Navigate to 'Playground' in the left hand menu and then select the recommender logic you wish to use - in this case 'Also viewed items'.
Once selected, the recommender configuration options will appear below.
You can input an item ID to get items that are also viewed with that item.
If you click 'SELECT ITEM FROM CATALOG' you will be taken to a search area where you can search for products. There is also the option to select from the user's recently viewed items:
Note: the default here is the test user id so you will see products the test user has browsed.
The user id testUser will allow you to view your activity from test mode on your shop (viewable in the events monitor). You can change the current user by clicking on 'CHANGE USER' and inputting a different userId:
The userId is optional for this recommender. If you include the userId in the recommender the output will remove products that the individual has previously purchased.
You can also alter the Days span for the recommender to retrieve products also viewed in the last N days. Simply slide the slider and set it to the time period required - 24 hours, 7 days or 30 days are the most popular.
Now you can select the attributes you want to include in the API response - typically these are everything you want to include in your design in your email or on site. Standard fields include:
quantity / availability
gender / category information
You can apply filters to the recommender to filter out any unwanted products. For example, you may want to only show products from 'Womenswear' or from a specific product category, or to filter out any sale items. For more information about filtering, click here.
Once you have configured your settings you can run the recommender by clicking on the green play button. The top 10 also viewed items with the itemId input viewed items will appear in graph view:
You can view the output in different views by clicking on 'Grid view' or 'JSON view'.
To view the API call, simply click on the green API call button. You can then use this API call as required.
Once you are happy with your configuration, click on the 'CREATE RECOMMENDER' green button. You will see a popup asking for a description for your recommender. Insert a description and click save - this will create your recommender.
The recommender will available in the 'Recommenders' area of the platform where you can export it into the Kickdynamic platform as a content source.