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Is it time for your call center to use conversational IVR?

18:59 07 October in AI in the Call Center, Artificial Intelligence, Call Center, Customer Experience, IVRs
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Last updated on October 16th, 2020 at 06:16 am

The advantages, disadvantages, and 5 realistic use cases for conversational AI

When it comes improving and enhancing customer service and support processes, AI holds incredible promise for both support and sales call centers. Especially with discerning customers wanting service quicker, faster, and as stress-free as possible.

(Also Read: What is Conversational IVR? And how can it improve customer service?)

Like with any technology however, it is unrealistic to assume that Conversational IVR can be used effectively in every scenario. I’ve noticed that for rapidly evolving tech such as conversational IVR, decision-makers often find it tough to distinguish between what is ready now, versus what is possible in the future.

In this blog, I try to take a balanced approach, weighing both the pros and cons of conversational IVR before delving into the best business use cases for the technology. Wherever it is relevant, I’ve also mentioned other automation options that might solve your business pain points more appropriately than conversational IVR.

Benefits of Conversational AI

Let us first look at the big advantages that conversational AI offers

Undoubtedly, conversational IVR is a fantastic tool.

  • It reduces queues and customer wait times while enabling cost optimization for businesses.
  • In comparison with physical agents who can only handle limited calls, automation with conversational AI can lead to unlimited volume handling.
  • Moreover, you can use the same AI across all your text and voice channels leading to consistency and software redundancy.

However, this does not mean you can use this technology indiscriminately.

Drawbacks of Conversational AI

As is the case with a lot of technology, Conversational AI too is effective only when used in the right customer support and service situations. Here are some caveats to keep in mind when considering the technology.

 

No voice AI has passed the Turing Test.1 Did you know that even Siri is unlikely to pass the Turing test? In other words, we can’t expect to carry out a full-blown conversation with a bot anytime soon. Although a lot of us are now comfortable with voice assistants in our home, we tend to keep our sentences short while speaking to Siri. But our customers often need more human conversations. Especially since many turn to a phone channel only after they have exhausted other means of solving their problem.

 

Errors may damage customer experience. While error rates may be forgivable and non-consequential when you’re telling Alexa or Siri to change the music or answer a question, it can easily anger a customer calling your call center with an issue. In this case even the smallest margin for error can damage your customer experience.

 

Your AI is only as good as your data.  An AI-powered conversational IVR solution is only as “intelligent” as the data it gets. If you do not have enough training data, your solution will not give optimum results. (Also Read: How to develop a voice bot for your sales or support?)

 

When should you use conversational IVR?  

 

In spite of the drawbacks, there are still a plethora of use cases where Conversational AI can make a huge difference to productivity without affecting, and in fact often improving, customer experience. Let’s take a look at these five use cases that are primed to making good use of conversational AI.

 

Use Case 1: Quick Data Capture

Whenever there is information flow from a CRM or database in the backend to an agent and then to the customer, Conversational AI can help do away the agent leg and automate it instead. For instance, lets take the case of cancelling a reservation or changing a delivery instruction. These tasks can be completed faster when a customer interacts with a conversational IVR.

 

This also includes use cases when you need to capture data that cannot be conveyed via DTMF inputs. For instance, descriptive feedback surveys, or user details like names and addresses.

 

Use Case 2: Straighforward communications

Whenever there is a standardized set of options, a conversational IVR is good idea.  For instance, when placing a pizza order, a conversational IVR can easily replace the human agent. (Though the system should always have the option of quickly routing to alive agent in case of any errors or complications)

 

Use Case 3: To replace long menus.

Because they are not limited by DTMF inputs, long multi-level menus can be simplified by conversational IVR. These are especially useful for banking, finance, and travel sectors.

 

Consider, for example, when you call a bank for a home loan. First, you need to select which department to connect with (dial1 for credit cards, dial 2 for loan and mortgages, dial 3 for banking related queries, and so on.) Once this is answered you might have to listen and select from a new set of options regarding which loan you want to know about (1 for home loan, 2 for student loan, 3 for personal loan) and so on.

 

In contrast, you can just tell a conversational IVR that “I want a home loan” or “ I want to know about the Egypt Holiday package”, and it should connect you to the right department.

 

Use Case 4: Collection Calls

Speaking of the use of Conversational AI in verticals such as the financial sector, Sagar Rane, who leads Ozonetel’s business teams in India West, and UAE, had some great insights about the use of AI for customer support and service activities like collections. He goes on to explain how conversational AI solutions can be effectively used in debt collection calls. These calls are otherwise notoriously unproductive and often unpleasant. In fact, research suggests that out of every 2,500 calls dialled, only 1000 connect, out of which only 200 may respond positively, and 200 may want to ask the agent something. Moreover, customers may prefer to hear about a pending loan payment from a bot rather than a human being.

Also Read: How debt collection work can greatly benefit from AI.

Use Case 5: For candidate screening

Another extremely viable use case for conversational AI, as Sagar states is for Human Resources. Here, the cumbersome job of candidate screening can be handed over to a chat bot. In fact for clients who have used this solution, their candidate reach out has become nearly 10 times faster, and led to a 40% reduction in cost per hire!

 

When should you avoid conversational IVR?

  • For a very diverse audience

Conversational IVRs are available in a multitude of languages. So it isn’t difficult to handle many different audiences with this technology. But within a single language, speaking styles and accents may vary greatly.

In these kinds of cases, explains our presales expert Namisha Gupta, Conversational IVR should be avoided. Namisha, who has successfully executed a number of self-service solutions, explains “In India, we’ve noticed that amongst amongst urban audiences, the speaking styles are similar. Whereas, for a rural audience, the dialects and speaking styles vary so much that the chances of failure increase.”

Therefore, when there is a lot of heterogeneity in the way a language is spoken, conversational IVR is not recommended. Here self-service can be delivered via DTMF input.

 

Also Read: How a logistics firm tripled their call handling capacity by implementing self service IVR with DTMF inputs.

  • For escalations

Does your customer primarily use the phone when they have an issue? Or do they prefer to use a digital chat? If your voice channel primarily handles escalations, then a conversational IVR is best avoided. (In fact, I recommend skipping the IVR and connecting to a live agent right away!) It’s important to understand your customer and place your self-service options on the channel they prefer, This may be as an FAQ page or easy to search video tutorials, a Chatbot or automated WhatsApp bots.

 

Also read: How to plan your self-service strategy?

 

Conclusion

We can conclusively say that if your call center has some simple conversations that need can be automated, then Conversational IVR is an excellent solution. It can reduce your call loads while ensuring a personalized and convenient customer experience. Like every successful implementation, the trick lies in identifying your problems correctly, and as always, deeply understanding your users, and their journeys.

 

Note: If you are planning to automate some of your customer conversations, Ozonetel provides excellent chatbot and conversational IVR and simple IVR solutions. Go to www.ozonetel.com for more information or contact a sales representative today.

 


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