With our statistics you get a good overview of the statistical data of your business or your franchise system.
General:
You create the individual statistics by selecting the store(s). You can further define the time period and even restrict it to certain times. Use the dropdown to select the statistics you want.
Should you want to make a store comparison for individual statistics, then select the "Individual Store Statistics" option.
Furthermore, you can also filter by order source and order type by selecting the options provided.
Article statistics:
The item statistics will show you which items you have ordered and in which time period. By clicking in the table header, e.g. on quantity, you change the order.
Complaint vouchers:
The complaint vouchers statistic shows you which complaint vouchers were issued and when they were redeemed. Complaint vouchers must be created as vouchers and can be deposited with the customer in the checkout using the "Complaint" button.
Outgoing order channel:
With the statistics "Outgoing order channel" you have a clear view of the distribution of your sales. You can see here, for example, how many orders are collections.
If you click on the line Personnel, you will get a listing of the personnel sales of the employees.[
Incoming orders channel:
In the statistic "order entry channel" you get an evaluation about the origin of your orders. You can see here, for example, how many orders come from your webshop or order portals.
Order frequency:
The statistic "Order frequency" shows you in which period how many customers have ordered more than once. Of course, your goal should be to ensure that existing customers order more than once. To make it easier for you to draw conclusions about causes, we also show you, among other things, how delivery times compared in the selected period.
Driver statistics:
The driver statistics show you how your drivers compare.
Coupons & Discounts:
This statistic shows you all redeemed vouchers and discounts in comparison. You can thus very easily check the success of your marketing campaign.
Heatmap:
With the heatmap, you can check the local distribution of orders and also see the order volume in the different zip code areas. Furthermore, after you have let the statistics load once, you also have the option of displaying the sales in the surrounding area and the radius in the delivery area. To do this, activate the switches below the dropdown for the various statistics.
Customer area:
The "Customer area" statistic shows you the time course of new registrations and usage.
Delivery portals:
Here you can see the distribution of orders from the various ordering portals, e.g. Lieferando. A drop-down menu can also be used to list the evaluation of orders by postal code.
Delivery portals acceptance/rejection: Here you can see the distribution of accepted and rejected portal orders, e.g. Lieferando.
New customers:
In the new customer statistics, you get an overview of the customers who have ordered from you for the first time.
Store comparison:
The store comparison allows you to compare your different stores in terms of key metrics. If you have been using SimplyDelivery for more than a year, it is also possible to view a comparison with the same period last year. To do this, click on the store name in the list.
Hours:
Under Hours, you can see the order volume broken down by the respective hourly periods.
Daily sales:
In this statistic you can see the different days in comparison to each other in terms of sales.
Sales statistics: If you use an employee login at the checkout, you can use these statistics to track the sales of your employees. This is extremely useful for using a bonus system for employees who, for example, have been particularly good at promoting a particular product or have generally completed a large number of orders.
Merchandise sales groups:
If you have created sales groups, you can make a corresponding evaluation here. With click on (Arikelliste) in the list you get again a listing of the calculations on which the article stood.
Material groups:
The product group statistics shows you at a glance how the sales are in the various product groups. Clicking on the product group opens a list with the respective products of the product group.
Merchandise groups (detailed):
In contrast to the normal product group statistics, the totals per product group are calculated for all product groups of an article, i.e. if an article is assigned to two product groups, it will be added up in two product groups in terms of number and total.
Driver waiting time:
The "Driver waiting time" statistic measures how long drivers had to wait, on average, before you could roll out the next order. In conjunction with the "Time in the kitchen" statistic, you can measure the efficiency or utilization of your kitchen staff.
Example:
Registration 08:00
First tour 08:15-08:22
Second tour 08:45-09:16
Break from 09:16-09:46
Third tour 09:50-10:12
End of shift at 10:15
It is calculated:
The times between all tours:
08:45 - 08:22 => 23 minutes
09:50 - 09:16 => 34 minutes => 57 minutes
The break time is subtracted from this if it did not occur before the first tour or after the last tour.
57 minutes - (09:46-09:16 => 30 minutes ) => 27 minutes
The time from the last tour to now/end of shift is not added, even if the driver waited during the time, because specifically the time between two tours should be evaluated.
So the driver has waited twice (number of tours-1 => 3-1 = 2) with a total waiting time of 27 minutes.
So on average he has waited 27/2 = 13:30 minutes.
Notes:
1) If a driver is not logged out in the evening and starts tours again the next day, he has waited all night for the one tour.
2) In the examples, the seconds values were omitted, but are also taken into account.
3) If drivers do tours and they don't assign tours to each other until later, then the kitchen times are also skewed.
Weekdays:
Compare different weekdays according to your order volume. Clicking on the respective day will also open a list of order periods.
Payment types:
In the statistics "Payment types" you can see all payment types in comparison.
Payment types (without tax breakdown):
Similar to the normal payment type statistics only without a subdivision by taxes.
Time in the kitchen:
The "Time in the Kitchen" statistic shows you, in different time ranges, how long an order took from the time it arrived at the store to the time it was taken away by the driver. In conjunction with the "Driver waiting time" statistic, you can measure the efficiency or utilization of your kitchen staff.
Example:
The difference between "invoice number generated" ( => kitchen receipt printout) and tour start is calculated for all delivery orders (no pre-orders, no cancellations).
These times are added up and divided by the number of the orders.
Example (deliveries only):
Order 1:
Re-date: 08:21
Tour start: 08:31 => 10 minutes
Order 2 (cancellation)
Re-date: 08:23
Tour start: 08:44 => 0 minutes, because of cancellation
Order 3:
Re-date: 08:27
Tour start: 08:45 => 18 minutes
Order 4:
Re-date: 08:35
Tour start: 08:45 => 10 minutes
Kitchen time: (10+18+10) / 3 = 38/3 => 12:40 minutes
Notes:
1) If a driver is not signed out in the evening and tours again the next day, he has been waiting all night for the one tour to be completed
2) In the examples, the seconds values have been omitted, but they are also taken into account.
3) If drivers drive tours and they assign themselves the tours later, then the kitchen times are also distorted.