By: Kristyn Emenecker, Global Vice President Enterprise Workforce Optimization, Verint
Whenever a customer calls on a service helpline, the interaction with the call operator stays on the customer’s mind and sets an expectation for how all experiences will go. An effective interaction is the result of a smart customer engagement strategy, delivered through tools such as big data analytics. For instance, a customer calling in to report a complaint is greeted by their name and a possible issue that the customer might have called to report. The customer representative is aware of the problem since he has analyzed the data of the customer’s previous tweet regarding this and his recent live message chat on the company’s website. The customer’s call is then transferred to the person who can help and within no time, the problem is solved and the customer hangs up satisfied.
The proliferation of the multi-device, omnichannel culture has made it more difficult than ever for organizations to manage the people and processes required to respond to consumer expectations in a consistent, personalized and contextual manner. The quantity and speed at which data is generated through these various channels, as well as the diversity of that data—much of which is unstructured and difficult to analyze—creates a major challenge for organizations. Very few companies have been able to effectively correlate and assess the data to drive an action-oriented strategy for their businesses. Nuggets of invaluable insight lie within that data—customer needs, wants and issues—information that can facilitate a special connection with the brand. But harnessing that actionable intelligence is tricky. Most organizations can get to the “what” of customer behavior through transactional data; it’s harder to get to the “why.”
In order to harness that actionable intelligence and create smarter customer engagement using big data analytics, businesses across all industry verticals should consider the following technology-driven strategies.
Enhanced Employee Engagement
The first effective strategy companies should explore in order to enrich the customer experience is through enhanced employee engagement. An engaged employee is more likely to contribute to a more engaged customer. Companies can look at the employee’s performance and development journey, in a similar manner to that of ‘customer journey mapping,’ to gain a better understanding of each employee and realize what motivates and drives them, thereby improving employee engagement with the organization. For example, personalized performance plans make target achievement realistic and motivating. When created with a single click from a concerning KPI, they are simple enough to make, manage and be utilized in the most under-resourced environments. Instead of focusing exclusively on point-in-time quality checks and measures for employee productivity, businesses with easily accessed personal development history can connect spot performance with the employee’s longer journey and growth curve within the company. In this way, the employee obtains better insight into their performance, is credited for their achievements and takes ownership of their successes. Where possible, it’s beneficial for employees to participate in their own quality evaluation process, which will make them feel more involved and connected to the results of their evaluations. Using technology available today, employees and evaluators can become more productive in their jobs by providing relevant and customized feedback
Automated Agent Guidance
Using real-time agent guidance, agents can enhance their interactions with customers during a contact center call through automated reminders based on the nature of the transaction, the sentiment that arises during the conversation, or even previous customer communications. With the help of big data analytics like speech and text analytics and desktop analytics, connecting the different points of the customer journey becomes easier, so that customers feel more connected to the organization Additionally, big data can surface certain themes that the organization might not even know, or might not be able to recognize in the huge amount of available data. Proactively addressing issues like a new agent struggling to provide answers or a fraud threat with a customer in real-time can go a long way to building a healthy relationship. And, gaining ongoing insights that can be turned into action, such as recognizing an emerging pattern of a customer’s product problem and offering proactive assistance can contribute to long-term brand loyalty and increased revenue potential.
Today customers expect extremely personalized experiences from all interactions. From the organization’s perspective, creating points of connection and memorable moments to develop an ongoing relationship with the customer serves to facilitate repeat occurrences. But customers now expect anticipatory relationships, where a particular business knows the type of engagement that customers are looking for from the companies with which they interact. For example, verification of the customer’s identity via a voiceprint from previous calls, without the need for multiple security questions, goes a long way in establishing a healthy relationship with the customer. By providing acknowledgement with action that the respective customer much prefers an SMS with his/her confirmation number as opposed to waiting on the call and writing it down makes the company/consumer relationship all the more strong. The use of big data analytics enables organizations to achieve this level of engagement by helping them understand customer sentiment, and the decision-making process, in an omnichannel fashion.
By implementing these approaches together into one strategy, organizations can move away from the challenge of big data to the opportunity of developing a positive overall customer experience that creates a strategic differentiator for the business. Organizations can break away from the competition by creating real connections between their customers and the brand—by mining and analyzing the right data, at the right time and at the right interaction points to achieve smarter customer engagement.