Conversational AI User Experience – Conversational AI is disrupting the way of working and doing business, by making human-machine interaction easier through natural language.

Conversational UI are not only meant to automate repetitive tasks, but also to change the way human solve problems, leveraging technology.

As declared by Alex Harper, Conversational AI COO at Deloitte:

“Conversation is the only interface everyone already knows how to use”

Halper, 2021

This would explain why 74% of organization agree that conversational AI agents are business and customer engagement strategy’s key enabler and 76% of these have already realized measurable benefits from voice and chat assistants (Press, 2019).

Conversational AI may be employed in every market and business function, but the one that is  already in the early stages of disruption is customer support. 

Conversational AI user experience in contact centers

Conversational AI User Experience – Contact centers are a “cost center” for organizations, expecially for the high turnover of employees that is up to 44% according to CallMiner.

Conversational AI can scale call centers’ capacity, allocating resources on more qualified tasks, and contributing to turnover reduction.

Conversational AI agents, made with, take in charge multiple requests at a time and operate 24/7, maximizing customer satisfaction and user experience, thanks to an autonomous understanding of over 98% of conversations, with no need of humans to intervene.

Conversational AI provides additional value by automating up front authentication and query routing / due diligence: these menial tasks can mean millions in savings for companies and millions of minutes saved for queuing customers (Press, 2019).

Also Conversational AI contributes to the agents’ daily job, working with them as an hybrid workforce.
With a concept called human-in-the-loop (or handover ) agents can monitor bot conversations live and intervene when necessary. On the other side, the bots can ask for help for a specific request and once the human agent provides the correct answer for the customer, the bot learns how to handle the same query on its own, the next time. Also, while agents take over the conversation, conversational AI agents, actively suggest and provide a preview of the correct answer to give.

building relationships with conversational AI: possible risks

It is fundamental having very well performing Conversational AI agents, in order to not compromize customers’ relationships and customer’s satisfaction rates.
The average of solutions currently on the market have an understanding capability and autonomy in conversation handling between 60% and 80%.
This means that, best case scenario, 1 customer out of 5 may be unsatisfied and have a bad opinion of the whole conversational AI agents category.

Infact, once a customer has tried your conversational solution and determined its ineffective, they are significantly less likely to use the tool again (Halper, 2021).

Also, companies will be disappointed with the performance of the solution implemented and the failure of the investment they have made.
This is way it is important to choose the right platform and the best vendor, that should be able to prove the effectiveness of a conversational AI deployed solution in terms of results achieved in at least one year production and proven performance in terms of conversation autonomous understanding.


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