You know it’s automated, yet can’t help but feel connected to someone on the other end. That friendly tone and fast response time is hard to beat. But when you start asking specific questions about the WiFi router you just bought, your savings account, or a concern about the cost of your prescription, the conversation falls flat: “I’m not sure I understand your question.” Suddenly, seamless support comes screeching to a halt.
According to research from Gartner, only 9% of customer requests are resolved by self-service chatbots on the first try. In this blog post, we explore why chatbots often fall short for hardware support—and how you can provide superior support with a hybrid AI solution that actually solves customer pain points.
What are the origins of chatbot technology?
While chatbots have gained momentum in the past decade, their history dates back to 1966. German computer scientist Joseph Weizenbaum was attending the Massachusetts Institute of Technology (MIT) when he developed ELIZA, a program designed to trick users into believing they were communicating with a real human.
Though it wasn’t labeled a chatbot at the time, ELIZA is among the earliest examples of software that has the ability to recognize keywords or phrases to mimic human responses.
Weizenbaum’s innovation paved the way for modern software that automates all kinds of support requests across industries—from e-commerce to entertainment, finance to food delivery, healthcare to hardware, tourism to telecom, and beyond.
The benefits of this technology? Chatbots are:
- Easy to build and install on websites. Bots offer a quick path to basic support automation.
- Readily available 24/7. This means no bottlenecks for customers, like waiting to connect with a live agent for hours.
- Cost-effective. An automated solution means fewer in-person employees—and lower labor costs.
Considering the above reasons, it’s no wonder why 67% of consumers interacted with a chatbot over the past year alone. But while these benefits are enticing, chatbots are also notorious for leaving customers feeling frustrated and unsupported because they lack the problem-solving skills and nuanced information needed to reach a real resolution. Let’s see why.
Where do chatbots fall short?
Rather than receiving a quick resolution via chatbot, customers across industries are regularly rerouted to live support agents when self-service technology meets its limitations. These limitations include:
1. Lack of nuanced knowledge and specificity
Remember: chatbots have been instructed what to do and how to respond. While they may be easy to install, one size certainly does not fit all when it comes to handling customer questions, concerns, or frustrations. Often, resolving customer issues requires nuanced product expertise, awareness of colloquial or slang terms, and additional knowledge that a traditional chatbot simply doesn’t possess. When a chatbot can’t offer the support it promises, a customer has no choice but to wait for a live agent or turn elsewhere. This inevitably leads to greater customer dissatisfaction.
2. Inability to problem-solve or self-reason
Similarly, chatbots lack the human capacity to problem-solve and self-reason. Instead, they’re rooted in very simple technology: decision trees that solve predetermined questions using a company’s manually entered, preset answers. And these answers can’t account for unpredictable, specific situations. This hinders a chatbot’s ability to make decisions on the spot, troubleshoot, and offer the kind of support customers really need.
3. Difficulty understanding customer intent
All too often, chatbots fail to understand the intentions behind customer support requests. If the right keywords or phrases haven’t been included in the customer’s question, they may get confused and reply to a reasonable question with an unhelpful response like “I didn’t understand”—leaving customers feeling completely dissatisfied.
4. Limited learning capacity
Unlike humans, chatbots don’t internalize previous errors and improve. Traditional chatbots tend to repeatedly hit the same walls since their software is hard-coded and difficult to change without modifying the entire program. If your bot doesn’t learn over time, your support team will wind up having to repeat the same troubleshooting processes over and over—which leads to agent burnout and heightened inefficiency.
How can businesses improve support automation?
While chatbots clearly have shortcomings, there are several actions companies can take to improve their support automation. Here’s how companies can turn mere “chatter” into action with a more comprehensive approach to product support:
1. Invest in smarter, specialized AI solutions
It’s important to find specialized solutions that focus on resolving real issues for real customers. By constantly analyzing past customer interactions, smart AI assistants can diagnose pain points and help companies achieve more precise problem-solving. Since they’re powered by machine learning algorithms that pull from past interactions, these AI assistants more accurately understand what customers are asking and how to help. This results in fewer repetitive, time-consuming tasks for live agents—and customers who walk away satisfied, not stressed.
2. Prioritize resolution over deflection
Chatbots are notorious for primarily focusing on deflection and not actually fixing problems. It’s easy to talk in circles without proposing a solution, but this only frustrates customers and wastes more of their valuable time—especially if they have to then reach out to a live agent. In prioritizing resolution, companies can provide the tools that customers need to actually self-serve and fix their product issues. A key part of this process is understanding customer needs by analyzing end user data.
3. Implement a hybrid support model across digital channels
Even in the digital era, nothing quite compares to human skill, expertise, and support. Rather than choosing between artificial and human intelligence, companies should embrace a hybrid support approach. The benefits? AI solutions like chatbots offer speed, scalability, and cost savings while human agents are experts at establishing emotional connections and providing personalized service.
Enter Mavenoid: the one-stop shop for superior product support
When it comes to providing complex hardware and product support, most chatbots simply won't cut it. Limited in intelligence, they lack true troubleshooting skills. They think inside the box. They hit walls. And instead of actually resolving customer problems, they fail miserably time and again.
Unlike traditional, limited chatbots, Mavenoid focuses on troubleshooting specific technical issues—not basic FAQ items or simple requests that can be solved with one to three steps of decision-tree logic.
How? Our hybrid AI approach identifies product solutions based on real data from our customers—with insight into their specific questions and user experiences. That way, our technology comes back stronger by self-teaching and avoiding repeat mistakes.
Better yet, Mavenoid can be used across digital channels. It's not simply a chatbot, but a comprehensive solution that is accessible in-app, over email, or via social.
Say goodbye to chatbots and hello to customized support.
