Customer service

How Advanced Analytics Can Improve Customer Service In Contact Centers

Enreach 04/03/2020
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To make the most of the advantages of advanced analytics, organizations must have the right foundation to take full advantage of their data.

Increasingly, seeking to put the customer first, supervisors require accurate and detailed performance information that real-time analysis can provide. In this sense, according to McKinsey, basic data and analysis tools are becoming a standard practice in call centers. However, only 37% of companies are using advanced analysis to create value.

Advanced analytics helps customer service centers identify possible malfunctions. Although, thanks to the data and intelligence of the analysis software, patterns can be found more easily and, consequently, the organization can make commercial decisions based on the real behaviors and activities of the clients.

In addition, by analyzing all available user data, agents can improve the customer experience and meet their expectations. As a result, users will get the solutions they need quickly and easily.

According to McKinsey data, call centers have already applied advanced analyzes to reduce average driving time up to 40%, increase self-service rates from 5% to 20%, reduce employee costs by up to 5 million dollars and increase the conversion rate in sales service calls by almost 50%. All this while improving customer satisfaction and employee commitment.

Why Have More Companies Not Taken Advantage Of The Opportunities Offered By Advanced Analysis?
1) Lack Of Integrated Data Through Channels

On the one hand, many companies buy a set of customized solutions and assets to solve individual problems, instead of developing a strategic approach based on a single integrated platform. On the other hand, the quality team, the workforce management team and the digital team do not communicate with each other and, in some cases, do not even have access to the same data.

2) Inability To Link Analytical Knowledge With Actions

Other companies generate knowledge from the analysis, but do not translate them into concrete actions. Most organizations, for example, run customer voice analysis to calculate the first call resolution (FCR) and customer satisfaction metrics, but do not use that feedback to redesign the processes.

What Are The Characteristics Of A Call Center Based On Analysis?
1) A Clear Vision And Strategy

Contact centers need a consistent view of the entire company to perform the analysis. This vision must have a clear link with the general commercial strategy, along with a road map to implement specific use cases or offer more self-service options to reduce demand in call centers.

2) An Agile Organization With Internal Analysis Capabilities

Companies need to develop internal analysis capabilities that align with the strategic objectives of the organization. And, in turn, companies need agile mechanisms to capitalize on analysis-based ideas that translate into better customer service.

3) An Ecosystem Of Partners

Few companies can meet all your data and analysis needs internally. Therefore, they must determine which needs can be handled internally and which must be outsourced to expert partners.

4) A Culture Of Objective Decision-making

The main call center organizations make their daily decisions based on the available data. For example, what are the best employee profiles to hire, in what areas training is necessary, if it is necessary to offer bonuses based on the performance of agents, as well as other initiatives to optimize results.

The best organizations identify the weaknesses of the clients as an opportunity to differentiate themselves from the competition proactively, but they cannot achieve this without advanced analytics. The current state of call center analytics offers companies the ability to improve service quality taking into account the final result.

Contact center data analysis offers a unique opportunity to monitor and improve a variety of service metrics such as call times, efficiency, agent performance and customer satisfaction.

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