What are chatbots:
Chatbots are Virtual Assistants that use the power of conversational AI to simulate human-like conversation that flows more naturally and seamlessly. Conversational AI is the technology that uses Natural Language Understanding to simplify the interaction between humans and computers.
These programs have become much more advanced and can be highly customised or personalised so they can carry a persona that compliments the brand, its values and mission. They now use more sophisticated machine learning techniques to better understand questions and provide more useful responses.
How do conversational AI bots work:
They parse the user input and use machine learning models to understand the intent behind what someone is saying instead of expecting predefined words or phrases. They can also extract supplementary information from the user input and only ask for information that hasn't been provided earlier; it then processes the user's input to provide a rich, meaningful response.
With all the tech advancements in the field of natural language understanding and processing, the chatbots are considered to be game changers in delivering excellent customer experience round the clock at a fraction of the cost, but in reality, they are struggling to keep up with the big promises and more often than not these are down to the poor implementation of the available technology. During the pandemic, a lot of companies added digital channels and implemented chatbots in a rush to keep up with high call volumes and lack of staff but are not hugely impressed with the outcomes.
Here are the top 10 reasons why chatbots are failing to meet customer expectations and what you must do to avoid that:
1. Lack of transparency - Pretending to be human or not letting the customer know that they are interacting with a bot is by far one of the biggest mistakes. While the technology enables chatbots to be able to interact with humans in a more natural way, it's not mature enough to replace humans yet. Not letting the customer know they are talking to a bot sets an unrealistic expectation and causes frustration when they realise that they are not interacting with a human. Instead, it would be more apt to let customers know upfront so they have reasonable expectations that are easier to meet.
2. Frail language model and poor conversation design - Chatbots are as good as the language model they implement. A strong language model must incorporate an understanding of multiple utterances and language structures. To achieve a high level of accuracy, it should understand slang, dialects and multiple languages. A weak language model, on the contrary, would fail to understand a user's query and would therefore result in a high number of interactions being transferred to human agents. A successful chatbot implementation requires experienced conversation designers and architects and not just the technology and integration specialists, so always ensure that you have the right team to build a comprehensive conversational model that can understand a variety of ways in which humans interact.
3. Not advertising the chatbot's capability - Just saying, "Sorry, I didn't understand that", and then asking customers to repeat their query in a different way when the chatbot can't understand the customer's input is not good enough. Most chatbots are guilty of doing this, and it can cause major irritation. If the bot is unable to understand what the customer has said, it's always best to let a customer know the range of responses it expects or the type of queries the bot is capable of handling and transferring them to an agent if it still can't understand the user's response.
4. Implement and forget - The virtual assistant implementation is not a project where you implement and forget, as this strategy is a recipe for disaster. The language model requires continuous monitoring and improvement. One needs a team that looks at issues/failures and updates the language model so the bot is always learning and matures as more customers interact with it. It is always recommended to engage with partners or specialists who are not there just to implement the bot but also to provide ongoing support that covers retraining of language models.
5. Lack of empathy - Most bots are not capable of understanding the feelings and emotions of a customer and can't empathise with them or their situation. This is by far one of the biggest challenges for anyone implementing the virtual assistant. One needs to ensure that they invest in the right technology that can understand customer insights and also adapt its response or subsequent action as needed.
6. No personalisation - Providing static responses to customer queries can only result in an ordinary customer experience. If you want to take it to the next level, the chatbot needs to be aware of the customer, their previous interactions, and everything else that the business knows of them to provide a personalised experience that can bring that wow factor to delight them. Do go the extra mile to utilise Customer Data and Experience Platforms to implement a more personalised experience.
7. Trying to achieve too much - It is important to understand the limitations of the technology when trying to automate and build the self-service experiences catered by chatbots. You can achieve a great customer experience by automating simple queries and leaving the more complex ones for the human agents. More often than not, the big chunk of all enquiries are the simple and straightforward ones, and these are also the ones that are monotonous to handle and cause agent burndown. These are, therefore, the low-hanging fruits that can be easily automated. Once automated, it is important to monitor and improve the experience they offer before accelerating the automation of other use cases to maintain high levels of customer satisfaction.
8. Asking what has already been said - Most chatbots focus on understanding the customer's intent and often miss out on capturing the supplementary details that the customer provides and end up asking them again, this can be really frustrating and can drag your customer satisfaction score down. It is important to focus on a robust conversation design that can extract all the minute details from what the customer says and adapt its responses accordingly.
9. Lack of personality - The chatbot needs to reflect the brand's personality. The responses from the chatbot and its tone must be aligned with the company's style and values so it provides a more consistent experience that is in line with other communication channels and other digital interaction touch points.
10. Broken conversation design - There is nothing more annoying than a stuck bot that doesn't know what to do next. Broken conversation paths, unhandled events or responses can result in a stuck bot where the customer is expecting the bot to respond, but it just goes dead. It is very important to consider all the paths of a conversational flow, especially the failed ones, as some of these might result in such deadlocks. Pay specific attention to the handling of no-matches, no-inputs, web-service or integration timeouts and failures when building and testing these conversational experiences.
To conclude, chatbots are still a game changer; the technology is continuously improving, and so is the customer's acceptance of it. All that is needed is an effective implementation that adheres to human-centred design principles and a commitment to monitor and retrain the models as needed. If done correctly, the automation of simple and repetitive tasks can not only help businesses reduce their cost and shorten the queue wait times for the calls in their contact centres but also boosts customer satisfaction.
