With Section recommendations, you can create a custom page with recommended products divided into sections. These sections display items based on a chosen item attribute and additionally they are automatically adjusted to match the customers' preference. This type of recommendation lets the customer have a product overview, with the items relevant for them, chosen by the AI-based models. In this use case, you can find an instruction on creating a recommendation for a retail website that consists of 5 rows of categories with 4 items for each category type. The categories of the products are represented in the following way: "Clothing > t-shirts and tops > t-shirts > long sleeve". However, we would like to present the section with a smaller granularity of categories, for example, "Clothing > t-shirts and tops". ## Prerequisites --- - The [items feed](/docs/ai-hub/recommendations-v2/item-feed-requirements) must be provided. - You must [configure the AI engine](/docs/settings/configuration/ai-engine-configuration/engine-configuration-for-recommendations): - Enable the Section page model. - In the **Attributes for distinct filters** section, you must select the attributes which will be available for use in the **Item attribute** field when [creating a section page recommendation](/docs/ai-hub/recommendations-v2/creating-section-recommendations#configure-item-settings). In the **Item attribute** field you will choose the item feature (for example, brand) based on which the items will be selected for a slot in the recommendation. If this step is skipped, the field will remain empty, making it impossible to complete the recommendation. Optionally, you can provide [metadata catalog](/docs/ai-hub/recommendations-v2/item-feed-requirements). ## Create a recommendation --- 1. Go to

**AI Hub > (AI Recommendations) Models > Add recommendation**. 3. In the top left corner, enter the name of your recommendation. 4. In the **Type & Items feed** section, click **Define**. 5. From the **Items feed** dropdown menu, choose the provided feed. 6. Choose the **Section** recommendation type. 7. Under the section types, from the dropdown list, choose your **Metadata catalog**. 8. Click **Apply**. 9. In the **Items** section, click **Define**. 10. Click **Add slot**. 11. Set the **Number of sections** option to 5. 12. Set the **Number of items per section** option to 4. 13. From the **Items attribute** dropdown, choose the `category` attribute. 14. In the **Category level** input area that appears, define the category level as a numeric value, in our case 2.

If your products categories have a `X > Y > Z` structure, level 0 will be `X > Y > Z`. Level 1 will be `X > Y` and so on. Here, you are defining how granular the category recommendations will be. For example, if you sell shoes, you will have a `Outdoor > Sport > Running` category and a `Outdoor > Sport > Football` category. If level 0 is provided, both categories can be recommended. If level 1 is provided, `Outdoor > Sport` category will be recommended to the customer.

15. Click **Apply**. 16. In the top right corner, click **Save**. ## What's next --- You can display the recommendation on your home page, use [dynamic content](/docs/campaign/dynamiccontent). 1. Go to **Experience Hub > Dynamic content > New dynamic content**. 2. In the body of the dynamic content, use the recommendation insert.

Click here to display the insert

{% recommendations3 campaignId=aIEkwqXw0wLB %} {% for slot in slots_products3 %} {% for row in slot.rows %} <!-- Variable metadata which allows you to access the metadata catalog --> {{ row.metadata.itemId }} {{ row.metadata.imageLink }} <!-- Iterates through items in a given section --> {% for item in row.items %} {{ item.itemId }} {{ item.title }} {% endfor %} {% endfor %} {% endfor %} {% endrecommendations3 %}

Read more about how to use recommendation in inserts [here](/developers/inserts/recommendations-v2).

3. Add CSS and/or HTML to the dynamic content. 4. [Define the rest of the settings](/docs/campaign/dynamiccontent/creating-dynamic-content). ## Check the use case set up on the Synerise Demo workspace --- You can check the [recommendations](https://app.synerise.com/ai-v2/recommendations/Ms42quPJDmQG) which let you implement described basic AI Search on your website. If you’re our partner or client, you already have automatic access to the **Synerise Demo workspace (1590)**, where you can explore all the configured elements of this use case and copy them to your workspace. If you’re not a partner or client yet, we encourage you to fill out the contact [form](https://demo.synerise.com/request) to schedule a meeting with our representatives. They’ll be happy to show you how our demo works and discuss how you can apply this use case in your business. ## Read more --- - [Recommendations](/docs/ai-hub/recommendations-v2)