#### AUT

Calculates the average number of units per transaction

##### Quick Calc

AUT = Unit Sales / Number of Transactions

##### Aliases

Average Unit Per Transaction
Average Units Per Transaction
AUT
Units Per Transaction
UPT

Dashboard View

# Definition

The average units per transaction, or AUT, is a primary Key Performance Indicator (KPI) that measures the average number of units purchased in a typical transaction value. The AUT is used as a lever to increase or decrease sales and margin.

In grocery, units are sometimes measured using weight, such as pounds or kilograms. Grocers and manufacturers may also create a standard unit which is a converted value that represents a common unit of measure. For example, two pounds might equal one standard unit and one unit might equal one standard unit, so two pounds equals one unit.

The AUT is typically combined with AVT, foot traffic counts, and/or conversion to determine the change in unit profitability caused by a change in strategy. For example, if marking down end of seasonal product resulted in 10% increase in the AUT,  the foot traffic remained stable, and the AVT increased, then the overall margin dollars should increase proportionally.

#### Calculation

AUT is calculated the following way:
AUT = Unit Sales / Number of Transactions

#### Dimensions

The AUT is generally calculated on the time and location hierarchy. While it is possible to calculate AUT on the product hierarchy, it is used for very specific types of analyses.

Time Hierarchy:  Can be used on any time dimension such as intra-day, daily, weekly, etc.
Location Hierarchy:  Can be used for one location or multiple.

# Example

AUT is a straightforward calculation, but as with any metric, you should always cleanse and understand your data to ensure you’re obtaining the actionable values. More about the nuances are discussed in the analysis section below.

AUT = Unit Sales / Number of Transactions

Let’s say we have three stores and we are interested in obtaining the AUT for last month and we also want to compare it to last year’s (LY) AUT.  Here is the data we’ll need:

For example, the AUT for Store 1 for last month is 20 units.

AUT = Unit Sales / Transactions = 250,000 / 12,500 = 20

# Analysis

The example above, as simple as it is, demonstrates the numerous ways AUT can be interpreted.  AUT belongs with other KPI metrics so that any changes from period to period can be evaluated in context. Typically, AUT is combined with the following comp metrics:

In our example above there are three stores each with different store opening dates, different product assortments, and different sales volumes, each highlighting the need to evaluate AUT more carefully.

• Store Openings:  Store 2 opened this year, so we don’t have a last year value for it.  This also means that when we add up last year data in aggregate we need to exclude this year’s data for Store 2 so we can obtain a comparative value.
• Product Assortments:  All three stores have different product assortments, which makes an aggregation hard to interpret. Ideally, the AUT should be broken down by the product assortment sub groups, like Men’s and compared only to other stores that sell Men’s.
• Sales Volumes:  Not every store sells the assortments in the same proportions.  If a store sells Women’s better than another and it sells twice the volume, it will disproportionally skew the AUT. This analysis above all others opens up another level of optimization, because it means some stores may be more sensitive to promotions and affinities.

Other nuances to consider:

• AUT Stability: For some retail formats, like discount or outlet, the AUT tends to be very stable. The stability can be used to determine the likelihood of substitution sales or the impact a stockout has on missed sales. For luxury, or slow selling retail formats, AUT can vary widely.
• Promotions: Any reduction/increase in price will have a direct impact on AUT. Promotions such as buy-one-get-one, or BOGO, can have a big impact on the AUT as well.
• Discount or Markdown Rate: When comparing AUT from one time period to another, it’s worth taking a look at the overall discount or markdown rate to gauge whether the comparison is in context.
• Percentage of Assortment Tagged as Markdown:  When there is a relative abundance of markdown product in the store, customers tend to reach for the lower priced items like during an end of season. For stable AUT retail formats, customers may spend the same, but the AUT will increase. The markdown product may provide an explanation.