Chatbots and Virtual Assistants
The challenge with chatbots
As humans, we converse naturally with people every single day. We talk to anyone from peers and colleagues to complete strangers to socialise, resolve enquiries, share insights, and get work done. Inadvertently, chatbots have an immensely high bar to meet. They are a tool designed for resource-crunched organisations to provide human assistance, and are increasingly expected to be able to converse as naturally as a human.
However, most are far from providing services similar to a human agent. Many rule-based chatbots can sustain simple dialogues to fulfil an informational function within their learned set of knowledge. They require explicit training to be able to understand specific utterances, to then command a manually-crafted response. This makes it difficult for them to scale to meet the natural diversity present in human language and interaction.
What are chatbots, virtual assistants and conversational AI?
Chatbots vs virtual assistants: differences explained
Within the industry, chatbots (rule-based chatbots) and virtual assistants (AI-based chatbots) are understood to have different capabilities, particularly in the tasks they can execute. The key difference is in the scope of work they are able to perform.
The standard chatbot is typically rule-based and built to provide scripted answers or actions to a defined list of questions. It may use conversational AI algorithms, but to a more limited extent. They perform well in a limited domain, such as information acquisition and customer Q&A. Often, they are unable to learn well on their own or with minimal resources, and require reconfiguration to be optimised.
Virtual assistants are AI-based chatbots that function more similarly to human assistants. They are far more advanced in their use of conversational AI, such as with the use of Natural Language Understanding. This makes them able to sustain dialogues, accurately understand intent and context behind utterances, and learn from real interactions without explicit training. Scalability is an important differentiating factor, as they’re able to take on more than just navigational tasks, such as transactions and decision-making, and are more easily maintained.
Features of virtual assistants
- High language processing capabilities
- Accurately understands intent and context
- Learns from real interactions without explicit training, enabling it to improve over time
- Multilingual and may understand slang and spelling mistakes
- Compatible with various integrations
- Applicable to a wider scope of use cases
Why virtual assistants matter for organisations
This rapid adoption and maturation of chatbot technology has raised the expectations for both customers and administrators. These expectations are not those of speed, efficiency and accuracy alone but the ability to address diverse customers, provide business insights to partners and function seamlessly and efficiently in cross-functional matrix organisations. And of course, do more than just having dialogues.
Virtual assistants can be employed for customer-facing operations, to assist employees in their everyday tasks, or a blend of both. Below, we list out some examples and modern day applications.
Virtual assistant use cases and applications
- Whole-of-organisation or enterprise virtual assistant
- Enterprise data collection virtual assistant
- Customer-facing insurance virtual assistants
- Hotel concierges
- Ecommerce recommendation chatbots
- Virtual sales representatives
- Virtual tour guides
- Virtual trainers or coaches
- Sales and marketing virtual assistants
What is Omnitive Converse?
Omnitive Converse is TAIGER’s Conversational AI platform that allows you to build and manage Virtual Assistants. These bots are autonomous, always-on representatives of your business that can help service your customers or employees needs across a wide variety of scenarios.
Omnitive Converse Bots are able to
- Interpret and answer user questions
- Guide users to relevant information
- Perform transactions on behalf of users
For example, a HR Bot can be configured to help your employees process their expense claims and a Customer Support Bot can help answer frequently asked questions and reset a customer’s account password.
At a glance: features of Omnitive Converse
Omnitive Converse allows you to create engaging conversation experiences, and allow your customers and employees to become more productive.
The core modules found in Converse are:
- Intent Dashboard – to manage the list of intents for the Bot
- Intent Editor – use for building content and conversations
- Libraries – for organising and access control of the intents
- Bots – to manage the Bots and making changes to look and feel for each Bot
- Common Space – a knowledge base where Bots can share common intents
- Unhandled Phrase Manager – for triaging of unseen phrases
- Analytics – to visualising the performance of the Bot
- Plugins – to manage the different plugins uploaded in Converse
- As chat has become ubiquitous and accessible to users of all skill levels, no training is required for end-users to interact with Bots you create.