Tamas Ham-Szabo is the CEO of SAAS First.
Customers have high expectations from the companies they choose to do business with. Around 80% of U.S. consumers surveyed by PwC indicated that "speed, convenience, knowledgeable help and friendly service" were the most important elements of a positive customer experience.
Delivering exceptional customer service is an ongoing challenge for brands that want to stand out among competitors. AI tools have tremendous potential to enhance customer support in a more cost-effective way than using human resources alone. Gartner predicts that, by 2027, chatbots will become the primary customer service channel for close to a quarter of organizations. Research from HubSpot found that 71% of people were willing to use customer service messaging apps, and many did so with the goal of solving their problem quickly.
I have over a decade of experience in the SaaS industry, and I recently launched a company that provides customer support for SaaS companies using conversational AI tools. As we’ve implemented AI chatbots for our clients in the past year, we have seen that approximately 70% of user questions can be answered in real time by bots. Here are five of the most important lessons I’ve learned from using AI in SaaS customer support.
1. Provide Knowledge To Manage Hallucinations
AI models can produce clear, authoritative responses to a wide variety of queries. The problem is: sometimes they make things up. An AI hallucination is when a large language model generates false, irrelevant or nonsensical responses that aren’t aligned with reality. I like to compare AI hallucinations to what may happen if you ask a small child about a topic they’re unfamiliar with. They may act as if they know the answer and respond confidently, but their response isn’t based on actual knowledge or experience.
To mitigate AI hallucinations in customer service, you must provide a model with a comprehensive knowledge base. In our company, we found that by researching and documenting every customer question throughout the course of a year and training our chatbot based on this data, we could reduce hallucinations to below 0.5%. By providing sufficient data through training, we effectively eliminated hallucinations and ensured accurate responses.
2. Understand Costs
Cost is the main concern that has come up in conversations I’ve had with CEOs and product managers about AI in customer support. They want to know that the cost of this new technology will outweigh its benefits. Building an in-house solution requires highly skilled programmers and can be expensive and time-consuming, but ready-to-use solutions can be trained quickly at a much lower price point. Many chatbot tools, including ours, also only charge when a customer leaves a conversation with all of their questions answered.
3. Weigh Pros And Cons
In addition to price, it’s important to weigh other factors when deciding between external and in-house AI solutions. Building a tool from scratch can give your company complete control and customization, but it requires a substantial upfront investment in development time and expertise. A ready-to-use, third-party solution is pre-trained to handle customer queries and allows for rapid implementation, but it won’t be 100% customizable.
4. Analyze The Cost Of Scaling
As your customer support needs grow, your customer support tools must be able to grow along with them. Scalability is another area where AI chatbots shine. They are available 24/7, and with sufficient resources and storage, they can be scaled infinitely to keep up with increasing customer queries. Scaling human support teams, on the other hand, involves hiring, training and managing additional staff, which is time-consuming and expensive. AI tools can easily answer many straightforward customer questions, giving human agents more time to manage more complicated queries and tasks.
5. Train AI For Complex Tasks
AI chatbots can handle complex tasks, as long as they are trained properly. AI needs detailed, step-by-step training—using an in-depth knowledge base—to produce thorough, accurate responses. When we first started training our chatbot, it was only able to answer one question at a time. We analyzed all of the questions and concerns customers had raised and looked for answers to each individually. Then we trained the bot to provide a correct, comprehensive response encompassing all of the information requested. Wide-ranging training is essential to ensuring AI chatbots can handle complex customer requests.
As AI technologies continue to advance, they promise to transform the way businesses deliver customer service. By using AI chatbots to address customer concerns, you have the opportunity to improve the speed and effectiveness of your customer support, handle a significant volume of requests at a lower cost and free up human agents to focus on more complex issues—benefiting your customers, your staff and your bottom line.
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