5 medidas de filas de espera en tiempo real para el manejo cotidiano de las esperas

Handling the day to day management of your waiting line, the points of transaction, and your service agents does not have to be daily guesswork. By monitoring your queue in real time, you can create a predictable and efficient process for managing both your workforce and your customer’s experience.

Here are five real-time queuing metrics for your daily wait line management that will help maximize efficiency and increase customer satisfaction.

1. In-line wait times

The topic of in-line wait times covers a range of metrics that should be utilized in queue management. First, start with the most basic measurement: the length of the queue. Always know how many people are waiting in line at any given time.

Next, calculate the average amount of time the customer is waiting in line before reaching the point of transaction. Compare that number to the acceptable wait time. Will your customers wait three minutes or five? You now have the ability to adjust staffing needs to stay within the acceptable time limits.

Finally, based on the historical data of your real-time metrics, come up with predicted wait times that can be communicated to your customers. This action will ease tension and manage customer expectations.

2. Queue abandonment rates

The queue abandonment rate is the number of customers that leave the waiting line before completing the transaction. Calculate the average queue abandonment rate then:

• Immediately resolve issues that cause that rate to increase above the acceptable average.
• Strategize on how to reduce the rate by implementing best practices for a better customer experience.

3. Point of transaction efficiency

How long does it take for a transaction to be completed once a customer has waited in line? By separating the transaction time from the in-line wait time, you can monitor where the source of a longer-than-desired wait time is being generated. Is it the service agent or something in the waiting line?

Additionally, monitor the number of customers each service agent is serving within a given timeframe. You can then take action if a service agent is not meeting the necessary goal that keeps wait times within the targeted parameters.

4. Peak service times

When is the queue the busiest? Utilize the historical data of your real-time metrics to determine when crowds are expected and when customers are at a minimum. It could be certain hours within a day, days within a week, months within a year, etc.

You will not only be prepared to be properly staffed during busy times, but you can inform customers of these peak hours to help better serve their needs and manage their shopping expectations.

5. Service agent allocation

By combing and using the metrics listed above, you can then monitor the configuration of the allocation of your service agents. Remember to include wait time, point of transaction efficiency and service time metrics in your analysis to reach the ideal configuration of available service agents to create the best possible service experience for your customers.

Utilizing real-time queue metrics helps effectively manage the waiting line and the point of transaction by eliminating the guesswork and creating a proactive environment. Managers can improve the queue through superior service staff performance, consistently shorter wait times and a better checkout experience for customers and service agents alike.