November 24, 2023
With the dynamic development of the digital world, customer expectations are constantly increasing. Buyers are becoming more aware of the diversity of products and services, making it increasingly difficult to keep them with a specific brand. The same products are available in many stores, which in practice makes it impossible to compete only on price. Is there anything more a service provider can do beyond implementing effective marketing activities? I will try to answer this question later in the article.
For consumers, the quality of the proposed products and services is often as important as the service they are offered. The ability to contact customer service, which is not limited by time frame, gives a great sense of comfort and security. To provide this without significantly increasing the costs of this service, it is worth considering the use of chatbots. It is to them that I want to devote this article.
Chatbox is software whose task is to simulate a conversation using text or voice messages. This solution is widespread in computer games and increasingly used in trade and services. The history of chatbots dates back to 1966, when Joseph Weizenbaum created a program called Eliza. His task was to simulate a conversation with a psychoanalyst.
Over 50 years of their history, chatbots have evolved dynamically. Currently, they can be divided into a number of groups. The simplest ones work like a hierarchical decision tree, where each subsequent question serves to specify the expectations of the user who makes contact.
Slightly more advanced solutions are based on keyword recognition. They try to analyze the information entered by customers by searching for specific phrases.
The combination of the two types above are hybrid chatbots that, when selecting subsequent questions from the decision tree, are supported by phrases sent to them by a human.
The next level of advancement is chatbots that support speech and context. Due to their greater complexity, I will devote more attention to the latter two.
In my opinion, these types of solutions are the future of this technology. In this case, the input data are users' voice statements, which, using appropriate tools, are transformed into a form whose analysis enables the continuation of the conversation. A critical aspect of such solutions is the implementation of an appropriate natural language processing engine - NLP for short. This is where artificial intelligence comes in, allowing machines to analyze human speech. Very good examples of this are Amazon Alexa and Apple's Siri.
I have already mentioned solutions where the program decides which questions to ask based on phrases found in the client's statements. The next step is to analyze the context of the statement delivered, depending on the form of input, in voice or text form. Using the benefits of artificial intelligence and machine learning, contextual chatbots use the history of previously remembered conversations and interactions to assess user requirements as accurately as possible. What deserves attention here is ChatGPT, which most of us have probably heard of.
As I already mentioned, chatbots allow you to ensure continuous availability of customer service with low integration costs. It is easier for employees to focus on more important tasks while reducing the time it takes to respond to customer questions. The cost of implementing such a solution is many times lower than maintaining additional support staff. Apart from being able to provide support at the stage of product search, purchase, or complaint, the chatbot can conduct many conversations at the same time. Chatbots make it possible to reduce human errors and analyze the behavior of consumers visiting a store or platform. The data collected in this way can be effectively used to improve solutions proposed to clients. Another advantage is easier access to global markets due to the fact that implementing an additional language in which the user will be supported is relatively simple.
Chatbot also poses threats that should be taken into account. Applications of this type that use artificial intelligence for self-learning may make mistakes by not correctly adapting answers to the questions asked by the customer. The intentions and emotions conveyed in statements may be misunderstood. Consequently, the effect may be different from expected and users may become irritated and give up the services. Data security is also important. The fact that the chatbot asks for personal data may be reluctantly accepted by the person placing the order/complaint, who may be afraid of disclosing such information to unauthorized persons.
The implementation of the discussed solution involves integration with one of the available platforms offering these types of services or independent implementation. Both solutions require the involvement of developers. I believe that if higher traffic volume is planned in the application, it is worth considering skipping ready-made platforms because the total cost of a monthly subscription to the platform may exceed the financial burden associated with a non-standard implementation requiring the one-time involvement of a programmer. I am writing this as a member of the team responsible, among others, for such implementations in Elite Crew.
In my opinion, chatbots offer many opportunities and conveniences, but also challenges. In my opinion, the biggest of them is the analysis of human intentions and emotions conveyed in the news. They may be veiled and conveyed in an ambiguous manner. People are changeable by nature, which can lead to people changing their minds during a conversation. Additionally, slang used in conversations or typographical errors in text statements may obscure the message.
Krzysztof Kura
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