omnichannel: continuous — picks up where it left off.
• Brand consistency. Multichannel: varies by channel and agent. Omnichannel: consistent tone and information everywhere.

Practical Applications of Omnichannel AI

• Shared context layer. To achieve continuity, omnichannel AI relies on shared context rather than having the same information repeated across channels. This can be achieved by having a context layer that is accessible to all channels involved in the conversation.
• Contextual intent identification. Intents should be identified on a per-conversation basis rather than per-channel. This is especially important for conversations where it is common for users to ask for something specific, then change their mind, or ask a follow-up question.
• Orchestration. A “glue” that coordinates interactions across channels and determines the best course of action given the conversation history. It may involve switching channels, escalating a conversation to a human agent, or following up on conversation threads via another channel.

Where Omnichannel AI Can Be Used

• Customer support. A customer can switch between channels seamlessly, without having to repeat themselves.
• Global business operations. A consistent brand image and consistent quality of support across channels is essential for global operations. This extends to multilingual support as well.
• Proactive customer engagement. Proactively reaching customers on their preferred channel helps deliver a consistent experience while reducing the workload on agents.

The Benefits of Omnichannel AI

• Lower repeat-contact rates. Because customers don't have to retell the same story, omnichannel AI reduces the number of times a customer has to reach out to a company.
• Faster resolution time. Fewer steps are required for the customer to resolve an issue, as they do not have to repeat information.
• Reduced overhead. Having separate tools for different channels adds up, both in time spent managing those tools and in cost.
• Brand consistency. A company that delivers the same quality of support across all channels projects an image of a competent, professional entity, whereas a company that is unable to do so appears fragmented.

Some Disadvantages of Omnichannel AI

Omnichannel AI is challenging to implement correctly, and an improperly designed system will create more confusion than anything else. The ability to switch channels depends on the ability to share context, and if that is not implemented correctly, customers will be justifiably upset that they have to retell the same information over and over. This is especially true if the company has promised omnichannel support, advertised it as such, and delivered something else entirely. In many ways, this is even worse than delivering subpar but consistent multichannel support, because customers who expect omnichannel support to work will be especially disappointed if it does not.

Should You Invest in Omnichannel AI for Your Business?

If you operate a company with customer support channels in more than one medium, it is inevitable that some customers will attempt to contact you using multiple mediums. For these customers, the promise of omnichannel support is desirable, if not expected. It is useful to consider where it makes the most sense to implement it. It is probably best to prioritize it for channels where the customer is likely to ask a follow-up question or raise a concern after initial contact, or where a request has been denied or otherwise requires additional clarification. This is especially true for large-scale operations, for which the cost of such support is relatively low, and for which the alternative — namely, the inability to switch channels — is undesirable. There is little point in implementing omnichannel support in a small-scale business with limited customer support capabilities, where the cost-effectiveness and practicality are severely limited.

How Does ResolX Address This?

Omnichannel continuity is at the core of what Omvia, ResolX's orchestration layer, is designed to do. A customer can reach out to a company via chat, escalate the conversation to email to have more details addressed, and then follow up by phone to voice approval of the proposed solution. Similarly, a company can follow up with a customer via email after an initial conversation if the customer has not responded. Omvia aims to provide continuity across channels, allowing conversations to continue uninterrupted, even if the channel itself changes, and even across multiple languages, at enterprise scale.