Which comes first—satisfied customers or happy employees? Let’s say a customer visits a restaurant. Her server is having a great day. He loves his job, he’s happy to be there, and provides exceptional service. As a result, that customer’s experience is a great one—she leaves highly satisfied, recommends the restaurant to multiple friends, and leaves high scores on her customer experience (CX) survey. Those scores are later shared with the staff, and the server is happy with the recognition.
But what if that server didn’t love his job? What if he wasn’t happy to be there or lacked engagement with the brand? It would probably show in his service. We’ve all been out to eat and encountered those servers—it makes for a very unpleasant experience. One that you don’t want to repeat, and possibly avoid by never returning to that restaurant.
Employee engagement and the customer experience aren’t mutually exclusive. That’s why it’s so important to measure feedback from both and combine that data for holistic insights on your entire service culture.
Establishing the right method
Knowing that connecting employee and customer data is an important step in understanding how each impacts the other, we set out to understand the optimal method of connecting these two datasets. To help brands determine the right approach, we conducted a series of analyses across multiple brands and industries. One of our main focuses was to determine the optimal timing for this correlation analysis, so we looked at several time periods:
Through this research, we were able to conclude that a rolling-month method 6 months after the employee survey strikes the right balance for timely analysis and optimal amounts of CX data.
The primary reason the rolling-month method tends to identify stronger relationships is because the sample sizes naturally increase as each month’s data accumulates and the impact of outliers is minimized in the larger sample size—resulting in more stable data. This is especially important at the location level where it can be a bigger challenge to reach minimum responses.
But if brands are anxious to see results sooner, using customer data collected up to 3 months prior to the employee engagement survey is an acceptable way to expedite the process. We believe this can help drum up early excitement in the employee engagement journey, and demonstrate to company leadership how employee engagement is impacting the business as well as why it is an integral piece to the feedback measurement strategy. Our research shows that no matter the time period you elect, you will see statistically significant correlations.
Drawing the connection
Your employees touch nearly every aspect of the customer experience—and happy employees mean happy customers. Connecting your employee and customer insights is an important step in formulating action plans that drive improvements across your entire service culture. Front-line teams play an integral role in shaping each customer experience, so be sure you’re getting an accurate read on their engagement and a deep understanding of how that correlates to customer satisfaction.
If your current CX measurement program isn’t combining employee engagement feedback, you’re missing crucial information vital to the health of your business. Successful correlation analysis takes the right methodology and timing—but once you find that sweet spot, you’ll uncover insights to take your brand to the next level.
For more on this research, download our white paper: Best practices for using correlation analysis to connect your employee and customer datasets.
Jeff Jokerst | VP, Client Insights