How improving customer service chatbot leads to optimized customer communication channels

Chatbots have become increasingly popular as a customer communication channel in the last few years. More and more companies are adding chatbots to their website.

It is cost-efficiency that makes companies turn to customer service chatbots. However, they are only worth investing in if they are able to help customers.

In this post we tell you how chatbots can be improved via analysis and targeted training, which also leads to better customer service as a whole.

Chatbots need more than installation

From the perspective of a company, customer service chatbots and self-service are the easiest and cheapest means of helping customers.

When visiting a company website and being offered assistance by a chatbot, a lot of customers would open the chat but then often, unfortunately, realize that the chatbot is unable to help them.

When this happens the customer will most likely use other customer communication channels such as phone or email. Those lines of support are, however, more costly for the company as they involve human resources. This would mean that companies’ investment in the chatbot becomes worthless.

In fact, adding a chatbot to a company website is not as simple as just installing it.

Chatbots require continuous work in terms of analyzing customer interactions. This is important to be able to understand, first, how chatbots can best help customers and, second, how other communication channels can be better optimized based on this insight.

Improved chatbot performance through analysis and targeted changes 

Feelingstream has developed a chatbot analytics platform (alongside our call analytics solution and customer email processing solution) that gives companies insight into the types of questions that customers ask the chatbot.

These chats can then be searched based on topics. The analysis can reveal which topics the chatbot can actually help with and what are the topics where the chatboth gets stuck. Action can be taken from there e.g. the chatbot can be trained to help with recurring questions.

In addition to this, failed chat interactions can reveal necessary changes to be made to self-service and website, so that the customers can better help themselves in the future.

Every issue that a well-functioning chatbot can either resolve or refer to self-service is a call or an email that has been avoided.

In terms of cost-efficiency, it makes sense then to invest in teaching chatbots to help customers rather than employing large customer service teams to deal with those same questions through more costly communication channels.

Examples of chatbot analysis and optimization 

One of our clients saw that their chatbot was used by their customers, but a lot of the customers abandoned the chat and called customer service. That’s because analysis done through Feelingstream showed that the chatbot was unable to help the customers with their issues.

Our client proceeded to analyze those customer chats and discovered several opportunities for improvement. For example:

  1. When customers asked about their invoice, the chatbot asked them to read a general billing-related page on the website
    + After analysis and training, the chatbot could refer the customer to the correct area in self-service to get their billing information.
  2. When chatbot asked what the customer has already tried to solve their issue, it did not take the answer into consideration later on in the chat (this problem applied to multiple different customer issues).
    + After analysis and updating, the chatbot was taught how to proceed using the additional information that the customer had provided, which led to the chatbot being able to provide more personal support.

Optimizing all customer service channels after analyzing chatbot interactions

There will always be issues that the chatbot is not able to solve for the customer, but there is a lot it can do with thorough analysis and training.

With Feelingstream’s chatbot analytics platform, businesses can get insight into how the chatbot can be improved. This insight can also reveal how the website and self-service could be enhanced.

After optimizing other communication channels, costly phone and email support will be available for those customers that really need it and greater focus can be turned to increasing sales.

If you would like to learn more about out chatbot analytics solution, get in touch with us here.

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