Self-service & customer relations

Self-service: a Key to Reducing Dissatisfaction in Customer Relations

Any online customer service inevitably has to deal with unsatisfied customers. Whether on social networks, by email or in comments, dissatisfied customers will let your business and the whole world know that they’re unhappy. Self-service can be a great ally for customer relations and in order to reduce customer dissatisfaction. Discover the methods and solutions to implement in order to improve your digital customer relationship.

Self-service and customer relations: provide autonomy to your customers

According to a Zendesk study, the main reasons for customer dissatisfaction are the multiplication of online contributors (57%) and a resolution time that is too long for 46% of respondents. A customer who fails to find an immediate solution to his problem will put an end to his journey and can even end up doing business with your competitors. It is therefore essential to offer them 24/7 assistance. Self-service tools are fully capable of responding to this growing need among your customers by offering a harmonised and automated solution.

AI chatbots and intelligent FAQs are the perfect tools to provide relevant, timely and easily accessible answers. The first one takes the form of a chat interface, while the other offers a large search field to submit a query.

Equipped with Automatic Natural Language Processing technology, these solutions are able to understand the true intentions behind customer’s questions and instantly find the right answer in a knowledge base. These technologies go far beyond the simple keyword search, which causes your customers a lot of frustration and wasted time. And frustration + waste of time = unhappy customers!

Whether through a Knowledge Management tool or a conversational bot, these self-service solutions will first of all allow you to provide the desired autonomy to your web visitors, and by side effect reduce the number of incoming contacts to your customer service.

On average, it is estimated that 80% of the incoming contacts reaching your customer services are requests with low added-value, which are time-consuming for advisors. Automating the processing of these requests will help reduce the queues in contact centers, and will save considerable time for advisors, who will be able to concentrate on more complex queries or dedicate themselves entirely to winning back dissatisfied customers.

Detect dissatisfaction and resolve it by integrating self-service

It is common knowledge that an unhappy customer is a customer that needs to be taken care of as soon as possible. However, when it comes to digital customer relations, this task is particularly difficult. Indeed, an Internet user has an attention span of 8 seconds on average and that he leaves a web page after 3 seconds when he cannot find what he is looking for. In other words, when you receive a complaint from a customer, the customer has already moved on, is complaining on social networks and may be seeing if the grass is greener elsewhere.

To solve this issue, you can provide them with autonomy and customize dissatisfaction management.

Our dissatisfaction detection tool is perfectly adapted to identify and customize the journey of a unhappy customer. This Machine Learning tool identifies signs of frustration in a query, and then triggers several retention measures described below.

Escalation to an advisor

Already possible via our AI Chatbot solutions when a user requests it, our “irritation detection tool” allows a proactive triggering of the escalation to an advisor, thus guaranteeing a direct treatment of your customer’s dissatisfaction.

Appropriate responses to dissatisfaction

Under certain conditions, it is possible to customize the responses generated by your bot. For example, in the case of a person who is very dissatisfied with the delivery time, who lets a bot know by the query – “What’s with the huge delivery time? Can’t you do your job?” – the bot will automatically be able to propose a personalized answer adapted to its discontentment.

A decision tree to clarify dissatisfaction

Another use case: once dissatisfaction is detected, it is possible to trigger a decision tree in order to determine the cause. This decision tree can propose either a personalized answer, escalation to an advisor or even offer compensation!

Personalization remains essential for effective customer relations, whether it is used towards satisfied clients or not. Today 83% of consumers say they have encountered at least one issue when coming into contact with a brand. There is still a long way to go to offer them a personalized approach that fully meets their expectations, but implementing a self-service solution is already a major step forward.

Self-service and customer relations: support your advisors internally

Self-service can also be a strength internally and become a valuable support to your customer service teams! Several of our clients provide their customer service teams with an intelligent FAQ or a conversational Chatbot to help them answer customer requests.

When managing an unhappy customer, your advisors could have access to predefined response elements or even to the entire dissatisfaction management procedure, just by typing a single query.

A Mailbot is another tool that can also support your advisors by automatically replying to your contact centers’ incoming emails and by filtering and redirecting or redistributing the incoming emails to the right person.

These solutions, which initially allow both your customers and your advisors to save time, also help you harmonize your customer service speech thanks to an optimization of the dissatisfaction management process!

Far from being a plug and play product, an AI Chatbot is a full-fledged self-service solution capable of adapting to all channels. If you’re interested in knowing more, download our PDF guide which highlights the keys to successfully complete your AI Chatbot project, from the thinking phase to the operational implementation.

Chatbot Guide

Estelle Verani