A few years ago, people would have never thought that modernized technologies such as augmented reality and conversational AI (artificial intelligence) would make a lasting impact with apps and software such as chatbots, voice-controlled AI but also with accompanied speculations like ‘why chatbots fails and how to tackle them?’, ‘why does the AI not understand what I am trying to say’ and so on. Now, Companies that develop chatbots are on a constant hunt to deliver a user-friendly, bug-free experience. There are a few important factors and tips to follow to handle and solve customers’ queries that improve the users’ satisfaction and promote the brand and the business. Now let us understand why chatbots fail and how to overcome them.
Reasons why chatbots fail and how to tackle them?
In reality, we humans can never deal with a bugged product or service and fail constantly. Same are the cases for a failed chatbot. To approach and overcome them, a company has to spend a reasonable amount of time learning to understand the mistake in their data or another source that may have malfunctioned. Below are some of the reasons why chatbots fails and how to tackle them:
#1 Chatbot fails to face and understand a user query:
There are times where a chatbot does not understand and gets stuck in the middle of a question from a user. Augmented chatbots fail as these chatbots rely on a limited way to manage and solve a query. Another reason is that a non-AI bot is embedded with an in-built rule-based conversational flow that could break if the chatbot is bombarded with unknown questions and could result in a chatbot failure.
Solution: – To overcome them, a chatbot must be in-built with a natural language processing software that can help the chatbot deal with the context of a query resulting in a human-like conversation. Ultimately, a company should provide services that enhance the contextual technology of the chatbot. It is mandatory first to have a clear picture of what the chatbot should be designed to do.
#2 Chatbots failing to ‘code-switch’:
Natural-language programmed chatbots failing to understand a mix of languages, dialects, and other barriers are expected if the chatbot data is built only on a specific language.
Solution: To overcome these language barriers, a chatbot needs to get programmed with multiple languages and dialects to solve various queries of the customers in their preferred language. This would surely overcome the questions like, “why chatbots fail to ‘code-switch’ and how to manage it.”
#3 Expectations of Omnichannel:
A user expects more from a chatbot beyond a typical interaction. Users like chatbots with no channel restrictions. Chatbot fails face a significant issue when complementing various uses of omnichannel.
Solution: – Providing an omnichannel supported chatbot to the users can have a sign of lasting positive impact on the business or the brand. Channels like messenger, WhatsApp, etc., can provide an overall experience to the user. At the end of the day, the best part is, accessing these apps is less time-consuming and only takes minutes for the user to interact with these chatbots. Providing an Omnichannel experience is one of the best answers to why chatbots fails and how to tackle them.
#4 Deal with the button-based conversational flow:
Customers have always complained about the typical button-based conversational AI of chatbots. The button-based conversational flow will provide limited options in the specific machine for the users to read and choose from. Ultimately, this makes the bot choose from specific listed options and proves harder to handle quarries, thus resulting in a failed chatbot.
Solution: – The best way to overcome these button-based conversational flow is by adding both buttons and a guided flow of chats. This way a user can get a chance to ask the chatbot something that is not mentioned in the list, and the chatbot could respond effectively and manage the query.
#5 Minimalized personalization:
Users always deal with the procedure of asking about personalized experiences. The best way to manage it is by providing humans-like interaction rather than a robotic interaction.
Solution: – Creating and learning about a single user’s personalized touchpoint and creating chatbots based on their demographic, clickstream, patterns and many more services.
#6 Accuracy really matters:
The ultimate technology success of a chatbot is achieved when the chatbot is very accurate with the responses. This can alter and have a great impact on the image of a chatbot and its creator. According to a trusted source, an average chatbot is said to have 50-70% of accuracy. It’s a mandatory factor for businesses and companies to take accuracy into consideration.
Solution: – A domain-specific natural language processing chatbot can overcome these questions as they are contextually very much accurate. This in-turn will have a great impact on the user experience whatsoever.
#7 Bots limiting itself to hand-off capabilities:
According to a survey, more than 63% of the people are concerned if a chatbot could handle a complex issue.
Solution: – A conversational AI chatbot is the best solution to solve this issue. The AI powered chatbot can compare and manage complex issues such as complex requests, priority or a skill. Ultimately, this would provide excellent customer services all together.
#8 Barriers placed by a multimedia:
The exchange done by a chatbot, when narrowed down, can perform minimal activities with its capabilities.
Solution: – The best solution is to enable a chatbot to extend its multimedia inputs and outputs across image, speech, and texts in documents. By this, chatbots failing can be minimized in this category.
#9 Redirecting users
If a chatbot redirects its users to a website or a link in between a conversation then it results in an incomplete user journey. According to researchers, it is revealed that people tend to like talking to augmented chatbots rather than waiting in the line to talk to a customer care executive. If the bot fails to actively solve the customer query, it ends in a failed chatbot, and according to a bigger organization, a chatbot fail is considered as a bad reputation towards the company.
Solution: – The best solution to overcome them is to have a good overall customer satisfaction (CSAT) score. A self-serve solution and a secure transactional interaction service is recommended.
#10 Understanding slangs and dialects:
For instance, A person can be more comfortable when he/she can communicate in their own slang, dialect or abbreviations. The same goes when a user tries to communicate with a chatbot in their own preferences. The same problem is faced when a chatbot fails face the concerned issue even after being an NLP powered bot. If the chatbot is not programmed to favour the dialects and the slangs of the customer, then the bot becomes a bad user experience.
Solution: – Training a chatbot to be accessible in a multi-language platform can bring in a huge difference. A multilingual chatbot can favor the interactions of the user by enabling them to use their own preferred dialects and slang.
These are some of the major chatbot failure and how to overcome them. Although, these might be a basic problem faced by a user, it is indeed a significant problem that needs a developer to spend their time fixing it. There are more complex problems concerning the performance and the credibility of the chatbot. Those complex problems need complex solutions. But, if a company or a brand fixes the above-mentioned problems, almost 70% of the users can be satisfied and can have a lasting positive impact. Solving the basic problems in a chatbot can sound easier than done. These problems require an expert researcher to learn and understand the malfunction before solving the problem.
There is another alternative to solving the problems. We highly recommend trying out integromat. Integromat is an app that allows users to connect to different apps and provide automated work-flow. Using Integromat to connect and use chatbots can have a great positive user experience among the community. Integromat is a significant integration platform that allows users to automate work, design and visualize their desired chatbot within minutes. The chatbot that is in-built in Integromat allows customers to connect apps together from marketing to IT and development. The integromat bot allows users to experience three thousand plus templates and helps in guiding them throughout. With thousands and thousands of satisfied customers, Integromat is sure to bring light to the failure of chatbots in a corporation or a business.
Artificial Intelligence is enhancing every day. So too is our collective chatbot functionality and expertise of user behaviour and necessities. To this effect, we are able to see the proliferation of chatbots, and the price they offer, hold to upward push to the point wherein most interactions with businesses could be with full service synthetic intelligence of some description. But we are not there yet; there is a protracted way to move. However, this needs to know not prevent us from growing virtual assistants which could add real price to users if we heed the not unusual pitfalls above.