Using Contact Center Analytics to Cultivate Organizational Growth

Contact centers should no longer be seen solely as enablers of customer service, but instead as a key driver of business growth. And the contact center space should be considered part of an enterprise’s overall customer relationship management strategy.

The enormous amount of data that contact center generates through multichannel interactions with customers via phone, VoIP, email, web chat and social networks is the pulse of their customers, their expectations, and their satisfaction indicators. Businesses must mine this data using different analytics tools to create actionable insights that enable them to develop roadmaps for brand promotion, product line expansion, workforce optimization and many other aspects.

Beyond Traditional Analytics Tools

While business leaders understand the importance of collecting data in the contact center; they do not necessarily understand the potential that analyzing this data has for organizational growth. Businesses are differentiated less by product features, functions and pricing and more by customer service and compliance. Simply having data analytics tools is not enough. You need the ability to amass, manipulate and evaluate massive amounts of unstructured data and subsequent actions.

On one hand, contact centers must interact with hostile customers who have zero tolerance toward mediocre and inconsistent experiences—and rightly so. In addition, the enterprise’s leadership expects nothing short of delivering an outstanding customer experience. But contact centers often get stuck in the middle. Optimally handling unstructured data using state-of-the-art analytics tools gives them the firepower to satisfy both sides. And this is where the need for deep-dive contact center analytics and customer care analytics comes in—these tools capture actionable insights from the wealth of data that customers leave behind during daily interactions.

Facing Contact Center Challenges Head On

The contact center faces several challenges, but properly mining and analyzing customer data with the right tools can help overcome them.

1. Contact center operations rely on a multitude of transactional systems, each of which generates large volumes of disparate data—usually stored independently. If this data were acted upon independently, the results have little to no value. You must look at big data holistically to generate actionable insights. Integrated contact center analytics offers high value to contact center operations.
2. More customer data is collected daily, both personally and in aggregate. Analytics gives you the ability to perform behavioral analysis of customers based on that data. For example, you can learn if customers primarily use SMS, when do they use social media and if they actually use their phones as phones. Analytics provides insights into near-real-time data to help solve problems like proper staffing, queuing and contact distribution. Essentially, it enables you to understand why a customer is contacting you.
3. The new European Union (EU) law called General Data Protection Regulation (GDPR) enforced from May 2018 is set to significantly change the way data would be stored, processed, transferred and analyzed. Data scientists have a huge role to play in preparing businesses for GDPR. One important area to be impacted would be the ways businesses profile customers and process personal data particularly to analyze or predict certain aspects of an individual’s behavior, socioeconomic condition, preferences, health and so forth. In fact, GDPR creates a “right to an explanation” for consumers by organizations that use automated decision-making. One of the fundamental tenets of GDPR is to empower users to give their consent willingly, and with full knowledge of how their information will be used and for what purpose. Under GDPR, the organization would need to notify the person involved, list potential consequences and then provide an opportunity to opt out. Any perceived bias within the processing algorithms is likely to breach the GDPR. The requirement of customer consent is likely to cause a sharp decline in the quantum of raw data. There would, therefore, be a need to incorporate robust anonymization to overcome this problem. One thing is for sure; GDPR is a reality for every data analyst or data scientist and is becoming an integral part of their job role. Therefore, they need to prepare for GDPR by understanding their obligations under the law rather than run away from it. There is a lesson to be learned from recent revelations involving Facebook and Cambridge Analytics.
4. Interaction with the customer is no longer confined to asking and answering questions. To ensure that the customer experience is positive, organizations are shifting from a reactive contact center operation to a proactive one—transitioning from a simple receive-and-respond mindset to one that’s designed to monitor, alert, predict and optimize customer interactions. An integrated approach ensured by analytics use at the contact center will improve customer satisfaction, lower operating costs and increase revenue per customer.
5. Customers demand new support channels, including social media, SMS, and email. And this can only be facilitated through larger IT investments. The rate of investment in IT to drive operational efficiencies and effectiveness within the contact center is much lower than demand growth rates. This puts a serious embargo on effectively managing the volume of customer interactions—and this issue requires special attention.

Priorities and focus within the contact center will shift from reducing call times and the number of calls to improving customer experience and understanding customer journeys. And this will be implemented with comprehensive—but appropriate—analytics tools.  See how PayPal leveraged reporting and analytics for rapid growth and to create customer journeys.