Chatbots are getting better: 5 trends


Chatbots were massively integrated into organizations. While bots certainly have benefits for the customer, not everyone has a positive experience with them. We can say that chatbots are not quite perfect yet. However, innovations are increasing at a rapid pace and with that new and surprising developments are waiting. These will significantly improve the contact between bots and customers.

1. Adaptive and personalized communication

Research shows that today’s customer is looking for fast and personalized services, primarily through digital channels (Gladly’s 2020 Customer Expectations Report; Oracle’s 2019 Global Customer Experience Insights Report). Organizations can respond to this by integrating an adaptive communication style into their bots. The bot has a database with various details about the person. The communication style can be adjusted depending on the person and various factors, such as his or her personality or the nature of the question (business or personal).

Example: difference between B2B and B2C

The bot recognizes a question asked in a B2B setting and provides comprehensive information, such as sharing a full terms and conditions document. In a B2C setting, the bot provides the customer with a summary of the terms and conditions and a link to the full document.

2. Recognition of emotions and tone

The typical “chatbot-like answers” are often cold and distant. This is because most bots lack human sensitivity to recognize feelings and emotions. The machine learning algorithms used to create bots can be trained to recognize emotions. The perceived emotions can be both positive and negative, such as frustration, anger or sadness. Bots can perceive this in both text and speech. Based on this, the bot can discuss the feelings expressed by the customer.

Example: frustrated customer

If a customer is frustrated, the bot perceives this emotion. In response, the bot directs the customer to an agent or offers help itself, as explained below in the understanding and offering help prediction.

Recognizing emotions goes beyond the current conversation. It is also a way for organizations to gain more insight into the number and type of complaints. This allows problems to be approached holistically and better solutions devised. Such analyzes are also very valuable to determine where (innovative) solutions can have the most impact and are therefore an important part of a customer-oriented approach.

Example: many complaints

Suppose a bot recognizes many complaints about delayed deliveries due to severe weather conditions in one day. Then the organization can decide to post a notice on their website to inform their customers in advance about possible delays.

3. Offering Understanding and Help

The biggest difference between employees and bots? The ability to recognize underlying problems and offer solutions, rather than just providing information. Together with adaptive and personalized communication (trend 1) and being able to respond to emotions (trend 2), this function can be of great added value. If a bot has information about the customers and their emotions, the bot can better determine which actions will help customers best.

Example: chatbot recognizes problems

If a bot recognizes that a customer is experiencing delivery issues for the third time, the bot can show understanding and offer a 10% discount coupon that the customer can use on a future order.

4. Omnichannel

Many companies are already developing an omnichannel situation in which they design the interaction between the customer and the intelligent system separately from the consumption channel. We expect that even more channels will come together through the integration of the bot rather than different bone mechanisms on different channels. This means that customers receive an unambiguous answer from the chatbot via all channels.

In addition, bots will develop more ‘senses’. A multi-sensory bot is one and the same bot that can talk to you (speech), show you a document via video (see) and finally give a written confirmation (write). For an optimal customer experience, multiple algorithms must be integrated. An overarching mechanism is also needed to consult information from other apps and passing information.

Example: this bot can do more

Suppose you have to show a paper document during a phone call with a bot. All you need to do is turn on the camera on your phone and show the document to the bot.

5. Omnitopic

Only a few bots, such as Siri or Alexa, can access other bots or websites for an answer. This is because bots are built in such a way that it is not really possible to cover different topics in the same conversation. The chatbot maintains a certain flow based on a predefined category and is unable to answer customer questions that are not directly related to the current topic. However, bots can be (re)designed so that multiple topics can be discussed with customers in one conversation.

The next step is to provide additional, valuable information before the customer has a chance to ask. Omnitopic bots also allow organizations to discover connections between topics that would go unnoticed by employees. This can lead to fundamental improvements in the customer experience and can have preventative effects.

Example: this is how a bot can combine categories

Suppose a customer first asks ‘What time does my train leave?’, which falls under the ‘time schedule’ category, and then asks ‘What will the weather be like at my destination?’, which belongs to the ‘weather’ category. Then the bot first shows the train schedule, then the weather forecast and offers a taxi if it rains – before the customer has had the opportunity to ask.

What’s next?

We look forward to seeing the five trends that we envision unfold in the coming years. But there will undoubtedly be further developments beyond these predictions. We are curious… What trends do you foresee?


Source: Frankwatching by feedproxy.google.com.

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