Quantitative analysis of the restaurant's sales
One of the key factors in the outcome of any restaurant They are your sales, which once exceed the level of breakeven, they begin to produce a positive operating result, that is, profitability. However, knowing what this level is and setting sales goals to achieve is not enough to manage the sales of the restaurantInstead, it is necessary to delve into how these sales are generated, composed and evolve, in order to act on them and improve them.
In this article we will analyze how to break down sales into different subvariables that can be acted upon and we will present some tables of management of sales that can be implemented based on the data accumulated in the TPV´s of the restaurants and to help the managers of restaurants to better understand how sales work.
1-Level 1 analysis: The first level of disintegration of sales It consists of breaking them down into the two subvariables that compose them, which are the No. of customers and the Average ticket (tcm).
The average ticket is calculated:
The sales of restaurant In a given period, as is obvious, they depend on the number of customers that enter and the expense they make. Therefore, sales grow if the number of customers grows, the Average Ticket (average spend per person) grows or both at the same time. Sales also increase, if one of the two subvariables has a higher growth than the reduction of the other variable. Let's see the picture of management next:
As we can see, the sum of the variation percentages of the number of customers and the average ticket give as a result the percentage variation of sales. Therefore, if we want to act on our sales we have several options:
1- Implement actions on the number of clients such as traffic promotions aimed at:
1.1- Attract new customers.
1.2- Increase the frequency of visit of current clients.
1.3- Increase the Party Size (number of clients per operation).
2- Implement actions on the average ticket such as:
2.1- Price increase.
2.2- Increase in suggestive sales to provoke the consumption of a greater number of references per customer or the consumption of higher-priced references.
Therefore, as we can see, knowing how the basic subvariables of sales behave gives us much more detailed and specific information, allowing us to know why sales are falling or increasing, traffic or average ticket ?, and where to act. Consequently, it will be essential to create and use a management like the one below:
As we can see in the table, sales for the month of February 2008 have fallen by 7,63% compared to those of February 2007. The fall was the direct cause of a significant drop in traffic, 8,06% of customers less, slightly cushioned by a small increase of 4,75% in the average ticket.
And, therefore, we conclude that measures must be taken to increase and defend traffic.
2- Analysis Level 2: What we do not know with level 1 analysis, is in which time slot we have lost customers and why the average ticket has increased, and, therefore, we have to disaggregate both subvariables by time slots / days.
To carry out this analysis, we must summarize the sales information in a table like the one below:
The upper table clearly indicates that the drop in sales, as a cause of fewer customers, has not been generalized to all bands and days, but has focused on weekend lunches, where the number of customers it has decreased an alarming 37,5%. Also, weekend dinner customers have fallen, but this band has grown by 1,9% due to the behavior of the average Ticket that has grown by 4,3%.
In conclusion, this information tells us that priority should be given to the weekend lunches sales band, since the rest of the bands, globally, have grown in sales.
It is evident that the picture of management 2 also provides us with other interesting information, such as, for example, the behavior of the average ticket in each time slot, and we can observe the difference between, for example, lunch during the week that presents a low average ticket of 9,5 ?? (influenced by a menu at 10 ??) compared to the average weekend lunch ticket of 15,9 ?? (sale only letter).
3- Analysis Level 3: The third level of sales analysis focuses on defining what types of customers we have lost at lunch during the week, attending to two segmentations. The first by party size (number of clients grouped) and the second by average spending. To do this, a table like the one below is made for the time slot analyzed.
Although the loss has been generalized, we can affirm that we have lost mainly clients who come in groups of at least 3 (families?), And clients with a lower average ticket. The conclusions can be many, one possible would be that we have lost families with high sensitivity to price.
4- Analysis Level 4: The next step in the analysis of the weekend lunch sales is to see if the drop in sales has to do with the sales mix and if the average ticket is influenced by the references sold per customer and / or variations in the mix selling.
Analysis by Sales Mix Weekend Lunch
As we can see, in this case the sales mix has not changed substantially, since the fall in the number of referrals, which has been 38,1%, is very much in line with the fall in the number of clients, which has been 37,5%, while the decrease in the number of referrals per client was only 1%, going from 4,05 referrals per client in 2007 to 4,01 referrals in 2008.
However, if two relevant facts can be seen in the consumption by customers:
1- Shifting demand from main dishes to starters.
2- Significant reduction in wine consumption, some 13 percentage points above the reduction in customers.
Analyzing the sales mix can often explain the reduction in the number of customers due to the changes made from one year to the next in the offer. Thus, for example, the elimination of the cheapest dishes from the menu or their exchange for more expensive ones, can cause the loss of traffic due to flight from customers with greater sensitivity to price.
SALES ANALYSIS DIAGRAM