The Control Panel automatically generates a unique ID for the strategy based on the name.

You can edit the ID when you create a new strategy, but only until you save the strategy for the first time. Once you save the strategy, the ID becomes non-editable.

Select the type of page on which the recommendation is displayed. The page type determines the available algorithms.

The available page types are:

• cart: Shopping cart page or other checkout funnel page.
• category: Any page that displays information about multiple items belonging to the same group. For example: game category page, product category page
• other: Any page that does not match the other types. For example: site home page, user profile page
• product: Any page that displays detailed information about a single product or other item. For example: product page
• search: Search results page.

Define the items that are always included ("fixed") in the recommendation.

You must at minimum define either one algorithm or one fixed item for the strategy.

If a fixed item also appears in the results generated by an algorithm, the platform automatically removes the duplicate from the final set of items returned by the strategy.

Adding a fixed item

To add a fixed item:

1. Click Add item. The Control Panel adds an undefined item.

2. In the empty field, enter or select the item ID. The field automatically lists items tracked for the site.

   

3. Enter the slot number for the item. The slot number determines the item's absolute position in the recommendation results. The position is not affected by algorithms, filters, or shuffling. For example, if you set the slot number to "1", the item is always displayed first in the recommendation. You cannot enter the same slot number for multiple items.

   

Editing a fixed item

You can change the ID and slot number of a fixed item.

Removing a fixed item

To remove a fixed item, click X for the item.

Select the algorithms for the strategy. The algorithms together determine the dynamically generated set of items returned by the strategy. You can further refine the set by applying filters and affinity.

You must at minimum define either one algorithm or one fixed item for the strategy.

You can select a maximum of five algorithms. A new strategy includes a single preselected algorithm, which you can change.

How algorithms work

The platform runs each algorithm separately against the same source usage data and combines the results from the algorithms in the order in which the algorithms are selected. For example, if you have Bought together with current item - 60 days with 5 items as your first algorithm and Viewed together with current item - 30 days with 3 items as your second algorithm, the strategy returns a total of eight items: the first five items are the top five items from the former algorithm and the remaining three items are the top three items from the latter algorithm.

The platform automatically reruns the algorithms at regular time intervals, thereby periodically regenerating the recommendation data returned by the strategy. The platform reruns each algorithm separately based on its regeneration frequency. If you select multiple algorithms with different regeneration frequencies, some parts of the data returned by the strategy will be updated more frequently than other parts. To find out the frequency of an algorithm, see Supported algorithms.

Adding an algorithm

To add an algorithm:

1. Click Add algorithm. The Control Panel adds an algorithm with default settings.

2. Select the algorithm you want to use. For more information about the supported algorithms, see Supported algorithms.

   

3. Enter the maximum number of items returned by the algorithm. The algorithm will always return this many items, unless it cannot find enough items matching its criteria.

   

Changing an algorithm

You can change the selected algorithm and the maximum number of items returned by the algorithm.

Removing an algorithm

To remove an algorithm, click X for the algorithm.

Create filters to further refine the set of items returned by the strategy. You can also apply predefined filters available to certain page types

The platform applies the filters separately to the full results of each algorithm, removing items based on the filter settings. The platform then picks the top items for each algorithm, and combines the top items and any fixed items into the final set of recommended items returned by the strategy.

Adding a filter

To add a filter:

1. Click Add filter. The filter settings open.
2. Define the filter settings.
3. Click Save.

Editing a filter

To edit a filter:

1. Click Edit for the filter. The filter settings open.

   

2. Edit the filter settings.
3. Click Save.

Removing a filter

To remove a filter, click X for the filter.

Limiting the results to the viewed category

If the Page type of the strategy is category, and if you only want to return items that belong to the category currently viewed by the visitor, select Only return items whose type matches the viewed category or Only return items whose categories include the viewed category, or both. Your selection depends on whether item data for your site uses the type (string) or categories (array of strings) attribute, or both, for storing category information.

If you select both options, the strategy only returns items that pass both filters.

Limiting the results to the viewed item's categories

If the Page type of the strategy is product, and if you only want to return items that belong to the same category or categories as the item currently viewed by the visitor, select Only return items whose type is the same as the viewed item's or Only return items whose categories include at least one category to which the viewed item belongs, or both. Your selection depends on whether item data for your site uses the type (string) or categories (array of strings) attribute, or both, for storing category information.

