Good Customer Service Gets a New Meaning with AI

Our idea of a good customer service system generally consists of a team of dedicated workers, who are responsive to all problems and queries of a company’s clientele. They are also responsible for taking up the issues proactively with the concerned departments of the company so that the problems can be resolved with minimum delay for the user. These standards have been highly regarded in almost all industries.

Even after the appearance of Artificial Intelligence (AI), especially conversational AI systems, these standards were held in high regard. The chatbots were used to serve the end of quick response and problem resolution of customers. And many companies have been able to do it very effectively.

However, this conception is changing recently, leading to an idea of customer service which will be able to bring out the full potential of AI. The aim of this new approach is to prevent customers from feeling the impact of the problem; because even in case of a proactive troubleshooting approach, the customer has to realize the existence of the problem and the entire effect of it.

Features of the New Approach

The new conception of customer service tends to believe in a more hand-holding approach. That is to say that the customers are guided all along the process of using a product (good or service). They can direct them with all the steps for getting the best out of the product, and also taking care of it.

But this approach goes beyond guidance, in terms of anticipating potential customer issues and problems. It tries to establish a routine of monitoring the issues and also the problems faced and analysis. This has to be coupled with the knowledge about the workflow of your customers. Moreover, the customers’ needs and priorities have to be kept at the center of the customer service process.

The company should be aware of the interruption of which functions are likely to affect the customers the most. The company should also be mindful of whether the client is dependent on the system along with the sensitivity of his data. This can be most efficiently done through AI systems. They are not only capable of assimilating such large data sets but also finding patterns within them with the greatest precision and without any bias.

Moreover, the approach allows generalizability. That is to say, the problems faced by a few customers can help the system identify the risk for other customers and prevent it in time and make the customer service team aware of it.

However, all this comes at a higher data security risk. It also is not transparent and takes away the personal touch. But if these services are carried out through chatbots which are based on a blockchain network, both the efficiency and security increases in the process of customer service.

In the OLPORTAL ecosystem, all the data about the customer is provided at the time of registration through a transparent process and stored safely on the blockchain. Moreover, the chatbots can be trained by the users themselves, making them capable of catering to the specific needs of the users. All of these features if used by a customer service agency can serve the purpose of a minimum inconvenience customer service procedure.

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