The average check, in general, is a fairly clear entity, just divide the sum of all payments by the number of payments and we will get the average value of one payment. But this approach has disadvantages, firstly, this approach is applicable for transactional business model, if you have something complex, for example, SaaS, you will have to look for another approach. Secondly, it is not clear how we can influence the average check taking into account the external market.

As a result, there are different formulas in unit economics that allow us to determine the average check through other metrics (product metrics) that are directly related to the business model. For example, for e-commerce the average check depends on the number of items in the shopping cart and the average cost of these items AOV = AIV×AIQ, and for SaaS the average check depends on the cost of subscription to a plan, customer lifetime on the plan, number of plans and distribution of customers by plans AOV = SUM(AIV×AIS×ALT)/SUM(AIS×ALT).

This approach allows us to understand what processes should be influenced in the business to change the average check, in addition, how to change the average check without changing the price of the product or subscription, for example, by stimulating to buy more products due to the size of the basket, display, etc., or by redistributing customers in SaaS to other tariff plans due to the distribution of functionality.