Do you capture metrics for queue management? If you aren’t measuring, you could be missing out on opportunities to boost productivity and customer satisfaction. With queue analytics at your fingertips, you can better manage your waiting lines (and customer flow) by focusing on real-time and historical data that have a direct impact on the key performance indicators of your business.
There are many metrics you could track, but we typically recommend boiling it down into three key buckets:
It is generally accepted that customers will only wait so long for service. That threshold can differ from one business to another (Apple store vs Target) and one product to another (cronuts vs. donuts). How long are customers willing to wait in your lines before they renege? Real time and historical data will tell the story about how long it takes for your customer to make their way from the back of the line to the register or service agent. Footfall analytics can track the rate at which customers enter the waiting line. And queue analytics can track the rate at which customers are being served. Combined, you can paint a rich picture of the factors that influence and determine abandonment rates. And based on the wait time threshold at which your abandonment rates rise, you could set real-time alerts to add staff, direct customers to under-utilized service points, or take other measures to stop abandonment in its tracks.
Understanding the service rate of workers and queues can be instrumental to managing wait times, employee productivity, and customer satisfaction. Through queue analytics, you can automatically measure the service rates of an entire queue or individual service agents to uncover areas of improvement. For example, perhaps you find the service stations on the farthest ends from the head of the queue are the least productive. You can then dig deeper to determine if fewer customers are visiting those stations, or if employees feel they are outside the eyes of management and are actively less productive. In other cases, productivity may be unequal between teams. Perhaps teams from 12-5pm serve more customers than teams that work 5-10pm. Knowing these trends can help you know where to focus your energy. While it is important to tackle these productivity issues, collecting the data is the necessary first step here.
Straight up asking customers is another great way to know whether your queue management strategy is working. Digital screens placed in the queue can display prompts to ask customers “How is your waiting experience?” Although simple, a feedback system is a great way to collect valuable information that can help you combine the hard data you capture from footfall and queue analytics with the thoughts and feelings of those subjected to the wait. Take this feedback and overlay it with the data you’ve collected on wait times, abandonment, and service rates and look for correlations that can help you further improve.
Systematically gathering the data is a great first step, but should not be the last. If you want the data to actually make an impact, be sure to set goals to strive for. Whether your aim is to balance out the productivity of each service station or reduce wait times to less than two minutes per customer, ensure your goals are clear with specific numbers (e.g. set a goal to decrease abandonment to 3% rather than just saying ‘reduce customer abandonment’).
Communicate your goals to staff and management. This can give your whole team a tangible target to strive for. Finally, stay accountable by periodically monitoring the status of your metrics relative to your goals. If you’re falling behind, it’s ideal to know that as early as possible to reposition your strategy, change your tactics, or motivate staff accordingly.
Curious about the queuing data and footfall trends driving your business? Explore queue analytics solutions that can help drive productivity, performance, and satisfaction.