Boost Customer Experience (CX) with Emotion AI Just in case you imagine that all chatbots are...
The most ideal way to bootstrap your chatbot building process is to employ ‘Flows’, where the Bot undertakes a singular pathway to communicate with customers.
Organizations that do not have the monetary resources or time to research, build and deploy an AI-powered chatbot tend to rely on flow-based Bots. Since the chatbot using flows doesn’t possess any supporting ‘intelligence’, the chatbot will function within a predetermined sequence.
To make it simpler, the chatbot merely guides the User/Customer through conversations (in the form of buttons or options) that are keyed in based on predefined parameters. For every selected response, there’s a defined pathway for the chatbot to pursue while communicating with the customer.
For a better understanding, look at the image below. It shows the Conversational Flow Diagram (Vertical) for a Highschool Chatbot that answers commonly asked questions by the students and staff.
Source: Master of Code Playbook Conversational Design Series #2
It becomes evident that the chatbot follows a pre-defined conversational rule or ‘Flow’ to guide a user towards a particular destination. However, what happens when the customer initiates a topic outside of this flow?
Here, the context of the conversational flow comes into question. Whilst Flow-based chatbots only ask closed questions to ensure the customer stays within the defined context, unique customer situations emerge as a hurdle.
Source: Google Images
Hence, Flow-based chatbots do not give the User/Customer any leg-room to receive additional information.
Flow-based chatbots are not accustomed to ‘Unnatural Flows’, like in the case of AI and Natural Language Processing (NLP) powered assistants. Since flow-based Bots follow a custom decision tree, it’s easy to maintain a lateral context in conversation. However, for chatbots using ‘Keywords’ in their Flow-based decision tree, an unknown word or phrase can lead to a breakdown in the conversational flow.
What about the Customer Experience? That’s a whole other can of worms.
A study by Salesforce showed that 23% of Customer Service companies are using chatbots to engage with individuals across diverse platforms and interfaces. And a statistics report by Userlike showed that 80% of the population have interacted with a chatbot at least once!
With more and more customers choosing to interact with chatbots, providing a seamless experience has become a driver for customer success.
Hence, chatbots must be able to provide help and support at all times. Answering a wide range of queries with meaningful information becomes a key metric for measuring chatbot effectiveness.
Flow-based chatbots fall short concerning EQ agility. Due to the strict pathway methodology followed by the chatbot, the assistants using a flow-based system often deliver empathetically poor responses or ‘Cold Responses’.
For chatbots in the Direct-To-Consumer (DTC) sector, maintaining an empathic and energetic tone paves the way for business conversions. In an environment where chatbots can directly impact revenue, seamless conversations become business-critical.
The very scale required to amass all of the required information, structure it into sequenced responses and chat out a flow is time intrinsic. And more time equals higher expenses.
And as the scale of chatbot interactions increases, the costs rise exponentially.
What if we told you that there was a cost-effective and scalable solution to beat this problem? A combination of AI-powered Conversational Intelligence and power-up flows, where conversation-flows get updated with just the click of a button.
Visit our website to learn more about how we’re helping organizations build and deploy chatbots in just 4 weeks.
You can also reach out to us to enquire about the product or understand how our suite of products can help your business.
