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Build Intuitive Voice Bot with’s Meticulous Approach to Context Management

Few years back, voice bots were considered as elements of novelty in business development. Today, they have become an integral part of customer support and lead generation. The demand for voice-based bots has increased exponentially. Businesses are now opting to automate their customer support channels to meet the ever-rising customer demands.

By the year 2022, the business driven by AI systems will touch $3.9 trillion. This staggering number tells us that AI assisted voice bots are set to become a crucial part of business processes.

Users all over the world are already getting accustomed to the intuitive precision of voice bots. 71% of consumers are immensely comfortable using voice bots such as Siri and Alexa. What does this tell you about the growing acceptance of voice bots in business operations?

Emerging Trends of Voice Bots

Today, voice bots are implemented in businesses all over the world. But there is a serious dearth of bots that are capable of discerning the customer’s intent accurately.

In technological parlance, this ability to understand the intent of the conversation is called Context Management. It is, by the way, the chief factor differentiating sophisticated voice bots from mediocre ones.

The above example demonstrates how Andy misses out on the basic intent of Jim’s request. What would you attribute this error to?

Andy’s dull-wittedness?

No, Lack of training is the main reason why Andy is unable to discern the context of Jim’s order. understands the shortcomings of Andy perfectly well. After all, the intelligent voice bot, unlike Andy, is highly trained to participate in deeply contextual conversation.

So, what separates our solutions from the rest? It is our attention to detail in Context Management.

Let us explore’s approach to Context Management that enables the Voice AI to participate and solve even complex customer queries.

Establish Intent Perception

Intent is, in simpler terms, the context of the conversation. Discerning intent allows the voice bot to identify the objective of the query.

This is why is extremely careful in establishing the voice bot’s capability to perceive intent. To achieve deep contextual perception, we train our voice assisted bot with as many intent phrases as possible.

Taking the above example into consideration, the voice bot should be fed with phrases such as
“My bad”, “I’m sorry”, “Pardon” and so on. Along with that, appropriate responses and journeys should be assigned to these phrases. trains the AI assisted voice bot with numerous phrases and responses to make it more interactive. This practice ultimately enhances the holistic contextual perception of the voice bot.

Develop Follow-up Intent

Establishing the intent is not the end of the story. In fact, responsivity of the voice bot depends upon how we create the follow-up intent.

When Jim says, “My bad, I meant 10 apples”, Andy should be able to identify “My bad” and discard his earlier order. This identification of the intent is also called context identification. employs follow-up intent as a tool to allow the voice bot to remember the objective of the text throughout the conversation. This memory of context is called the Lifespan of a chat.

Typically, the lifespan of the voice bot is 4-5 statements. It means that the voice bot can successfully recollect 4-5 statements for each context.

By simulating the ability to recollect past exchanges, the voice chats are able to intuitively deal with complex customer queries.

Benefits of Context Management in’s Voice Bot

The intensive contextual training of the voice bot enables it to deal with all kinds of complexity involved in the customer support process. Below are some features that showcase how context management drives the voice bot to deliver a highly intuitive customer experience:

  • Recalls the context in case of a call drop
  • Identifies the context without having the caller repeating the query again
  • Swiftly switches the context when the caller moves from one topic to another
  • Holds and seamlessly recalls the previous context from the conversation

Final Words is known for its scrupulous training of the voice bots. We pay great attention to detail in adding dense training phrases, and responses. Furthermore, we are hugely invested in establishing a dense network of contextual data for precise intent identification.

This is why the AI-Assisted voice bot is more than capable of taking up at least 97% of customer queries and bringing them to conclusion by simulating intuitive interaction.

In the light of rising customer demand, integrating your business with a highly trained voice bot is a no-brainer. For businesses with long-term vision, employing a voice bot is nothing but a crucial step forward.

Akshada Benke

Senior content developer- Marketing

Akshada Benke is a content marketer at with more than twelve years of experience in digital content marketing field. She describes herself as a Philomath. She is confident & professional in developing strong consumer-insights driven goals to build brand and relationships.