The first thought that jumps to mind when the main topic is customer care associated with AI is RPA (Robotic Process Automation). It is impersonated in most cases by a small icon, usually on the bottom right of a web page showing that you have an incoming message in the chat.

The implementation of Artificial Intelligence applied to the customer care area of an ERP is, of course, not only a bot. Let’s discover this world with this fourth episode of our journey.

Weighted priorities

A customer care operator has a vast list of todos. Where to start between follow-ups, RMAs, etc.? At this point, the ML (machine learning) offers the priority feature. It proposes the entire list ordered by a weighted metric. The algorithm evolves each time the operator confirms the suggested schedule or chooses one of the succeeding elements. Elements considered in the algorithm may be, for example:

– The expected time for executing tasks.

– The benefit of performing an activity earlier.

– The possible risks of completing a job with a delay.

– The effort in switching between one activity and another of a different kind.

– The number of breaks for interrupting repeating operations.

AI can listen to the call with the customer. It contributes to compiling the form even during the communication, the more the customer provides information. Detects the tones the customer uses, providing a confidence percentage for each. When the operator confirms what matches better, AI provides a strategy for managing the communication accurately.

RPA in surveys

The bots have a better attitude to success when they are conducting the communication. Collecting answers is, in fact, more convenient than an interpretation of a question that could mean many veiled directions because of background knowledge and culture.

Surveys, follow-ups, and customer satisfaction questionnaires are the best candidates for being presented and conducted by a bot. Furthermore, the AI can add metadata to the resulting set of answers (i.e. time of response, tone confidence percentage, number of retries in detecting the content, etc.).

Support service with relief

If you ever received a call from an angry customer, you can read the title with high scepticism. For the same reason, you know how stressful it is trying to help someone under tension. AI is the moral aid that the support operator needs to release the pressure the customer transfers. It searches for the best solutions to apply even during the communication, presenting them to the operator by calculated priority. Then the operator chooses which solution to propose. Finally, AI suggests even the sentences for the answer and the tone to use.

The ML algorithm’s best Side is its constant improvement, perpetual availability, and knowledge that gets never lost (e.g. if a skilled operator leaves for retirement or is changing company).

Conclusion

This fourth chapter has shown the real potential of Artificial Intelligence. It maximises the operators’ efficiency, and, consequently, customer satisfaction rises high, even in difficult moments.

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