Creating section recommendations

Section recommendations allow Synerise users to promote the items on the website by displaying any number of sections. These contain items selected based on the feature of the item and additionally personalized for every customer.

It means that users can create separate areas on the website that include personalized recommendations of items based on brand, category, color, price, or any other attribute included in the item catalog.

Distributing recommendations


You can use the ID of the recommendation and insert it in other types of communication, such as:

  • dynamic content - this way you can show the recommendations on your website.
  • email - this way you can send out recommended items through emails.
  • mobile application - you can use documents to build your own mobile app and show the recommended items.
  • mobile push - you can send recommendations through notifications in your mobile application.
  • web push - this way you can send notifications to your customers through a web browser.
  • SMS - this way you can reach your customers with recommendations on their mobile.

Requirements


Select feed and recommendation type


Select the feed from which items will be sourced to recommendations and the type of recommendations to be displayed.

  1. Go to Communication icon Communication > Recommendations v2 > Add recommendation.
  2. Enter the name of the recommendation (it is only visible on the list of recommendation).
  3. In the Type & source section, click Define.
  4. From the Catalog dropdown list, select an item feed.
  5. Below, select the Section page recommendation type. If the recommendation is greyed out, it means the AI engine is not trained yet.
    Note:

    You can find more information about:

  6. Optionally, from the Metadata catalog dropdown, select the catalog that include additional information about items in your feed.
    Note: More information about metadata catalogs is available here.
  7. Confirm the settings by clicking Apply.

Configure item settings


The next step is to define the items to be displayed in the recommendation frame.

Managing recommendations slots

You can use slots to assign space in your recommendation frame to specific items. In the settings of a single slot, you can declare the number of items, the attribute based on which the items will be generated.

  1. In the Items section, click Define.
  2. If you’re adding more than one slot and want to define the order of displaying them, toggle the Keep slots in order option.
    • When the option is disabled, the slots will be arranged according to their score in the recommendation and boosting factors.
    • When the option is enabled, the numbers next to the names of the slots indicate their display order.
  3. Click Add slot.
  4. In the Number of sections field, enter the number of rows you want to dedicate to display recommendations.
  5. In the Number of items in a section, enter the maximum number of items to be displayed in one section.
  6. From the Item attribute dropdown, choose the feature of the item based on which the items will be selected to the section or sections in the slot.
  7. To manage the variety of items in the sections, use Static filters and Elastic filters.
    Elastic filters explained

    Apart from selecting the items to be displayed in the recommendation frame, the elastic filter supplements the recommendation frame if it’s not entirely filled up with 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 displayed in the recommendation frame, then the empty slots will be filled with items which do not match elastic filter (based on scoring of each model).

    Static filters explained

    When you use a static filter, it shows the fixed number of items that match the conditions of the filter. If there are not enough items to fill in the recommendation frame (the number you entered in the step 2), the recommendation frame is not displayed at all.


    Note: You can learn more about filters in recommendations and see examples of use.
  8. Save the changes by clicking Apply.

Define the boosting factors


You can influence the arrangement of items in the recommendation, which is by default arranged according to a score provided by the model (the type of recommendation selected). You can boost the items in two ways (both can be used at the same time):

  • Metric boosting uses pre-defined item popularity metrics to influence item scoring.
  • Attribute boosting influences item scoring depending on rules applied to the item’s attributes. This is done by applying a filter to items and adjusting the score of those items that match the filter. For example, you can increase the scoring of a particular brand without excluding other brands entirely.
An example of a Boosting section, with metric boosting used to promote items and attribute boosting used to demote items
An example of a Boosting section, with metric boosting used to promote items and attribute boosting used to demote items
  1. In the Boosting section, click Define.
  2. Metric boosting:
    1. Click Select and select a metric to use for adjusting the score.
    2. Choose the Promote (default) or Demote option.
    3. Use the slider to determine how much you want the metric to influence the score of the items.
  3. Attribute boosting:
    1. Click Add rule.
    2. Click the created rule to open its settings.
    3. In the Items scope section, click Define filter.
      Items that meet the filter will have their scores adjusted. To learn how to build filters, see Recommendation filters.
    4. Choose the Promote (default) or Demote option.
    5. Use the slider to determine how much you want the metric to influence the score of the items.
  4. Confirm the settings by clicking Apply.

Additional settings


  1. In the Additional settings section, click Define.
  2. If you want to exclude items that the customer already purchased, enable the Exclude already bought products option.
  3. If you want to sort the items, select a metric from the Sorting metric dropdown list.
  4. If the recommendation type you selected has default filters defined, you can disable them by using the Default filters toggle.
    Important: When the default filters and the filters defined in the recommendation are mutually exclusive, recommendation filters take precedence. You can find more information on configuration of default filters here.

Saving the recommendation


To save the recommendation:

  • as a draft, click Finish later.
  • and activate the recommendation, click Save.

Once you activate the recommendation, you can use it as described in the Distributing recommendations section.

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