How many customers do you lose due to the wait?

All industries have access to tools that provide statistics and reports about their activity, usage, and results of workflow. Summaries of these activities help owners and managers understand their businesses better and develop strategies for growth to increase their revenue.

For walk-in restaurants that manage seating with pen and paper, or seat customers with buzzers or pagers, there is no system for oversight. No data is collected; no usage is monitored. Even a restaurant buzzer system doesn’t provide any data on usage such as wait times or the number of people who leave due to the wait.

The Carbonara digital waiting list changes this. For the first time, restaurants are able to measure and then manage this area of the business and gain very useful insights. Carbonara app gives stats about:

  • Customers added to the waitlist
  • Overall waiting times
  • Accuracy of wait time quoting by the restaurant

These statistics are included in the Carbonara Daily Usage Report, an executive summary and breakdown of the customers added to the waiting list. 

Each restaurant that uses the Carbonara Digital Waitlist automatically receives the summary of the previous day which includes a number of elements:


Why is this summary important? Today there is no system that calculates how many customers had to wait and how many were not seated. Pen & paper doesn’t provide any reporting of this nature, so we often do not think about those ‘lost customers’ that were not seated. With Carbonara app, you will actually understand how much money was lost due to not seating all of the customers from the wait list.

The best thing about this report is that It’s automatic – restaurant managers have an accurate number of the revenue earned and lost, based on the average spent per guest, simply by using the wait list.

Additionally, the party-type breakdown gives a clear snapshot of the three party-types that restaurants can manage through the Carbonara app:

  • Walk-in
  • Call-ahead
  • Reservation


The Carbonara app records all the waiting times assigned to different guests and at which time they are seated. This allows the system to generate two stats:

  • Quoted wait time – the wait time that the restaurant host tells to the customer
  • Actual wait time – the actual time the customer waited prior to being seated

The daily report then shows how accurate / inaccurate the quoted wait times actually were.

The graph divides the parties added into three different parts:

  • Overquoted parties: those parties that waited less than the estimated wait time they were given to be seated at their table
  • Underquoted parties: those parties that have waited more than the estimated wait time to be seated.
  • Accurate parties: those parties that were assigned the correct wait time.

If the host tells a customer the wait will be 20-30 min, does the customer wait 20-30 min or does the customer have to wait longer? Or, was the wait only 10 min, but just to be on the ‘safe side’ of things, we ‘over-quoted’ the customer 20-30 min. It’s very easy to measure and track this with Carbonara app.

Why is it so important NOT to over-quote?

Busy restaurants that don’t accept reservations often have long wait times. Since they don’t have a tool to know exact wait times, restaurant managers and staff work on assumptions. Imagine a group of people that have asked for a table is told the wait will be approximately 50-60 minutes. Given that this is a relatively long wait, some customers may be inclined to leave. If the actual wait time is closer to 20 min, but customers left because they feared that they would wait 50-60 min, then overquoting has done a big disservice to the business. In this way, it’s important to know when we’re overquoting because it directly leads to lost revenue.



Restaurants that use pagers (or buzzers) are missing out on unique insights that an app like Carbonara digital waitlist can provide, such as the average wait time per hour.

This graph shows the average waiting time for each hour of the day based on the covers added to the waiting list. The average waiting time per hour measures how long the customer waits at a given time of day. The graph could show, for example, that there is an average wait time of 45 min at 20:00, whereas there is only an average wait time of 10 min at 18:00. This indicates to the manager how to potentially staff for busy hours, or what to tell a customer that asks when the wait would not be as long. It could also identify a breakdown in service at a given time – that is, perhaps things didn’t go very well on a specific day (e.g. a shortage of staff) and because of this, it caused customers to wait much longer.

Casual dine-in restaurants that use a wait list need statistics and reports of their activities as much as other businesses. Switching from pen and paper to Carbonara’s digital waitlist service provides restaurants with details, graphs and statistics that will help restaurant managers to create a better workflow, seat more customers, increase their revenue and review their losses. Plus, non-reservation restaurants will finally have the possibility to find out their average waiting time, a number that pen and paper waiting lists can’t provide. It is so easy to have access to these statistics with no extra work, you just have to use the Carbonara app.

Are you ready to get personalized statistics about your restaurant for FREE?

Download the Carbonara App Today