Editorial
Let’s face it: customer experience chatbots have been a major disappointment. They currently sit squarely at the bottom of Gartner’s Hype Cycle for Natural Technologies, July 2021 (“As an innovation does not live up to its overinflated expectations, it rapidly becomes unfashionable and attention wanes.”). GOMoxie found only 22% of consumers have a positive impression of chatbots. A Userlike survey found that the No. 1 thing that consumers want from chatbot experiences is the ability to escalate the interaction to a human. (Not a good look for the bot.) No wonder some research firms have called the current chatbot landscape a “failed revolution.”
Why, despite the millions upon millions of dollars of funding going into the space, have chatbots yet to provide anywhere near a level of experience warranted from such market hype? In my most recent book, "Experience Is Everything: Winning Customers’ Hearts, Minds, and Wallets in the Era of NOW CX," we dive into some of the major reasons behind the current chatbot disillusionment. I wanted to share a few of them below:
1. Chatbots (Generally) Fail at Empathy
Even when interacting with a bot, consumers expect to be treated like a human. But the current crop of chatbots are palpably robotic. Even the most beautifully scripted pre-written language that a bot pulls from can’t replicate the empathetic touch of a good customer service agent. And this makes a huge difference on the bottom line: Epsilon found that 80% of consumers are more likely to make purchases from brands that offer personalized experiences. Any CX leader looking to drive real revenue from their organization is digging themself a hole by putting too much faith in a bot’s ability to act human.
Related Article: A Good Chatbot Is Hard to Find
2. Bot Providers Overpromise and Underdeliver
In "Experience is Everything," a CX leader at a major manufacturing firm told us their bot provider estimated they could handle 30% of all in-scope tickets. It ended up only handling between 10% and 15%. Similarly, a rapidly growing male grooming brand saw initial success after assigning 11% of its ticket volume to a chatbot. It then attempted to increase that share to 35% — only to learn the hard way that the bot couldn’t resolve much more than its original 11% allocation.
Forrester Research recently noted that “chatbots may need months of care and feeding before they’re capable enough to handle a meaningful proportion of inbound queries” — a time-consuming and costly proposition that cuts against the notion that automation will free your customer service team to focus on higher value buyer engagement and eats away at the savings you might realize by automating support.
Learning Opportunities
Webinar
Apr
23
AI: The Essential Vitamin for a Healthy CX
Join us as we unravel the mysteries of AI adoption and discover the key to unlocking a thriving CX ecosystem.
Register
Webinar
Apr
23
Navigating Market Dynamics: Leveraging Reputation to Propel Business Growth
Join us to uncover the secrets of mastering reputation management in today's competitive environment.
Register
Webinar
Apr
24
The State of Outsourcing: At the Crossroads of AI, Quality, and Cost Savings
Learn how companies can maximize the results from their outsourcing investments.
Register
Webinar
Apr
30
Supercharge Contact Center Efficiency with Generative AI
Learn practical strategies to reduce post-call documentation time by over 8 minutes.
Register
Related Article: 4 Questions to Ask Before You Send in the Chatbots
3. For Being a 'Smart' Technology, Bots Aren’t Great at Learning
The whole promise of artificial intelligence is that it understands, learns and gets better over time. However, by far the most widely deployed type of chatbot today are rule-based chatbots. These bots hold basic conversations based on if/then logic, without actually understanding context or intent. They are scripted by human trainers: agents who map typical conversations, set up flows, and program decision paths based on common questions and their associated answers. From here, the chatbot will only work within the scenarios for which it was trained.
Sure, the human trainers can get smarter over time, and that certainly happens. But the bot providers themselves aren't doing a whole lot to help. Customer service data is notoriously unstructured. Larger companies often have hundreds of different categories in which customer service tickets can be “tagged” for analysis purposes. This makes it very difficult for a bot provider to find trends and insights even for one of their customers, much less to identify any macro trends across multiple customer accounts which could further make their bots better. This means that it’s inaccurate to call most customer service chatbots “intelligent,” artificially or otherwise.
To be clear, I am not against the idea of customer service chatbots. They can be an effective way to offload customer service inquiries, provide some base level of service during off-hours, and can solve more transactional and straightforward inquiries better than some human agents.
However, we live in an era when customers expect immediate, personalized solutions to their issues. An appropriate response can’t solely rely on chatbots. We need to rethink their place within the overall customer experience and also consider whether, in the pursuit of automation, we have lost the emphasis on human-to-human touch that has made customer service such an integral part of the customer experience today. What I learned in interviewing dozens of CX leaders for "Experience is Everything" is that a more balanced, hybrid approach that seeks to integrate the best parts of human agents with what chatbots can offer is the future of CX. And for those who wish to gain more customers at the expense of their less forward-looking competitors, that future is now.
Learn how you can join our contributor community.
