Telios IQ

The intelligent match
between customer and employee

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Telios IQ

The intelligent match
between customer and employee

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Telios IQ

The intelligent match between customer and employee

Telios IQ

The intelligent match between customer and employee

What is the importance of soft skills in a contact centre where technology and data are becoming increasingly important? And how can the various soft competences of employees best be reflected in conversations? In addition to strengthening competencies, there are also opportunities for linking customers to the most suitable employee. The match is complex, so there is work to be done for smart systems. The answer is the new Telecats solution: Telios IQ

Optimal match customer & employee

It is our vision that the match between employee and customer becomes increasingly important. The explanation for this is simple: simple questions are being handled more and more automatically. Commercial feeling, creativity and empathy play a role in complex subjects. If an optimal match is made between the context of the customer and the employee's characteristics, it is more likely that a good and pleasant conversation will take place.

Employees and customers are increasingly being divided into groups with specific characteristics. In this segmentation, the intention is that the most "challenging" customer contacts are routed to the most experienced employees. This makes the' matching' model of customers and employees more complex and a big challenge for the traffic and planning.

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From queue to waiting area

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In other words, the current routing of calls based on 'IF THEN ELSE' rules (next caller assigned to next available employee) takes little account of the value of customers and the potential of employees.

That is why this approach is giving way to intelligent routing. On the one hand, this takes into account the characteristics and preferences of the customer - customer value, customer preferences, personal characteristics, social and family situation, current context such as a predefined question, etcetera. On the other hand, intelligent routing also takes the employee's profile into account.

In other words, the current routing of calls based on 'IF THEN ELSE' rules (next caller assigned to next available employee) takes little account of the value of customers and the potential of employees.

That is why this approach is giving way to intelligent routing. On the one hand, this takes into account the characteristics and preferences of the customer - customer value, customer preferences, personal characteristics, social and family situation, current context such as a predefined question, etcetera. On the other hand, intelligent routing also takes the employee's profile into account.

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Predicting, matching and deciding

Look at it as a dating site: on the basis of what characteristics can we achieve the best possible match and when do we choose it? This intelligent routing is more than just about employee and customer characteristics. You can also predict how long it will take before the best fit employee is available. Based on all kinds of factors, the system can decide whether it is worthwhile to let the customer wait for a moment with the result that he or she is transferred to the most suitable employee.

In other words: make the best choice for the customer and agent at any time. This intelligence comes together in our new Telios IQ solution. The most important question, of course, is what factors should such smart routing be based on.

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Intelligent routing requires information

Routing based on Telios IQ is more complex than the standard method of first in, first out or a method like skill-based routing. Therefore, the choices within this method are made on the basis of machine learning. This starts with mapping out the characteristics of both customers and employees, and then measuring the results of combinations. What is the outcome - in terms of customer satisfaction or conversion - if you match a particular employee to a particular customer? All these results will be used as the input to make the system clear which combinations between customer (features) and employee (properties) work best.

Machine learning is necessary because the underlying patterns in the multitude of variables are too complicated to solve with manual analysis. When the system has learned to make the most suitable combinations, you start a pilot in the existing operation, which gives you the desired insight. The system will have to be fed with information - for example through workshops - and collect the necessary data, make decisions and use the results to improve decision making. In other words, in order to arrive at intelligent routing you have to go through a number of steps; it is not something that you just turn on.

Artificial intelligence in customer contact

Telecats is making full use of artificial intelligence in the development of speech technology and now also for Telios IQ. After all, truly intelligent routing is only possible with the use of machine learning. Artificial Intelligence will really break through in the coming years and lead to major changes in customer contact.

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