**Behavioral Data Hub > Expressions > New expression**.
2. Enter the name of the expression.
3. Set the **Expression for** option to **Event**.
4. From the **Choose event** dropdown list, select `transaction.charge` event.
5. In the **Formula definition** section, click **Select**.
6. From the list that opens, select **Function > Regexp**.
7. In the brackets, click the **Select** button and from the list, select **Event attribute**.
1. Click the **Unnamed** node that appeared.
9. At the bottom of the page, click **Choose parameter**.
10. In the list of attributes, find and select **TIMESTAMP**.
8. Click the next **Select** button in the brackets and from the list, select **Constant**.
1. Click the **0** node that appeared.
2. At the bottom of the page, type `....-..-..` for date format.
9. Save the expression.
10. Create a second expression and repeat all steps for `page.visit` event.
Behavioral Data Hub > Live Aggregates > Create aggregate.
Behavioral Data Hub > Live Aggregates > Create aggregate.
Behavioral Data Hub > Live Aggregates > Create aggregate.
Behavioral Data Hub > Live Aggregates > Create aggregate.
Behavioral Data Hub > Live Aggregates > Create aggregate.
Behavioral Data Hub > Live Aggregates > Create aggregate.
Behavioral Data Hub > Live Aggregates > Create aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
2. Enter a meaningful name of the aggregate.
3. Switch the **Show in profile card** option on.
3. Click **Analyze profiles by** and select **First** or **Last** to return the date of the first or last date customer visited the web page.
4. Click the **Choose event** dropdown list.
5. From the dropdown list, select the `page.visit` event.
6. Click **choose parameter** and search for the [expression created in the previous part of the process](#create-expressions) regarding the chosen event.
7. Using the date picker in the lower-right corner, set the time range to **Lifetime**.
8. Click **Apply**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
2. Enter a meaningful name of the aggregate.
3. Switch the **Show in profile card** option on.
3. Click **Analyze profiles by** and select **Sum** to return the time of call center calls.
4. Click the **Choose event** dropdown list.
5. From the dropdown list, select the `callcenter.call` event.
6. Click **choose parameter** and choose the `callDuration` parameter.
7. Using the date picker in the lower-right corner, set the time range to **Custom** and set to **30 days** or according to your business needs.
8. Click **Apply**.
9. Save the aggregate.
**Decision Hub > Metrics > New metric**.
2. Enter the name of the metric.
3. As a metric kind, select **Simple metric**.
4. As the type, set **Event**.
5. As the aggregator, set **Sum**.
4. As the occurrence type, set **All**.
5. From the **Choose event** dropdown list, select `product.buy`.
6. Click 
button.
**Result**: The **Choose parameter** button appears.
7. From the **Choose parameter** dropdown list, choose `$quantity`.
8. To select a specific time range, click the calendar icon. In our case it will be **Lifetime**. Confirm your choice with the **Apply** button.
9. Click **Save**.
**Decision Hub > Metrics > New metric**.
2. Enter the name of the metric.
3. As a metric kind, select **Simple metric**.
4. As the type, set **Event**.
5. As the aggregator, set **Count**.
4. As the occurrence type, set **All**.
5. From the **Choose event** dropdown list, select `product.return`.
6. To select a specific time range, click the calendar icon. In our case it will be **Lifetime**. Confirm your choice with the **Apply** button.
7. Click **Save**.
**Decision Hub > Metrics > New metric**.
2. Enter the name of the metric.
3. As a metric kind, select **Simple metric**.
4. As the type, set **Event**.
5. As the aggregator, set **Count**.
4. As the occurrence type, set **All**.
5. From the **Choose event** dropdown list, select `page.visit`.
6. To select a specific time range, click the calendar icon. In our case it will be **Lifetime**. Confirm your choice with the **Apply** button.
7. Click **Save**.
**Decision Hub > Metrics > New metric**.
2. Enter the name of the metric.
3. As a metric kind, select **Simple metric**.
4. As the type, set **Event**.
5. As the aggregator, set **Count**.
4. As the occurrence type, set **All**.
5. From the **Choose event** dropdown list, select `page.visit`.
6. Click button.
**Result**: The **Choose parameter** button appears.
7. From the **Choose parameter** dropdown list, choose `product:retailer_part_no`.
5. From the **Choose operator** dropdown list, select **String** and **Is not empty**.
6. Using the date picker in the lower-right corner, set the time range to **Lifetime**. Confirm your choice with the **Apply** button.
7. Click **Save**.
**Decision Hub > Metrics > New metric**.
2. Enter the name of the metric.
3. As a metric kind, select **Simple metric**.
4. As the type, set **Event**.
5. As the aggregator, set **Count**.
4. As the occurrence type, set **All**.
5. From the **Choose event** dropdown list, select `item.search`.
6. Using the date picker in the lower-right corner, set the time range to **Custom** and set to **30 days** or according to your business needs. Confirm your choice with the **Apply** button.
