There has never been more pressure on businesses to deliver fast and efficient customer service. For proof, look at any number of studies that have found modern customers not only want rapid responses when they reach out to organisations but demand it.
- 90% of customers consider instant customer service crucial or very important1
- 33% of consumers feel most frustrated by waiting on hold, while a further 33% are equally frustrated by having to repeat themselves to different support representatives2
- Nearly 80% of Americans nominate speed as one of the most important elements of a positive customer experience3.
Speed alone is not enough though. Customers also expect personalised responses and when it comes to seeking immediate assistance, they do not care if it is the weekend or the middle of the night. Our 24/7 culture has created an environment where the only way to guarantee positive customer experience scores is to guarantee customers can quickly connect with them, regardless of the time of day or night.
For these reasons, conversational AI is fast becoming a must-have technology for forward-thinking organisations. The use of Large Language Models (LLMs) to simulate human conversation allows businesses to offer seamless, around-the-clock support to address customer concerns in real-time and handle exceedingly high numbers of enquiries and personalised recommendations.
This article is a one-stop resource for executives and managers keen to learn how conversational AI works, how it differs from traditional chatbots and the myriad of ways in which it can be applied. Crucially, it will also provide businesses with the evidence they need to stop thinking about the future of customer experience and instead adopt the technologies they need to stay ahead of their competitors.
What is conversational AI?
Conversational AI is a form of artificial intelligence that facilitates interactions between humans and machines. While chatbots have traditionally been limited in functionality (eg, handle simple tasks and offer pre-written responses), technological advances such as LLMs are enhancing conversational AI by facilitating the ability for the technology to understand, empathise and respond with rich vocabulary.
Source: Conversational AI in Customer Service: Need, Benefits, and More (ameyo.com)
What is the difference between conversational AI and chatbots?
It is not uncommon for people to use the terms ‘chatbots’ and ‘conversational AI’ interchangeably, but there is a world of difference between the two technologies. While traditional chatbots have played a key role in the evolution of customer service, the continuing development of conversational AI is shining a spotlight on their limitations.
Basic chatbots use NLP to understand queries and respond accordingly, but they are rule-based, which means they are trained to answer only specific questions. The inability to access information outside its programmed knowledge is why customers often encounter the frustration of being greeted by a generic response such as: “Sorry, I don’t understand.”
Conversely, conversational AI integrates artificial intelligence to enable ‘smarter’ chatbots that can have more human-like conversations. Crucially, conversational AI is two-fold. One option is using AI and other tools in a programmed way to create a more human-like experience. Alternatively, conversational AI can use a pure LLM that runs free and enables wide-ranging and complex dialogues.
Both create conversations that sound nuanced but they have different constraints. Using a programmed approach means businesses can tell it what it is allowed to do but it can only do that, whereas incorporating LLM will enable it to do anything unless a guardrail or prompt is in place to forbid it from doing so. The result? The need to employ a lot of rules to close avenues and, of greater concern, the risk of negative impacts if one is missed.
What cannot be denied is that conversational AI has delivered immense benefits for consumers, with MIT Technology Review reporting that more than 90% of businesses have seen significant improvements in complaint resolution, call processing and customer and employee satisfaction through its use4.
What are the use cases for conversational AI?
Conversational AI’s versatility and effectiveness are evidenced by the number of industries to which it can be applied.
Retail –
Few sectors are made for conversational AI quite like retail. The technology’s ability to provide personalised assistance, guide online shoppers in real-time and assist with tracking orders has been a key driver in enhancing the modern eCommerce experience. Crucially, it is also playing a vital role in the back end by improving inventory management, processing returns and collecting feedback. Customers also benefit from 24/7 support, tailored promotions and optimised marketing strategies.Healthcare –
Digital banking is on track to become a superfluous term, with younger generations having grown up in a world where the only banking they know is ‘digital’. This means a huge demand for streamlined and efficient automated options that eliminate cumbersome request processing and enhance instant online support. Conversational AI virtual assistants are answering the call by accompanying banking customers on every step of their journey. The technology is also helping combat the scourge of fraud, with the likes of knowledge-based authentication and voice biometrics adding unprecedented layers of protection.
Customer service –
Conversational AI is high on boardroom agendas as executives and managers seek the twin triumph of enhancing customer support while reducing costs. Its ability to learn from interactions means it can deliver more accurate and appropriate responses to customer questions while simultaneously allowing human agents to focus on more complex enquiries. Integrating the technology into CRM systems also ensures it can develop a clearer picture of a consumer’s history and deliver personalised advice and solutions.Sales and marketing –
Conversational AI is hugely beneficial for existing customers but do not underestimate its value in helping businesses convert potential customers into active ones. By gathering crucial customer data during interactions, it can provide sales teams with vital insights into customer preferences and allow them to tailor marketing strategies accordingly. Evaluating sentiments, pinpointing common requests and collating feedback are all key steps in conversational AI’s journey to enhancing data-driven decision-making.Real estate –
the modern real estate market thrives on potential buyers’ search experience and conversational AI is transforming the playing field. Tech-enhanced virtual assistants can identify user preferences to recommend properties based on budgets and locations, while the ability to offer 24/7 customer support is boosting client engagement and reducing the workload of human agents. Throw in benefits such as AI-supported document management, contract processing and market updates and it is clear why forward-thinking agencies are investing heavily in conversational AI.Conclusion
Conversational AI is a game-changer, just as Convai is changing the game with its ground-breaking interactive voice response (IVR) system. Oration uses advanced AI-powered speech recognition to provide organisations with an automated telephony system that interacts with callers, understands intent and routes calls to the appropriate recipient. Forget about pre-recorded prompts and touch-tone keypads. Oration is using AI-powered solutions to take IVR to the next level.
Ensuring AI’s safe and ethical use is paramount to harnessing its full potential while mitigating risks. Learn how to use AI safely and the zones where keeping a tight rein is non-negotiable.
