6 features your voice bot needs for smooth conversations

What is a Voice bot?

A chatbot or voice bot, as the name suggests is a virtual ‘Bot’ or computer program that conducts a conversation. Powered by artificial intelligence (AI) and natural language processing (NLP), these Bots are designed to simulate human conversational patterns. These bots are used in a variety of practical scenarios such as customer service.

As mentioned, some chat/voice bots use sophisticated underlying technology such as AI and NLP. Some simpler ones scan for keywords from within a pre-defined database to extract a reply with the most matching keywords or wording pattern. Depending on how they are configured, bots can be highly differentiated with respect to their functionality and conversational quality.

Here’s a blow by blow of what differentiates one voice bot (or chatbot) platform from another. In other words, the key features a voice bot needs to ensure a smooth conversation:

1. Intent Analysis: the ability to understand meaning

This is perhaps the most essential criteria. Meaning and comprehension is everything during a conversation. Sadly, as human beings, we aren’t always literal or to the point when we speak. Given this inherent human irony, a bot should be able to use its ‘Intent Analysis’ (super)power to extract the meaning behind our words.

For example, the intent behind a “sure” or “why not” is most likely a “yes”. Conversely, “I’m good”, “later” and “not really”, likely translates to a “no”. These simple examples show that a chat bot’s job is rather nuanced. Today, as companies rely more and more on technology to ease the burden on human labor, chatbots or voice bots are common. As a result, these bots need to ensure that nothing is lost in translation!

To enable a successful transition to automation, voice bots need to be smart to carry out convincing conversations. They need to understand if they’ve reached the right person, they need to understand the sentiment of the person and act accordingly (e.g. schedule a later call or transfer the call to another department or agent, etc.). Here are some scenarios to provide more context:

Scenario 1: When the customer who receives a call is unable to speak and hangs up very quickly after a few words.

Bot: “Hello, this call is regarding your credit card payment for January 2019. Am I speaking with Mr. X?”

In all the above responses (except for the last one), the bot’s task is tricky. It needs to discern that the caller is unavailable for some reason and that the call needs to be rescheduled. A smart bot would politely thank the person on the other line and ends the call. The bot is mindful of the customer’s time, and in the back-end, it will schedule a call a few hours later to follow up.

Scenario 2: When the customer’s answer has multiple steps

Bot: “Hello, this call is regarding your credit card payment for January 2019. Am I speaking with Mr. X?”

Customer: “Mr. X, speaking. I’m busy. Call me in the evening.”

Here the voice bot or chatbot needs to comprehend and act upon 3 steps all in one go without having to repeat the question:

2. The ability to pause & listen:  Barge-in

The first point around intent comprehension makes it clear that the bar set for machine programmed assistants like chatbots and voice bots is rather high. While you want the bot to be a ‘good listener’ so it can determine next steps, or pause when the person on the other end is talking, you also want the bot to be able to make the reason of its call very clear.

For example, voice bots are frequently used to apprise clients of some important information or remind them of say, a due date. A good bot design would be one where the bot is programmed to not pause during that time when it’s providing critical information, even if it is interrupted. So as to make the intent of the call clear.

As illustrated in this article, AI-based smart bots can be a huge value-add. However, as also mentioned, they are here to assist and not replace core human-to-human interaction. There are some scenarios where bots should quickly differ to live agents. Tough negotiations, sensitive conversations, calming irate customers, for instance, are best handled by people as opposed to machines, no matter how smart they may be.

3. Streaming recognition

As with all technology, speed is essential for a pleasant, efficient experience. A good voice bot should, therefore, be able to interpret and act at the same rate at which the customer speaks. Lags and slow responses cause frustration and create a poor impression of the business.

4. Personalization

When a customer calls a business they want fast responses! This includes being able to unburden their problem to someone capable as soon as possible. So it’s frustrating to increase the number of steps a caller has to go through. For instance, after going through the trouble of calling a company,they need to navigate an IVR to identify themselves ( id number, account number, street address, etc.); select the relevant options to categorize the reason for the call, before they explain their problem.

Here, personalization is the key to improving the customer experience.

For instance, optimal integrations and programming should ensure that the bot greets the caller by name, knows caller history, picks up the likely reason for the call based on current and past calling patterns. Most importantly, a good bot should be able to personalize suggestions based on this type of customer knowledge.

5. Access to live agents

Voice bots are there to assist agents in meeting customers’ needs. They are not there to replace agents. At any time during a call, the customer should have a seamless option to speak to a live agent. Not to say that this should happen at the drop of a hat, but should be based on pre-define user-oriented fallback rules. For instance, if the bot can’t understand the customer’s issue within a single question, the customer or caller should be redirected to a live agent on priority. The last thing a customer wants is to be stuck with a bot that just doesn’t get it!

6. AI-powered to continuously learn

Understanding human speech is a complex bottomless pit. It’s a seemingly never-ending process. How often do we humans misunderstand each other’s words? In this regard, bots have come a long way. An AI-powered bot, for instance, understands this reality and never stop learning.

It continuously improves accuracy and predictability based on previous results. Currently, our bots are able to parse long sentences, understand slang or colloquial speech, comprehend a few multilingual words (without switching language modes). They cannot, however, understand sarcasm as yet!