7. Click **Save**.
**Decision Hub > Reports > New report**.
2. Enter a meaningful name of the report.
3. Click the **Choose metric** and from the dropdown list, select [a metric for number of bought products, created in the previous part of the process](#number-of-bought-products).
4. From the **Range** dropdown list, select the number of top (the most frequently bought) products to be shown in the preview of the report. In this case it will be **TOP 5** products.
5. In the **Dimension** section, from the dropdown list, select **Event > Parameters**. To be able to show products name in the report, choose `$name`.
6. Click **Add dimension**.
1. Click **Choose dimension** and from the dropdown list, select **Event > Specials**. To be able to show when the product wast bought, choose `TIMESTAMP`.
8. Click **Enable filter**.
1. Click **Choose filter** and from the dropdown list, select **CLIENT_ID**.
2. Click **Choose operator** and from the dropdown list, select **Equal (String)**.
3. Change the type of value by clicking the icon until you get 
.
3. In the first field, write `clientId` and in the second field enter `.`
4. Click **Apply**.
**Decision Hub > Reports > New report**.
2. Enter a meaningful name of the report.
3. Click the **Choose metric** and from the dropdown list, select [a metric for number of returned products, created in the previous part of the process](#number-of-returned-products).
4. From the **Range** dropdown list, select the number of top (the most frequently returned) products to be shown in the preview of the report. In this case, it will be **TOP 3** products.
5. In the **Dimension** section, from the dropdown list, select **Event > Parameters**. To be able to show products name in the report, choose `name`.
6. Click **Add dimension**.
1. Click **Choose dimension** and from the dropdown list, select **Event > Parameters**. To be able to show what the product price is, choose `price`.
6. Click **Add dimension**.
1. Click **Choose dimension** and from the dropdown list, select **Event > Specials**. To be able to show when the product was returned, choose `TIMESTAMP`.
8. Click **Enable filter**.
1. Click **Choose filter** and from the dropdown list, select **CLIENT_ID**.
2. Click **Choose operator** and from the dropdown list, select **Equal (String)**.
3. Change the type of value by clicking the icon until you get .
3. In the first field, write `clientId` and in the second field enter `.`
4. Click **Apply**.
8. Using the date picker in the lower-right corner, set the time range to **Custom** and set to **90 days** or according to your business needs. Confirm your choice with the **Apply** button.
9. Save the report.
**Decision Hub > Reports > New report**.
2. Enter a meaningful name of the report.
3. Click the **Choose metric** and from the dropdown list, select [a metric for number of all page visits, created in the previous step](#number-of-page-visits)
4. From the **Range** dropdown list, select the number of top (the most frequently viewed) products to be shown in the preview of the report. In this case it will be **TOP 5** products.
5. In the **Dimension** section, from the dropdown list select **Event > Parameters**. To be able to show product's brand in the report, choose `brand`.
8. Click **Enable filter**.
1. Click **Choose filter** and from the dropdown list, select **CLIENT_ID**.
2. Click **Choose operator** and from the dropdown list, select **Equal (String)**.
3. Change the type of value by clicking the icon until you get .
3. In the first field, write `clientId` and in the second field, enter `.`
4. Click **Apply**.
8. Using the date picker in the lower-right corner, set the time range to **Custom** and set to **30 days** or according to your business needs. Confirm your choice with the **Apply** button.
9. Save the report.
**Decision Hub > Reports > New report**.
2. Enter a meaningful name of the report.
3. Click the **Choose metric** and from the dropdown list, select [a metric for number of all visited products, created in the previous step](#number-of-visited-products)
4. From the **Range** dropdown list, select the number of top (the most frequently visited) products to be shown in the preview of the report. In this case, it will be **TOP 5** products.
5. In the **Dimension** section, from the dropdown list, select **Event > Parameters**. To be able to show products name in the report, choose `title`.
6. 6. Click **Add dimension**.
1. Click **Choose dimension** and from the dropdown list, select **Event > Parameters**. To be able to show the product's price, choose `price`.
8. Click **Enable filter**.
1. Click **Choose filter** and from the dropdown list, select **CLIENT_ID**.
2. Click **Choose operator** and from the dropdown list, select **Equal (String)**.
3. Change the type of value by clicking the icon until you get .
3. In the first field, write `clientId` and in the second field, enter `.`
4. Click **Apply**.
8. Using the date picker in the lower-right corner, set the time range to **Custom** and set to **30 days** or according to your business needs. Confirm your choice with the **Apply** button.
9. Save the report.
**Decision Hub > Reports > New report**.
2. Enter a meaningful name of the report.
3. Click the **Choose metric** and from the dropdown list, select [a metric for number of all searched items, created in the previous step](#number-of-searched-items)
4. From the **Range** dropdown list, select the number of top (the most frequently searched) phrases to be shown in the preview of the report. In this case, it will be **TOP 10**.
5. In the **Dimension** section, from the dropdown list, select **Event > Parameters**. To be able to show the searched query in the report, choose `query`.
