What are the benefits and challenges of using AI chatbots for customer service?

Reflecting on my journey as an Engineer with the AI Chatbot team at Kubiya.ai, I've learned that deciphering user intent can be one of the most complex challenges we encounter. Focusing on the user's desires often serves as the linchpin, aligning other components in the process. This is precisely why the concept of NLU (Natural Language Understanding) is gaining momentum in our discourse today. For superior NLU, I highly recommend the following: * Investing in effective embeddings systems. * Deploying top-tier classifiers. * Prioritizing exceptional prompt processing. These tools form the foundation of our armory, empowering us to tackle the complexity of user intent head-on.

Chatbots for customer service have come a long way, but there is still work to be done. As someone who worked on a chatbot for software developers, I understand the challenges of creating an effective chatbot. One major issue is the impatience of customers who expect immediate results. Think of every time Alexa tells you the weather instead of shutting the lights off like you asked. However, as AI technology improves, chatbots are becoming more reliable and efficient. In the very near future, it's possible that people will look forward to interacting with chatbots on websites or online because they know they will receive excellent service. Although we're not quite there yet, the future for chatbots in customer service looks promising.

Having advised on and delivered dozens of contact center optimization programs using AI chatbots, here are the two sides of the coin Works very effectively for both the customer and the organization when the customer intent is very clear and the action required is very simple and the action required is basic (eg update my address, provide balance outstanding, email me a claims form.....etc) Needs a lot of work training the chatbots when the customer intent is nuanced and the action is quite ambiguous (eg explain why my premium has gone up 20%) How does one deal with it? Create an effective Triage model upfront using NLP algorithms that can accurately spot the intent so that complex intents are farmed out to a human

As a customer its very annoying when you dont get a resolution for a problem, but with AI chatbots going through a lot of learning and able to solve atleast the first step problems, it very beneficial for organisations to use them effectively. However, there has to be an option to escalate to a human if the AI chatbot is unable to solve the problem and that is lacking in many of these integrations. The benefit of 24/7 availability and instant responses mimics care. Chatbots struggle to understand and respond accurately to ambiguous, complex customer queries. They rely on predefined scripts, patterns, which can limit their ability to address evolving customer needs and varied linguistic challenges.

Always remember that the customer likes speaking to a real person. That moment they discover it’s a robot can be detrimental to your business. Coming from the world of brands, I recognise how somebody handles a customer, complaint or a question is best delivered in the same tone of voice as your entire brand. So if you’re using AI, always ensure that it embodies the spirit of what you stand for. Always ensure that every consumer touch point talks the same language and in the same style.

AI chatbots also aid in accessibility by offering these 1. Text typing interface for hearing impaired users by leveraging textual communication, speech to text and text to speech. 2. Voice interface for visually impaired users by leveraging speech to text. 3. Voice interface for non native English language users. They can ask in any language they know and get the support back provided the language support is baked into the chatbot platform.

While AI-powered chatbots have some utility, in my opinion, the current buzz about their benefits is exaggerated. Most of today's AI-powered customer service chatbots are no more than a fancy natural language UI on top of the website's existing customer support features. A customer can generally navigate the website's support functionalities using the traditional web UI. When they seek assistance, they typically require a higher level of actuation such as handling exceptions, fixing errors, or authorizing managerial decisions. That’s where the chatbots often frustrate customers, concealing the actuation limitations. Instead, swiftly connecting the customer to a live representative tends to enhance the overall customer experience.

Save time for the customer, save them money by saving the company money, reduction of confusion due to accents or moods, data can be easily leveraged retrospectively, and to give the customer more autonomy.

From a UX Designer's perspective, an AI chatbot is a valuable tool in the pocket that serves both - the customer by enhancing the experience, as well as the business. Let's take a look at several poignant examples: - comparing the 24/7 availability, unlimited by time zones or business hours AI chatbot with typical business hours, - delivers instantaneous responses, while the human counterpart has a queue and a waiting time to respond, - adeptly manages high volumes of customer inquiries while unearthing data-driven insights from user interactions and behavior patterns, and offers a wealth of insights for strategic decision-making, - ensures a uniform brand tone and style in standardized responses (e.g. seamlessly achieved in the Flo app).

