How Testing & Training Conversational AI Can Reduce Channel Hopping


The omnichannel customer experience (CX) is quickly becoming the norm, and consumer expectations are likely to continue rising. According to data from Retail Dive, 88% of Gen Zers expect a mix of digital and physical interactions with brands.

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However, just because customers prefer the option to engage brands on multiple channels, that doesn’t mean they want to be forced to switch between channels to resolve their issues. As SQM research highlights, the vast majority of customers want their problems resolved on first contact. A full 93% expect resolution without changing channels when they call the contact center, and 72% expect it when they reach out via the company website.

This presents a conundrum for many contact centers: Omnichannel service is essential, but channel hopping is largely seen as a negative. The question, then, is how a brand can offer a robust omnichannel CX without sending their customers hopping down an endless rabbit hole in search of answers.

While there are many ways to address this challenge, conversational AI is particularly potent for improving service — especially self-service — and minimizing channel hopping. But grabbing this benefit of conversational AI requires not only that you leverage the technology but also use conversational IVR and chatbot testing to ensure effective CX.


What Is Channel Hopping?

In customer service, channel hopping refers to any instance in which a customer has to switch from one service channel to another. For instance, they might start an inquiry in an online chat widget but request a call from an agent when they can’t get their questions answered.

Channel hopping, also known as channel switching, can occur for many reasons, none of which typically bode well for CX. Consider just a few possibilities:

  • Channel/service preferences: A customer might start their inquiry online only to change channels when they realize they’re dealing with an incompetent chatbot.
  • Long wait times: Response delays may cause a customer to give up on a specific channel before they’ve even connected.
  • Complexity: If it becomes clear that an IVR, chatbot, or live agent isn’t able to address their issue appropriately, the customer may try a different avenue.


Clearly, these aren’t situations in which these customers are happy about switching — they’re doing so out of frustration. By the time this type of channel hopping occurs, these customer relationships are already off on the wrong foot, and the costs will accumulate quickly. Forrester reports that these types of escalations cost online retailers $22 million on average.


The CX Opportunity of Channel Hopping

The risk of souring the customer relationship is even greater when you consider that the act of channel hopping itself is often cumbersome. According to a survey by Gartner, customers find that 62% of channel transitions are “high effort,” meaning they have to repeat information, endure long waits, or still fail to have their issue resolved in the new channel.

Reducing the effort involved in channel hopping can, in many cases, decrease the costs and damage to CX. When these transitions become more seamless, 93% of customers still report high satisfaction. Particularly when handoffs between self-service and agent-assisted channels are handled well, customers tend to spend even more time in self-service channels.

This leads to an important caveat: It’s not necessarily that channel hopping is bad in and of itself. When it’s handled well, it can actually improve CX quality. Thus, the goal shouldn’t be to eliminate channel hopping entirely but to use conversational AI (among other tools) to drastically reduce it and improve the experience when it does occur.


The Purpose of Conversational IVR and Chatbot Testing

Conversational AI presents a unique opportunity to enhance customer self-service channels and support human agents when they need to step in. Whether it’s your IVR or chatbots, well-designed and trained conversational AI can effectively resolve many customer inquiries and prevent channel hopping. When it reaches its limits, it can still gather sufficient information and pass it on to an agent so they’re well prepared to engage the customer in the next support channel.

However, we can all name plenty of support experiences with AI that didn’t quite go that way. The conversational IVR that keeps sending you to the wrong menu. The chatbot that simply can’t understand what you’re asking, no matter how many ways you put it. Or the agent that appears to have no information from the 20-minute chat you just had with the bot.

None of these scenarios leads to a pleasant channel-hopping experience, and they all have one thing in common: poorly trained conversational IVR systems. In many cases, this comes down to a misunderstanding of the customer’s intent or a failure to properly collect information.

Chatbots aren’t hardwired to pick up the countless nuances of human communication. They have to be trained to understand that something like “want $ back” is the same as “Can I have a refund on this item?” Or that “rep” means “Can I talk to an agent?”

Conversational IVR and AI chatbot testing helps you discover where your AI’s intent understanding falls short so you can inform it and build up its natural language understanding. It can also help you pinpoint gaps in your bots’ handoff capabilities — places where the necessary information isn’t getting passed to human agents.


Reduce Channel Hopping with Cyara

No conversational AI is complete without comprehensive testing support. Cyara Botium is uniquely designed to cover myriad testing and training scenarios to help you improve self-service, reduce channel hopping, and enhance CX throughout the customer journey.

Botium can help you bolster your bots by collecting customer inquiry data and building test cases based on that information. It simulates human quirks and flaws and can introduce background noises, accent variations, and more to test your IVR system’s understanding capabilities. It can also ramp up test volume to see how your AI performs under pressure.

By automating AI chatbot testing with Cyara, you’ll gain a much clearer picture of your conversational AI’s flaws — and be equipped with the tools to fix them. On average, companies see a 10% boost in call containment and a 71% increase in customer satisfaction when they test and train their bots with Botium. Ultimately, this drives greater self-service and Improved brand sentiment, enabling you to make the most of today’s conversational AI technology.

Ready to put a stop to high-effort, unnecessary channel hopping? Contact us today to learn more.