Repeat order

Repeat Order returns a list of customers who have made a repeat purchase during the chosen date range. For example, return all customers who made a repeat purchase within the previous 6 months:

Important

Repeat Order identifies a repeat purchase by comparing purchases within the chosen date range to all purchases. For example, a customer who first purchased 2 years ago, and then purchased again last month would be returned by a relative date range “today - 1 month”. A customer who first purchased 10 years ago, and then purchased again last month would also be returned. As well as a customer who first purchased 2 months ago, and then purchased again last month.

After you specify a date range you may apply filters to associate repeat orders to specific products, brands, channels, and stores. For example, return all customers who made a repeat purchase of shoes from your ACME Footwear brand.

What are purchase behaviors?

Purchase behaviors are a feature of Amperity that are built on top of standard output for transactions (orders and items). Purchase behaviors require standardized product catalog field names to be present in your standard output for transactions.

Use purchase behaviors in segments to return a list of customers, and then filter that list of customers by any combination of brand, channel, individual items in your product catalog, and store.

Purchase behaviors are available for first order, has not purchased, has purchased, most frequent order, repeat order, and total value of orders.

How repeat order works

Repeat Order represents a common approach people use when they build segments: find customers who have purchased more than one time within a time window, and then associate those customers to specific products and brands.

Repeat Order is a compound attribute, which means that it’s built from a combination of attributes that already exist in your data, and then appears as a single attribute that you can choose from the Segment Editor.

With this attribute, you can focus less on SQL and more on finding answers that align to your marketing goals and strategies. Purchase behavior attributes simplify the number of steps that are required to associate a list of customers to your products, stores, channels, and brands.

Tip

For more information about how Repeat Order works, including an explanation of the SQL that runs behind the Segment Editor, review the Repeat Order topic in the Amperity A-Z reference.

Use repeat order in a segment

To find all customers who made their first order within a specified date range, start with the Repeat Order attribute located under Purchase behaviors:

After the attribute appears in your segment, choose a date range:

After you specify a date range you may apply filters to associate these customers to specific products, brands, channels, and stores.

Available conditions

The following table lists the conditions that are available to this attribute.

Note

Recommended conditions for this attribute are identified with “ More useful” and conditions with more limited use cases are identified with “ Less useful”.

Condition	Description
was after	More useful Returns a list of customers where repeat purchases were after the specified time window.
was before	More useful Returns a list of customers where repeat purchases were before the specified time window.
was between	More useful Returns a list of customers where repeat purchases were between two specified time windows.
was not between	Less useful Returns a list of customers where repeat purchases were not between two specified time windows.
was not on	Less useful Returns a list of customers where repeat purchases were not on the specified date.
was on	Returns a list of customers where repeat purchases were on the specified date.

Filter attributes

A filter attribute is a standard column that is output by Amperity and is available from the Unified Itemized Transactions table. When a filter attribute is associated with a purchase behavior attribute, you may use them to filter the results by specific items in your product catalog, such as by brand, by channel, by store, or by specific details about the items in your product catalog, such as color, SKU, and so on. The list of filter attributes that will be available for product catalogs depends on their availability within your Unified Itemized Transactions table.