In my experience which has only been since November 2022. I’ve seen the pros and cons. As a job seeker it’s helped me with mock interviews and I see the lack of the human touch. I still needed to revise many parts of my content to add that personalized element but it definitely speeds up the process. When it came to drafting articles, tailored cover letters, and career summaries I feel more confident with my work and content. It’s a big support to me and makes my work look more refined and professional.

AI chatbots, while efficient, pose ethical challenges such as privacy, consent, transparency, and accountability. It's crucial to only collect necessary data and protect it from misuse, with customer consent. Customers should also be aware when interacting with an AI. Clear responsibility lines are vital if errors occur, and systems must be monitored for bias or unfair treatment. Ethical considerations should be an integral part of chatbot design and deployment, ensuring a future that respects human rights and values.

While AI chatbots can deliver efficiency and consistency, they lack the adaptability and nuance of human interactions. Customers want to feel understood as individuals, not just input-output machines. Rigid chatbots struggle with open-ended conversations and grasping context and intent. They may fail to pick up on non-verbal cues like sarcasm or frustration that humans would notice.

Irrespective of technical intricacies that cause the malperformance of the bot, customers can initially be revolted when their queries fail to reach a real person, causing an immediate loss of personal touch. Furthermore, they must embark on a learning curve to effectively communicate with the chatbot as the bot needs simple wording, so putting the problem in large blocks of text may present itself as useless as the bot will have a hard time understanding the intent. Empathy often falls short in the chatbot's design and linguistic capacity, leaving customers feeling misunderstood. Privacy concerns come to the forefront when the users feel a reluctance and distrust to share data with a chatbot versus a human counterpart.

An AI Chatbot can likely be tuned to yield fuzzy results to simulate context clues/nuance, but every once in a while, customers will be misinformed or be unable to accurately describe what they need from Support. And in those cases, tribal knowledge, customer service experience, or simply prior run-ins with the same mistakes from other customers will be the key piece of information that leads to a timely resolution.

It's the compassion & empathy for me. AI could never. AI could not pick-up on the subtleties from my external & internal customers. The human touch will and should always be valued when dealing with humans.

Chain GPT plugins and other AIs/autonomous agents to do more in the backend for the users of your chatbot and you will take its potential to the next level. Skate to where the puck is going.

Most problem-solving techniques rely on analyzing historical conversational data to improve chatbots. But we can go beyond past limitations by proactively stress testing chatbots using generative AI capabilities. Specifically, leverage large language models to automatically generate edge case conversational scenarios that users may encounter. For example, craft dialogues with complex multi-step requests, niche vocabulary, and unusual contexts. Feed these simulated dialogues into your chatbot to assess how it handles new complexities it hasn't seen before.

Depending on the overarching business goal, a Pareto analysis would be a good starting point when looking for e. g. scaling potentials. Distilling data to determine which customer inquiries have the biggest impact, finding relevant data that measure the impact, and developing features that address those inquiries. As for the 5 Why and Ishikawa diagrams, they are standard parts of the 8D Report of customer complaints in the automotive industry. In my experience, the challenge is that they all take an interdisciplinary approach, allocating resources. This is why it would be interesting to see the customer going through the 5 Why with the AI chatbot and at the end the customer would get a set of possible solutions and measures.

AI definitely has benefits in some industries. In my professional opinion though, there will never be a replacement for human eyes and human thinking/problem-solving. Knowing and understanding how to professionally and effectively communicate is a key part of career and organizational growth.

I believe the real challenge is that the absence of emotional support, empathy and compassion. While the good thing is eliminating the waiting time and reduce the AHT for new cases.