Filters can apply additional logic on top of recommendation results served by the AI engine.
They are used in two situations:
- For filtering, to exclude or include items from a recommendation.
- For score boosting, to promote or demote matching items.
Filtering concerns all attributes of items that you declared to be filterable while configuring AI engine and also you can use static customer attributes such as
birthdate, segmentations, and tags.
The acceptable format of the attributes include: string, integer, float, boolean, nested objects, and arrays.
The attribute names are case sensitive, however the filter values are not. So, the filter
brand == "ABC" is equivalent to
brand == "abc", but different than
Brand == "ABC".
Before you create the filter rules, you must decide which filter type you will use:
This type of filter allows you to select the items to be included in the slot and supplement the slot if it’s not entirely filled up with the items.
For example, if you select to display up to 10 items, and you have only 5 items that meet the conditions of elastic filter to be included in the slot, then the slot will be filled with additional items which do not match the elastic filter (based on scoring).
This type of filter allows you to show a fixed number of items that match the conditions of the filter.
- If the applied filter conditions (that don’t include any customer context) are too strict and there are not enough items to fill in the recommendation slot, the slot is not generated at all.
- If the filter conditions include customer context from one of the following sources: aggregate, expression, or a profile attribute, and the context cannot be retrieved for any reason:
- By default, the filter is ignored and the slot will be generated without applying the filters.
- If Fail slot when the context is missing is selected from the Ignore filter dropdown list, the slot is not generated at all.
This type of filter allows you to increase the variety of items included in the slot. You can define the allowed number of items that share the same attribute value to be shown, for example, a number of items that have the same brand, color, shape, category, and so on.
For all recommendation types except for Last seen, the engine considers up to 1000 items with the highest score that match the recommendation type. For example, if you selected the Cross-sell type, the engine analyzes up to 1000 items that match the cross-sell recommendation type, and then selects the number of items you chose to include in the slot.
For the Last seen recommendation type, the engine considers the last 100 page visit events. Based on the data from these events, the engine selects the number of items you chose to include in the slot.
Filter building methods
You can create filter rules by using two filter wizards:
- Visual Builder - You can construct the filter conditions similarly to creating a segmentation in the Analytics module. The list below presents the features available in the wizard:
- Creating separate filters and then defining conditional dependencies between them
- A separate option for matching/not matching filter conditions
- A separate option for defining formula of conditions
- Lack of the elements: functions, take none and take all options (available in the IQL Query wizard)
- The range of options available to build filter conditions and the form of building the conditions may restrict the scope of business applications
- IQL query - Advanced
may construct a formula of the filter, which is similar to creating expressions. The list below presents the capabilities of the wizard:
- Possibility to create filter conditions for advanced business applications
- Building one formula involves all conditions and dependencies between them
- Additional elements that visual builder lacks: functions, segmentations, tags, take all, and take none options
While building the filter conditions, remember about the limits.
In the visual builder, you need to define the filters by:
- selecting one or more attributes
- describing the condition for the attribute using operators and their values
- defining the dependency between the filters by preparing a formula
- An item feed is already chosen and filterable attributes have been defined.
- From the dropdown list, select an attribute of an item (in this example,
brandis the selected attribute).
Result: The Operator button appears.
category attribute allows for additional settings. Its structure represents the hierarchy of categories that the item belongs to (read more here).
It allows you to define what part of the category should be taken into account by the filter. For a given category value, you can define the part using the level range.
- Positive values define how many subcategories from the right should be dropped.
For example, if the category is “X > Y > Z” the level range is
1, the resulting category value is “X > Y” (Z is dropped).
- Negative values define how many subcategories from the left will be included.
For example, if the category is “X > Y > Z” the level range is
-1, the resulting category value is “X” (only X is included).
Describing conditions by operators
The next step is defining the conditions concerning the selected attribute by using operators. The list of operators contains:
- Is defined - If the selected attribute has any other value than
null. For example, if a filter is set to “
brandis defined”, the result contains only those items which have a specified brand (in the item feed).
- Equal - If the selected attribute has an exact value. For example, if a filter is set to “
acme”, then the result contains items of Acme brand.
- Does not equal - It excludes a particular value of an attribute. For example, if a filter is set to “
branddoes not equal
acme”, then the result contains all items except for the items of Acme brand.
- In - It checks whether the attribute is present in a selected array(s). For example, if a filter is set to “
red, blue/array/”, then the result contains all items that are in the red and blue color.
- Not In - It checks whether the attribute is not present in a selected array(s). For example, if a filter is set to “
red, blue/array/”, then the result will not contain items in red and blue color.
- Less than - For example, if a filter is set to “
50”, then the result contains items that are cheaper than 50 dollars (or other currency you use).
- Less than or equals - For example, if a filter is set to “
attribute.sizeless than or equals
43”, then the result contains items of size 43 or less.
- More than - For example, if a filter is set to “
10”, then the result contains those items whose quantity in your stock is greater than 10.
- More than or equals - For example, if a filter is set to “
discountAmountmore than or equals
20”, then the result contains items which are discounted by $20 or more.
Defining the values of operators
The examples presented in the Describing conditions by operators section already contain the value of the operator. The list of values is as follows:
Value from the list
Out of the list of attributes sourced from the feed, you select one, like in the example: “
The filters of any recommendation type can use the attributes of the item that the customer is currently browsing. For example, you can create a filter that shows items with the same category as the viewed item:
Customer context value
It allows you to use the customer attribute as the value of the item attribute. For example, you can filter displayed items by size, using the size value stored in an attribute of a customer who displays the recommendation.
