The following is a guest contributed post from James Ramey, CEO of DeviceBits.
Chatbots have been making a stronger appearance in more businesses today. If we go back a few years at the available technology we had, the idea of chatbots would have people wondering what exactly they were and how it can help their brand experience. Now, chatbots have begun to surround our everyday lives with daily used products to help people grab their modern cab (Uber), or send messages daily (WeChat). Chatbots have been developed into more refined pieces of technology, adding customer service to their job descriptions. They are answering a number of questions on products customers have purchased, because they have begun replacing live human agents in the customer support journey.
Seems like chatbots are becoming a popular tech entity for businesses to use and millions of consumers around the world are interacting with them more. However, what happens when businesses are not all too familiar with building chatbots correctly? This can lead to misrepresentations of what their capabilities are, and can affect how customers view them if they encounter them in the future.
As businesses begin building their chatbots, they should be aware of the issues and key steps in engineering a successful chatbot.
Overlooking Keys in a Successful Chatbot
Chatbots, like any other technology, come with their challenges, and as more businesses are not correctly setting them up for success, their automation strategy begins to spiral downward. Around 21% of consumers polled do not interact with chatbots that appear, or if they do decide to interact with one, another 34% said they do so because they can’t find answers on their own.
Out of those polled, unfortunately 45% said chatbots do not provide the answers they need, and another 29% said they could only get answers from chatbots with simple and straightforward questions.
Chatbots are still trying to become favorable to consumers, but the conception of their improper engineering by businesses is holding consumers back from truly accepting them as a customer support tool. Another survey polling brand marketers in the U.S. acknowledges how brand marketers are not truly prioritizing chatbots into their strategies. 33% reveal that they do not have a chatbot, while 27% of other brand marketers said they do have a chatbot strategy but it still needs a lot of work to be successfully functional. 53% of these marketers also revealed that their bots were made to follow scripts, meaning they do not have any capabilities to learn from past customer data and interactions.
As different as any person is from one another, so are their questions on a product or service. Take the recent iPhone iOS 11 system upgrade and iPhone product launch, which drew in many issues and complex questions brought up by customers. New queries also require chatbots to “learn” over time the new products and issues brought on by the customers, and because of this, businesses need to re-engineer their chatbots to identify and understand new customer queries.
The update in technologies can be compared to the evolution of search engines. Today, Google is heavily used and is the primary source of research. Before Google, however, early search engines where not as accurate and did not provide as much relevant and specific information. As Google began stepping into the spotlight, their algorithms began to adapt customer queries and modifying itself to provide better information for each search.
Building A Better Bot
Chatbots run off past information, constantly updating with the help of artificial intelligence (AI) and machine-learning, creating helpful and downloadable self-support materials. As popular as self-support materials have become amongst consumers, there are still some businesses that have yet to implement these materials into their customer service strategies. As 82% of brand marketers follow this setback, they are also inhibiting chatbots from learning from customers.
Using A Chatbot
The effective use of chatbots results when the chatbot has been engineered correctly by businesses: assisting customers and cutting their time in self-research by communicating and interacting with their questions to provide the answers they are looking for. Chatbot technologies are changing how businesses are handling customer service. With the use of self-support materials and these bots, customers can effectively be led to the answers they need, and at the same time customers are helping these chatbots learn through predictive analytics in order to successfully handle future customer support journeys.
If businesses want to make the most out of their customer service, they need to create a customer support system that is intelligent enough to answer complex questions and analyze its past customer support experiences.
Editor’s Note: James Ramey is CEO of DeviceBits, a software company that services clients through a predictive and personalized understanding of interactive tutorials, adaptive FAQs, Interactive Guides, and Videos designed to for self-serving consumers. For more info visit www.devicebits.com.
