Loyalty programs are designed to guide customers through specific marketing scenarios in accordance with the loyalty point thresholds they reached. You can make recommendations the essence of these scenarios. This use case focuses on a recommendation that presents 4 items above $500 for the customers in the VIP segment. Very often, VIP customers have additional discounts such as vouchers for a specified amount, the consumption of which from the seller's perspective should not excessively diminish the profit margin from the customer's purchases. Using the information about the VIP segment to which the customer belongs, we can recommend items from the highest price range or those whose margin allows the customer to "safely" use the discount. ## Prerequisites --- - Enable the [personalized recommendation model](/docs/settings/configuration/ai-engine-configuration/engine-configuration-for-recommendations). - Assign a VIP tag to your customers.

Assign the tag to the customers who meet your requirements for premium customers.

## Create a recommendation --- 1. Go to

**AI Hub > (AI Recommendations) Models > Add recommendation**. 2. Enter a meaningful name of the recommendation. 3. In the **Type & Items feed** section, click **Define**. 1. From the **Items feed** dropdown list, select the catalog that contains items for the recommendation. 2. As the type, select **Personalized**. 3. Click **Apply**. 4. In the **Items** section, click **Define**. 5. Click **Add slot**. You can name the slot for later reference. 5. In the **Number of items** subsection, set the minimum and maximum number of items to `4`.

Setting the minimum and maximum number of items to the same number ensures that exactly this many items will appear in the slot.

6. Click **Static filter** and choose **IQL Query**.

Learn about the difference among [elastic, static filters](/docs/ai-hub/recommendations-v2/creating-recommendation-campaign#select-conditions-of-displaying-items), and [distinct filters](/docs/ai-hub/recommendations-v2/creating-recommendation-campaign#distinct-filter).

7. Click **Select** and from the dropdown list, select **Function**. **Result**: The **ADD** function appears. 8. Click **ADD** and from the dropdown list, select the **IF** function. **Result**:

8. Click the first **Select** node. 1. From the dropdown list, select click **Client Tags**. 2. Next to the **client.tag** node, click the

icon. 3. From the dropdown list, select **String**. 4. Click the **value** node. **Result**:

appears below. 3. Click **Manual value** and choose **Tag**. 4. Click **Select value** and choose the tag that specifies if a customer is a VIP customer. In this example, it is `VIP`. 6. Between the **client.tag** node and the **VIP** node, change the plus sign to **HAS**. 9. Click the next **Select** node in the **IF** function. 1. From the dropdown menu, choose **Attribute**. 2. Click tne **null** node. **Result**:

appears below. 3. Click **Select value** and choose the attribute that describes the items' price. 4. Next to the price attribute, click the

icon and choose **Number**. 5. Click the **0** node. **Result**:

appears below. 6. Enter the bottom price limit for items. In our example, it is `500`. 7. Between the price attribute and the 500 nodes, click on the

icon. 8. Choose

(greater than or equal). 10. Click the last **Select** in the **IF** function. 11. From the dropdown menu, choose **Take all**. **Result**:

The final configuration of the IQL query

11. Click **Apply**. 12. In the **Items** section, click **Apply**. 13. In **Boosting**, you can enable [boosting](/docs/ai-hub/recommendations-v2/creating-recommendation-campaign#define-the-boosting-factors). 14. In **Additional settings**, optionally, you can exclude already bought products and set a metric to sort by. 15. Save the recommendation by clicking **Save**. ## What's next --- You can display the recommendation to customers in a number of ways, for example by using the [recommendation insert](/developers/inserts/recommendations-v2) in [dynamic content](/docs/campaign/dynamiccontent/creating-dynamic-content). ## Check the use case set up on the Synerise Demo workspace --- Check the [recommendations settings](https://app.synerise.com/ai-v2/recommendations/Ut9xo2SHlBis) in Synerise Demo workspace. 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 --- - [Building elements in IQL builder](/docs/ai-hub/recommendations-v2/recommendation-filters#elements-of-the-formula) - [Creating recommendations](/docs/ai-hub/recommendations-v2/creating-recommendation-campaign) - [Filters in recommendations](/docs/ai-hub/recommendations-v2/recommendation-filters) - [Requirements for item feed](/docs/ai-hub/recommendations-v2/item-feed-requirements) - [Tags](/docs/assets/tags)