Abandoned in Cart
The Abandoned in Cart strategy recommends items to users that have added to cart but not subsequently purchased. This strategy encourages shoppers to return to their cart to finish checkout from email campaigns, home pages, or any user profile type setting page. Abandoned in Cart items are limited to the most recent twenty items added to cart over the last thirty days. Additionally, items added to cart, then removed to cart, but not purchased will still be recommended to shoppers as long as it is one of the last twenty add to cart actions.
By collecting and analyzing co-occurrence data based on user behavior, Constructor can recommend similar items. The result will show products a user might consider as an alternative to a particular product or set of products. For example, if a user is looking at toothpaste, this algorithm shows other types of toothpaste.
Additional customizations can be made to the strategy by adding unique conditions, specific to the business in mind. Conditions can be specific to items or based on attributes and allow for showing or hiding specific items/attributes. Items within recommendations can also be slotted into specific positions, when a recommendation pod is displayed.
Shows most popular items for a specific time frame. By default, bestsellers will show the most popular items over the last 7 days. This detail can be customized to show bestsellers over the last 7, 14, or 30 days. Customers that would like to change their current setting should contact their Customer Success Manager as this change will need to be made on the backend by the Constructor data science team.
Bundles are an advanced complementary strategy that return items which are most frequently purchased in sets together. The bundle strategy optimizes for products that are likely to be added to cart as a whole set with the primary product on a PDP. Please reach out to your customer success manager to learn more about best practices for implementing the bundle strategy.
Constructor evaluates co-purchase behavior and other conversion signals to dynamically create lists of products that users often buy together with a given item. These are often distinctly different from alternative recommendations, and are useful to use in conjunction with other suggestions or in a different context (such as a checkout page). This results in showing products a user would purchase in addition to a particular product or set of products. For example, if a user is looking at toothpaste, this algorithm shows toothbrushes and dental floss.
Just like the alternative strategy, additional customizations can be made to the strategy by adding unique conditions, specific to the business in mind. Conditions can be specific to items or based on attributes and allow for showing or hiding specific items/attributes. Items within recommendations can also be slotted into specific positions, when a pod is displayed.
A pod with this strategy will recommend items matching a filter expression provided when calling the recommendation strategy on the front-end. An example would be if you sell educational books to an audience of teachers, this strategy could be applied on product pages to show products most similar to the current product within a specific grade level. Within the parameters of the filter being applied, the most popular items will be displayed.
The requirement for this strategy is a filter expression in the specific format, that would be provided in browse or search endpoints. Several facets can be included too. Items more similar to a product can also be prioritized by providing an optional item ID. More detail about enabling and customizing the filtered items strategy can be found in this technical documentation.
Query recommendations recommend items based on what users have clicked, added to cart, and/or purchased after a zero result query. This pod is intended specifically for pages that result in zero results.
The last items the user has clicked on will be shown when utilizing this strategy. An additional note, when a user is both searching and browsing the recently viewed items will alternate between user behavior in those two areas.
This strategy focuses on items the unique customer is likely to buy. The items displayed are based on the specific user's prior behavior and are ranked highest to lowest based on this personalization score.
Remove Converted Items - By default, this feature is turned off. This means, items converted on by the customer could still show up in a recommendation pod. This feature could be turned off if it does not align with the needs of your business.
Filter out items with same naming convention - For customers with products in multiple variations, whose items are recognized as unique products, those products with the same name can be filtered to not repeat within a pod. For example, an apparel company with a product ‘corduroy pants’ that comes in multiple colors can choose to filter out items with that same naming convention (“corduroy pants”) from appearing multiple times in the recommendation pod. This feature is not activated by default but could be activated by reaching out to your Customer Success Manager.
Not Enough Items Default - If there are not enough items that meet the criteria for a particular recommendation pod, Constructor will automatically plug in another strategy to fill the remaining spots. By default, Constructor will use the Bestsellers strategy in this scenario. This logic can be turned off by request.
Personalization - By default, personalization is added on all recommendations. This feature could be turned off by request, with the exception of the ‘User Featured’ strategy as that is based entirely on personalization.