It’s Win-Win-Win When Businesses Use Analytics to Gauge Customer and Employee Satisfaction

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Just as analytics helps brands better understand customer behavior, data can be used by businesses to gauge how happy employees are and how likely they are to stay. Here are three steps to implementing the right analytics strategies.

The customer is every brand’s number one priority, right? Not quite. A few years ago, Richard Branson flipped the traditional thought process on its head by saying, “So, my philosophy has always been, if you can put staff first, your customer second and shareholders third, effectively, in the end, the shareholders do well, the customers do better, and you, yourself are happy.” Based on recent research, he was right.

According to Aon Hewitt’s report, “Trends in Global Employee Engagement,” engaged employees are a brand’s most valuable asset. Employees who are 5 percent more engaged than their counterparts lead to a 3 percent increase in top-line revenue the following year. When employees are disengaged, the warning signs manifest themselves in everything they do, which ultimately trickles down into all aspects of the customer experience. The problem is most companies miss the warning signs until it is too late.

Just as analytics can help brands better understand customer behavior and adjust strategies to reduce churn, it can do the same for employees. With analytics, companies can gain a firm understanding of employee behavior and sentiment, allowing brands to implement the right programs, policies, and procedures that keep employees happy and engaged. In the end, everyone wins – especially customers.

Here are three steps to implementing the right analytics strategies.      

1. Break ground

Many HR departments already use employee data to garner insights during the hiring process, or to understand compensation, turnover and other crucial variables. While that information is essential, it is not taking into account day-to-day employee behavior that shows engagement (or lack thereof) in action. Everything from spoken words and tone of voice to desktop activity can indicate employee satisfaction, and to get that information, brands must go one step further.

To glean those insights, contact centers are implementing agent analytics, which is a combination of speech and desktop analytics. Implementing these analytics is a critical first step to gauging employee sentiment, especially through those employees who interact the most with customers. Speech analytics capture conversations that agents have with customers and link agent interactions and behavior to outcomes, such as call resolution.

In addition to speech analytics, desktop analytics can show companies which resources agents are using during those calls. If an agent is a high performer, companies can use those insights to understand why that person is successful, which can inform training strategies. On the other hand, if an agent appears to be disengaged, companies will have the data to address the underlying cause before the point of disgruntlement or attrition.

2. Get connected

To create a better customer experience, companies are implementing omnichannel strategies to interact with customers and understand their sentiment about the brand. Companies should look at employee engagement analytics the same way and apply those contact center strategies across the organization. As employees become connected to more and more devices, such as watches and activity trackers, it gives companies additional opportunities to understand and engage them. For some companies, that connectivity is imperative to the employee experience, so they are taking it to the next level.

Recently, Three Square Market offered its employees the choice to implant a microchip device into their skin that will allow them to connect with the company’s RFID systems. From door access to purchasing cafeteria food, employees can quickly accomplish otherwise mundane tasks. With this type of technology, employers may eventually be able to track an employee’s commute time, and a supervisor could pre-emptively offer a road-weary employee the opportunity to work from home.

3. Be predictive

The beauty of data lies in the fact that it not only helps brands generate insights about the current state of affairs but when used predictively, that data offers a wealth of additional information. As more employee data is collected, behavior trends will emerge that correlate with key events, such as employee tenure or turnover.

By running predictive models, companies can spot trends in individual employee behavior and understand if those changes will likely lead to disengagement or eventual separation. If companies take appropriate action and right the ship before an employee is too far down the path of disengagement, they can decrease employee turnover and prevent customer experience issues.

As businesses continue to rely on various sources of data to inform employee retention and engagement strategies, analytics will only become more important. That said, as opportunities arise to track and understand employee behavior, it is crucial that programs be designed to aid employee engagement rather than simply track and monitor if an employee took too long on a break. When used correctly, employee data can be instrumental in a brand retaining its most valuable asset: its people.

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