According to the financial model and business model of different formats and brands, as well as different levels of resource mastery, a variety of new store turnover estimation methods are derived. Let's take the catering industry as an example to share several commonly used methods for estimating the turnover of new stores.
First, the estimation method of people flow
This is very common in the fast food chain industry, and the basic prediction formula is:
Daily average turnover = daily average doorway flow * grabbing rate * per capita consumption
Daily average pedestrian flow at the entrance, according to the method of pedestrian flow test, continuously measure the total pedestrian flow at the entrance of the intended store for one week, and then divide it by 7, which is the daily average pedestrian flow at the entrance. If there are special circumstances during the calculation period, such as bad weather, legal holidays, etc., it needs to be corrected. We need to find a corner to stay here for a week. We'd better record the proportion of people coming from all directions, whether by escalator or by straight elevator. Because it is time-consuming, some brands only measure the data of 15 minutes, and then *4 to estimate one hour. In fact, this is inaccurate and imprecise.
Capture rate = the ratio of the number of people passing through the door to the actual number of people entering the store. This capture rate can generally use the data of branches with similar business districts and positions of the same brand. You can also use the average grab rate of the whole brand. General fast food chain brands will sort out this data, and different business districts will have different values. In addition, if the intended store happens to do the same category, it also needs to be calculated when calculating the flow of people as a reference.
Per capita consumption data, similar to the capture rate, can refer to the data of similar stores of the same brand.
Second, similar storage (shadow) estimation method
According to the city, business circle, floor location, area, door width and other factors of the intended store, find the most similar store with the same brand and make the same estimate.
Third, the prediction method of aggregation point
For a new store that is usually used in all formats, according to the basic situation of the shopping mall, the turnover of existing old stores with similar or similar gathering points can be selected as the estimated turnover of the new site. If there are differences, the variable coefficient can be determined according to favorable or unfavorable factors.
Fourth, the evaluation method of competitive brands
Generally used at the beginning of brand building. Because there are few old shops and they are unevenly distributed in regions, cities, business districts and gathering points, it is impossible to find similar shops, so it is a remedial measure to estimate brand turnover under similar conditions.
According to the performance comparison of independent brands and competitive brands in the same city and shopping mall, the coefficient is obtained. The more shops here, the more accurate the coefficient. Then find the turnover of rival brands similar to the predetermined position and multiply it by the coefficient to get the estimated turnover. If there happens to be an opponent brand in the intentional landing, you can directly use the turnover of the opponent brand * coefficient * popularity accessibility adjustment coefficient = the expected turnover of the intentional landing.
Five, the estimation method of tourist attractions turnover
Suitable for shops in scenic spots. Because the customer base is tourists, the formula for estimating the turnover of the new store is:
Average daily turnover = total number of tourists in scenic spots /365* capture rate * per capita consumption.
The probability of capture rate has been mentioned before. In addition, if the menu price of scenic spots rises, the per capita consumption amount needs to be multiplied by the rising factor.
Chain catering brands will jointly use the above five methods when forecasting the turnover of new stores, and get the average value according to different methods, which will eventually be used as the expected turnover data of new stores. The comprehensive estimated turnover obtained in this way will be more rigorous and scientific, and of course the accuracy will be higher.