This value type is only available for the In operator.
It lets you include items whose attribute matches a value from an array.
You can use it with attributes whose values are strings, numbers, and arrays. If you compare an array to an array, at least one value between them must be the same.
To define an array:
- Click 0 items.
Result: A pop-up appears.
- In the text box, you can paste the array from a notepad, enter values manually or you can select values from the dropdown list.
- Confirm your choice by clicking Add.
- Save the array by clicking Apply.
Result: The output of the filter conditions in Figure 5 will include items whose color attribute contains at least one of the colors defined in an array.
Allows you to select an aggregate as a value of the attribute from the item catalog.
- The aggregate result must match the item attribute type defined in the feed. For example, if the attribute of an item is a number (price), you must select an aggregate that produces a number as the result.
- You can use two various aggregates or expressions, or one expression and one aggregate. This limit applies per one recommendation campaign for filtering and boosting options. Multiple occurrences the same aggregate count as one towards the limit.
- If the condition contains an aggregate whose result is null, this condition is skipped, unless it’s the only condition.
nullas a condition in an aggregate is impossible. Using a
nullvalue as a string is not supported.
Allows you to select an expression as a value of the attribute from the item catalog.
- The expression result must match the item attribute type defined in the feed. For example, if the expression of an item is a text string (favorite color of the customer), you must select the expression that produces a result which is a text string as well.
- You can use two various expressions or aggregates, or one expression and one aggregate. This limit applies to one recommendation campaign for filtering and boosting options. Multiple occurrences the same expression count as one towards the limit.
- If the condition contains an expression whose result is null, this condition is skipped, unless it’s the only condition.
nullas a condition in an expression is impossible. Using a
nullvalue as a string is not supported.
You can create it through the IQL Query builder. It allows you to define the advanced conditions, which can be done with the available operators and its value types. For example, if you want to display in the recommendation frame items which are discounted more than the currently viewed item.
Defining filter conditions
You can define how filters coexist by defining the dependency between them by using logical operators. Below you can find exemplary configuration of filters.
The IQL Query wizard allows for a greater flexibility of creating the formula of the filter due to the wide range of elements and the possibility combine them using mathematical operators.
Elements of the formula
The filter formula can be built of the following elements:
String (a sequence of characters)
Array (a group of elements)
Take All (include all items)
Take None (include no items)
- Attribute - any parameter from the product feed
- Item Context - a parameter of an item a customer is currently viewing
- Customer Context - a customer attribute you can use as an item parameter value
FunctionsClick to see the list of functions
Function Description Syntax & Example of use ADD Adds a constant to value of a selected variable 1. Syntax 2. Example of use In this example, the result includes items which are more expensive than the item the customer is currently browsing. AVG Returns the average value of a selected attribute (for example, a shoe size) 1. Syntax 2. Example of use In this example, the result includes items that have the average size in relation to size of the item the customer is currently browsing. CATEGORY Allows to define the categories to be included or excluded while filtering items 1. Syntax 2. Example of use In this example, the result includes items of exactly the same category as the item the customer is currently browsing. In this example, all items that belong exactly to
Electronics > Phones and Smartphones > Smartphones, or in one of the subcategories of
Electronics > Phones and Smartphones > Smartphonesare included in the result. The filter also includes items that have the category defined in the
additionalCategoriesparameter.Note: The number allows to manipulate the category value. A positive number defines how many subcategories from the right should be dropped. If in the second example
0was replaced with
1, these would be the categories included in the filter:
Electronics > Phones and Smartphones. A negative number defines how many subcategories from the left should be included. If in the second example
0was replaced with
Electronicswould be included in the filter.
IF Allows logical comparisons between values and defining actions to be performed when the condition is met or not. 1. Syntax 2. Example of use Explanation is available in the Examples of use section (example 3). MULTIPLY Multiplies the value of a variable by a specified constant 1. Syntax 2. Example of use In this example, the result includes items whose final price is higher than the price of the item the customer is currently browsing multiplied by
MIN This function returns the lowest value in a set of values 1. Syntax 2. Example of use In this example, the result includes items whose size is larger than the smallest size of the item the customer is currently browsing. MAX This function returns the highest value in a set of values. 1. Syntax 2. Example of use In this example, the result includes items whose size is larger than the largest size of the item the customer is currently browsing. NOT Negates a filter 1. Syntax 2. Example of use In this example, the result includes items of all colors except for pink.
The elements of the filter formula can be combined with the following mathematical operators:
- Apart from the symbols of mathematical operations such as addition, subtraction, multiplication, or division, you can use operators such as
ORhave the same function in the formula as
ORin the Visual Builder (which is defining conditional dependencies between filters).
INoperator works the same in both wizards and allows you to check if a value is included in an array. The first argument is a value, and the second is an array.
HASoperator is available only in the IQL wizard. It allows you to check if an array includes a value. The first argument is an array, and the other is a value.
- The brackets
()let you group elements, for example to dictate the order of mathematical operations.
Creating a formula in the wizard
Using the elements listed above and mathematical operators, you can create a filter formula that defines the conditions an item must meet in order to match the filter.
In the tutorial below, the condition of the filters states that the recommendation displays only items that are of the same brand as the item currently displayed by a customer and the number of available items in the stock is higher than 12. If an item doesn’t meet two conditions simultaneously, it won’t be included in the result of the filter.
Comparison between filters
The table below shows the same business application of the filter in the two filter wizards. The further parts of the article include the explanation of the similar examples as those presented in the table.
|Visual Builder||IQL Query|