If you select both options, the strategy only returns items that pass both filters.

Limiting the results to searched categories

If the Page type of the strategy is search, and if you only want to return items that belong to the same category or categories as the items returned by the search, select Only return items whose type matches a searched category or Only return items whose categories include a searched category, or both. Your selection depends on whether item data for your site uses the type (string) or categories (array of strings) attribute, or both, for storing category information.

If you select both options, the strategy only returns items that pass both filters.

Set the level of visitor affinity applied to the recommendation. The higher the level, the more personalized the set of recommended items is for each individual visitor.

The platform applies affinity separately to the full results of each algorithm, after first applying filters to the results. Applying affinity reorders (reranks) the items to a greater or lesser degree depending on the level of affinity selected and how closely a given visitor's affinities match the algorithm results.

The possible slider values are:

• 0% (no affinity applied, an algorithm fully determines how the items it returns are ranked)
• 25%
• 50% (affinity and algorithm have equal weight in determining how the items returned by an algorithm are ranked)
• 75%
• 100% (affinity fully determines how the items returned by an algorithm are ranked)

If a visitor's affinity is not known, the platform does not apply any affinity to the recommendation for that visitor.

For more information about affinity and how it works, see Feature: Super-Affinity.

Returns items bought together (by default, in the past 60 days) with the items the visitor has recently bought (by default, in the past 7 days). The returned items are from the same category or categories as the items bought by the visitor.

Example

The visitor recently bought the following items:

• Item A from category X one day ago
• Item B from category Y five days ago
• Item C from category Z nine days ago

The algorithm returns items from categories X and Y that visitors have commonly bought together with items A and B.

Returns items viewed together (by default, in the past 30 days) with the items the visitor has recently viewed (by default, in the past 7 days). The returned items are from the same category or categories as the items viewed by the visitor.

Example

The visitor recently viewed the following items:

• Item A from category X one day ago
• Item B from category Y five days ago
• Item C from category Z nine days ago

The algorithm returns items from categories X and Y that visitors have commonly viewed together with items A and B.

Returns items viewed together (by default, in the past 30 days) with items from the three categories that feature most in the visitor's current search results.

Example

The visitors current search returns 20 items:

• 2 items from category A
• 5 items from category B
• 8 items from category C
• 2 items from category D
• 3 items from category E

The algorithm returns items that visitors have commonly viewed together with items from categories C, B, and E.

Create one or more rules that together define the filtering logic for the filter.

A rule defines a single comparison operation between an item attribute value and a target value defined by you. The rule is used to include and exclude items from the final recommendation results: any item for which the rule evaluates to true is included, while any item for which the rule evaluates to false is excluded. The comparison is case-insensitive.

If you create multiple rules, the platform applies them all, that is, the platform treats the rules as combined with logical AND operators. The platform only returns items for whom all the rules evaluate to true.

The filter must include at least one rule. A new filter includes a single empty rule, which you can edit.

Example

If you wanted to exclude items that cost more than 100 in your site currency, you would filter for items whose price attribute value was less than or equal to 100, which would give you the rule:

price is less than or equal to 100

The platform would then evaluate every item in the algorithm results and remove any item for which the rule evaluates to false. The final recommendation results returned by the strategy would thus exclude these items. For example:

# Set of items returned by the algorithms

Item 1, price: 100
Item 2, price: 500
Item 3, price: 30

# Filter evaluation

Item 1, price: 100 -> TRUE
Item 2, price: 500 -> FALSE
Item 3, price: 30 -> TRUE

# Set of items returned by the strategy after applying the filter

Item 1, price: 100
Item 3, price: 30

For more examples, see Filter examples.

Adding a rule

To add a rule:

1. Click Add rule. The Control Panel adds an undefined rule.

2. Select the item attribute you want to use for filtering items. The field automatically lists the item attributes tracked for the site.

   

3. Select the relational operator for comparing the item attribute value to the target value. The drop-down menu only displays operators that are valid for the data type of the selected item attribute.

   

4. Enter or select the target value for the comparison. The field automatically lists the different values tracked for the specified item attribute.

   

   The target value can be either a regular string or, for one of and any one of operators, a JSON-stringified array. For regular expressions, use the RE2 syntax.

Editing a rule

You can change the attribute, operator, and value of a rule.

Removing a rule

To remove a rule, click X for the rule.