Conversational interfaces have the potential to enhance customer satisfaction and increase customer engagement, effectively managing various aspects such as online customer service, real-time social sales, and marketing automation.
This explains why businesses eagerly embrace AI chatbot solutions. However, there is a multitude of buzzwords to consider, such as chatbots and conversational AI.
Are they distinct from each other or essentially the same?
The abundance of options can be overwhelming when it comes to assessing them and actually developing something. Rest assured, we are here to assist you in understanding and navigating through it all.
While these terms are often used interchangeably, there are some important distinctions to make.
What are Chatbots?
Chatbots are a type of software designed to conduct online chat conversations via text or text-to-speech, in place of direct human interaction. These bots are programmed with a predefined set of rules and responses (a script, basically). Depending upon the input (queries from users), they generate responses following their programming.
Simple chatbots are effective in managing a narrow range of tasks. They rely on rule-based programming to match user inquiries with potential responses, usually for fundamental frequently asked questions (FAQs). However, the limitations of basic chatbots become evident when they encounter an unfamiliar request for which they lack predefined instructions. In such cases, they are unable to provide assistance and will respond with a generic "Sorry, I don't understand" message.
To cater to the needs of bigger enterprises such as banks, fintech, insurance and telecommunication companies, etc, chatbots require artificial intelligence to augment their capacity to comprehend human language and execute intricate tasks and transactions.
Within the realm of chatbots, this field of artificial intelligence is referred to as conversational AI, which we’ll get to a little later.
Benefits of Chatbots
24/7 Customer Support: Chatbots are available round the clock, making them useful for providing instant responses to customer inquiries.
Cost-Efficiency: They reduce the need for human customer service representatives, leading to significant cost savings for businesses.
Scalability: Chatbots can handle thousands of chats concurrently, something human agents can't manage.
Limitations and Disadvantages
Limited Understanding: Rule-based chatbots can only answer queries they are programmed for. Any deviation from the script often results in the bot failing to comprehend the user's intent.
Lack of Personalization: Most chatbots are not capable of understanding user context or providing personalized responses.
Examples of chatbots include WeChat’s Xiaoice, and basic customer service chatbots on websites or social media apps like Facebook, which are usually rule-based.
What is Conversational AI?
Let’s get to the bread and butter.
Most chatbots rely primarily on text-based interactions, meaning they depend on users typing input in order to generate responses.
It's worth noting that historically, the term "chat bot" referred to a bot designed for online chat rooms rather than a bot for informal conversations. While some individuals classify voice-based virtual AI assistants like Amazon's Alexa as chatbots, others are hesitant to categorize them as such.
Given this ambiguity, what should we label these devices?
A suitable umbrella term is "Conversational AI." It encompasses AI engines, systems, and technologies utilized in chatbots, voice assistants, and conversational applications. This broader term helps capture the range of functionalities and applications involved.
Conversational AI refers to the use of messaging apps, voice assistants, and chatbots to automate communication and create personalized customer experiences at scale. It leverages technologies like Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning to understand, process, and respond to human language in a natural and engaging way.
How is Conversational AI Different?
At first glance, basic chatbots and advanced conversational AIs may appear quite similar. Both possess the ability to engage in conversations with individuals, and in some cases, they can yield the same outcomes.
Nonetheless, many business leaders express concerns when it comes to implementing bots. Approximately 47% of them worry that bots still lack the ability to fully comprehend human input.
However, there is a crucial distinction to be made. While a traditional chatbot merely repeats pre-defined responses, an AI system can genuinely grasp the context of a conversation and provide more natural and contextually appropriate replies. The natural language processing capabilities of artificial intelligence engines enable them to better understand human emotions and intentions, allowing them to engage in more intricate dialogues.
For instance, conversational AI possesses the awareness to distinguish between customers who are enthusiastic about a product and those who are expressing anger and expect an apology.
Artificial intelligence (AI) can also utilize intent analysis to determine the purpose or objective behind messages. For instance, when someone writes, "I'm looking for a new smartphone," it is likely that their intent is to make a smartphone purchase. On the other hand, if someone writes, "I just bought a new smartphone, and it doesn't work," their user intent is likely to seek customer support.
This solution is continuously advancing in sophistication, indicating that in the future, AI will have the capability to fully handle customer service conversations. Implementing AI technology in call centers or customer support departments can yield significant benefits. It enables business owners to focus on more complex matters, while AI handles interactions with customers and users, freeing up their time and resources.
Benefits of Conversational AI
Understanding User Intent: Conversational AI platforms are capable of understanding complex queries, interpreting user intent, and delivering more accurate responses.
Personalized Experiences: They can remember past interactions and use them to provide contextually relevant and personalized responses.
Human-Like Interactions: Thanks to advancements in NLP, these systems can carry on human-like conversations, thereby improving the user experience.
Limitations and Disadvantages
Cost and Complexity: Developing a conversational AI system can be complex and costly as it requires significant data, advanced machine learning models, and continuous tuning.
Data Privacy: Conversational AI systems often require access to user data to provide personalized responses, raising privacy concerns.
Examples of conversational AI include Apple's Siri, Google's Assistant, Amazon's Alexa, and Microsoft's Cortana.
While the end goal of both chatbots and conversational AI is to automate and enhance interactions, their approach, capabilities, and complexity differ significantly.
Chatbots are more scripted and follow a predefined path, while conversational AI uses advanced technologies to understand and generate more natural and contextual responses. While chatbots can handle simple requests, conversational AI can manage complex interactions and even engage in human-like conversations.
On the flip side, conversational AI requires more investment, both in terms of time and resources, than chatbots. Moreover, data privacy concerns can also be more significant with conversational AI as they need more user data to function effectively.
The choice between a chatbot and conversational AI largely depends on the specific needs and resources of a business. For simple, straightforward tasks, chatbots might be a cost-effective and efficient solution. For more complex, personalized, and engaging conversations, investing in conversational AI might be the way forward.
Do you think you are ready to start building your own conversational AI agent to grow your business? Book a free call with us to learn how we can help!