Chatbots have come a long way over the years. They were once limited to rule-based algorithms in handling and answering questions. Modern chatbots now use natural language processing (NLP), machine learning and conversational artificial intelligence (AI) to interact with users.

Organizations looking to increase sales or improve service efficiency use chatbots to save time and improve efficiency, as AI chatbots can communicate with users and answer recurring questions at any time convenient for them.

As consumers move away from traditional forms of communication, many experts expect chat-based communication methods to grow. Companies are increasingly using virtual assistants for simple tasks, allowing employees to focus on other responsibilities.

Yes, chatbots really make it easier to collect and release information, but they also irritate most users with their lack of understanding and obsession.

To understand how chatbots still help businesses, first let's figure out why they cause discomfort.

Why do users hate chatbots?

Chatbots impersonate a real person/employee

The client receives a standard response to a detailed personal request, and this leads to a decrease in trust in the resource and refusal of the company's services.

Do not understand users

Not all users will write a question exactly in accordance with language rules. Because of this, they will often receive an answer that the bot does not understand them or will not receive an answer at all. It is unlikely that the user will be persistent and will rewrite his request. Most likely, he will simply go to another company.

Create an extra link between the client and the employee

One of the most common errors is giving the chatbot one function - collecting contact information. To any user question, the bot sends a message asking you to specify the phone or email where the answer will go. This indicates that the user will have to wait a long time for an answer, which in turn will encourage him to go to another resource, where you can immediately get an answer.

Too imposed

Many chatbots are configured so that they independently activate the chat every 2-3 minutes. The chat is also activated when the user works in another window with an audio signal. In addition, chatbots often continue the conversation in the already completed dialogue and offer the user various reference or advertising information without request. Usually, this behavior causes only one reaction from users - to urgently close the interfering window.

Developers attribute non-existent functions to them

In most cases, the chatbot in the greeting says that it has the opportunity to solve many problems. But in fact, after a number of calls on duty, he forwards the answers, he forwards the request to the operator or asks for contact details for a response. Thus, the user runs out of patience, he does not wait for the solution of his problem and leaves the site.

Any company can face such mistakes of chatbots, but to avoid them, you need to understand the reasons for these failures.

Chatbot restrictions

Chatbots are said to increase customer engagement, improve communications with the brand and give businesses useful insights. But plenty of chatbots can't fulfil their potential because of the limited nature of most of their technology.

The main problems can be divided into four main areas:

1. Lack of training data

It is a common misconception that machine learning systems somehow operate entirely on their own, without any human control. It is not true.

Just as a linguistics-based dialogue system requires a person to work painstakingly on each rule and response, a machine learning system requires people to collect, select and purge each individual piece of training data because using machine learning to understand people requires a staggering amount of information. What is natural for us, people is the relationship between words, phrases, sentences, synonyms, lexical units, concepts, etc. must be "learned" by the machine.

For businesses that don't have a significant amount of relevant and classified data, it can be an exorbitant and time-consuming part of building apps for AI chat bots.

2. Poor understanding of spoken language

An even greater problem is the risk that machine learning systems will not understand the client's questions or behavior.

In a linguistics-based conversational system, people can ensure that questions with the same meaning get the same answer. The machine learning system may not correctly recognize similar questions formulated differently, even within a single conversation.

There is also the problem that pure machine learning systems do not have consistent individuality because all the responses in the dialogues are combined text fragments from different sources.

3. Easy to create global appeal

Organizations need to support their customers in different languages, an issue that will only increase over time. Consequently, AI-based chatbots should be fluent in many languages and be able to learn more when needed. But that's only part of the problem because they often need support for different platforms, devices or services.

Most chatbot development technologies require a lot of effort and often complete rearrangement for each new language and channel that needs to be maintained, resulting in many disparate solutions that clumsily coexist.

These types of chatbot solutions cannot reuse resources from the original build, nor can they display the same chatbot solution on multiple devices and different services.

4. Data Protection Rules

Data is at the heart of dialogue and is used to personalize conversation, improve the system and provide business information, so it is important that businesses can take advantage by complying with regulations and legislation.

For organizations, the problem is not only storing data, but also extracting information for export or deletion in a safe and verifiable way.

In addition, many chatbot technologies restrict access to generated dialog data, which means that companies are losing one of the key benefits of implementing a dialog bot. Without this data, companies practically do not see their customers.

The Benefits of Chatbots over Employees

Chatbots offer several advantages over live chat or contact center agents. By offering your customers intelligent, automated self-service, you get the following benefits:

Ongoing customer support

One of the benefits of chatbots is that, unlike humans, bots can respond to customer requests around the clock at no additional cost. With 24-hour chat capabilities, your bot can answer customer questions instantly without requiring them to call your support during business hours.

Data processing speed

The AI chatbot is designed to recognize, understand and respond to specific queries and problems in seconds. They can even offer "best fit" requests, saving even more time for the customer. In addition, most agents usually have to refer to standardized responses for general requests, which requires additional time. And chatbots have answers already programmed, giving them an edge over live employees.

Lack of human factor

The operator may be mistaken, misunderstood, not be prepared, he may have dissipated attention due to headaches or problems in the family. The bot is configured once and always acts exactly according to the algorithm.

Cost savings

One reason for the use of chatbots in the company is that they are more economical than hiring employees. In addition, bots do not need to go on vacation and take sick leave, they work constantly and are ready to answer several clients at once.

But the need for a person is still a requirement

Sometimes nothing can replace the empathy that living people can provide, or the type of intelligence that requires creativity or judgment to solve a question. In such situations, it is often the human ability to draw parallels with similar experiences that allows problems to be solved in difficult or unusual circumstances.

Therefore, it is important that the chatbot can freely switch to a live agent when necessary. And, accordingly, transmit all the information to the operator that was received during the conversation so that the client does not have to start all over again.