8. Click **Enable filter**.
1. Click **Choose filter** and from the dropdown list, select **CLIENT_ID**.
2. Click **Choose operator** and from the dropdown list, select **Equal (String)**.
3. Change the type of value by clicking the icon until you get .
3. In the first field, write `clientId` and in the second field, enter `.`
4. Click **Apply**.
8. Using the date picker in the lower-right corner, set the time range to **Custom** and set to **30 days** or according to your business needs. Confirm your choice with the **Apply** button.
9. Save the report.
**Decision Hub > Trends > New trends**.
2. Enter a meaningful name of the trend.
3. Click the **Choose event** button and from the dropdown list, select `page.visit`.
8. Click **Enable filter**.
1. Click **Choose filter** and from the dropdown list, select **CLIENT_ID**.
2. Click **Choose operator** and from the dropdown list, select **Equal (String)**.
3. Change the type of value by clicking the icon until you get .
3. In the first field, write `clientId` and in the second field, enter `.`
4. Click **Apply**.
9. Set the **Interval** in the lower-right conrer to **day**.
8. Using the date picker in the lower-right corner, set the time range to **Last 7 days** or according to your business needs. Confirm your choice with the **Apply** button.
9. Save the trend.
**Decision Hub > Trends > New trends**.
2. Enter a meaningful name of the trend.
3. Click the **Choose event** and from the dropdown list, select `callcenter.call`.
8. Click **Enable filter**.
1. Click **Choose filter** and from the dropdown list, select **CLIENT_ID**.
2. Click **Choose operator** and from the dropdown list, select **Equal (String)**.
3. Change the type of value by clicking the icon until you get .
3. In the first field write `clientId` and in the second field enter `.`
4. Click **Apply**.
9. Set the **Interval** in the lower-right conrer to **day**.
8. Using the date picker in the lower-right corner, set the time range to **Last 7 days** or according to your business needs. Confirm your choice with the **Apply** button.
9. Save the trend.
**Decision Hub > Dashboards > Add dashboard**.
2. Enter the name of the dashboard.
3. To add a widget to the dashboard, click an icon on the 
panel. The icons are (left to right): HTML code, text field, image, [segmentation](/docs/analytics/segmentations/creating-segmentations), [trend](/docs/analytics/trends/creating-trends), [funnel](/docs/analytics/funnels/creating-funnels), [metric](/docs/analytics/metrics/creating-simple-metrics), [histogram](/docs/analytics/histograms/creating-histograms), [aggregate](/docs/crm/aggregates/creating-profile-aggregates), [expression](/docs/crm/expressions), and a [report](/docs/analytics/reports/creating-reports).
**Profiles** and select a customer on the list.
2. On the top of the activity list, click **Statistics**.
**Result**: A set of statistics appears.
4. On the top of statistics, click the 
icon.
**Result**: A dropdown list appears.
5. Select **Manage dashboards**.
**Result**: A pop up appears.
6. On the top of the pop-up, click **Add dashboard**.
**Result**: A dropdown list appears.
7. From the dropdown list, select a dashboard.
8. To confirm your choice, click **Add**.
**Result**: The dashboard appears on the bottom of the list.
9. To manage the order of the dashboards added to the customer's profile, drag and drop them in the preferred order.
10. To save the changes, click **Apply**.
## Check the use case set up on the Synerise Demo workspace
---
You can check all configurations directly in Synerise Demo workspace:
- Expressions
- [Transaction date](https://app.synerise.com/analytics/expressions/0d844720-6bb7-4776-a661-52cc81577b06)
- [Page visit date](https://app.synerise.com/analytics/expressions/d31828b7-ef9c-4c7d-8316-3769eb8612c2)
- Aggregates
- [First transaction date](https://app.synerise.com/analytics/aggregates/7380e558-3d44-30b7-ac26-b1e233e9b16e)
- [Last transaction date](https://app.synerise.com/analytics/aggregates/d6baacd7-684e-31f6-b3c4-76376090c061)
- [Last bought product name](https://app.synerise.com/analytics/aggregates/ccbd08cc-1cd0-3b44-bc39-eb2dcd0998e5)
- [Last transaction value](https://app.synerise.com/analytics/aggregates/8a459dea-e2e7-3c99-8e9b-1b7e12f850e0)
- [Number of transactions](https://app.synerise.com/analytics/aggregates/24011aa2-632d-319f-9047-8f13712105c8)
- [Sum of all transactions](https://app.synerise.com/analytics/aggregates/55cf86a5-acd9-3540-8293-13737a495300)
- [Last returned product name](https://app.synerise.com/analytics/aggregates/d36783fa-382d-3141-8537-9c70ff53ba97)
- [Last returned product price](https://app.synerise.com/analytics/aggregates/2aee5c1f-2cbc-3961-9d07-cc15ef8550e1)
- [First page visit date](https://app.synerise.com/analytics/aggregates/b75f9b8f-01b8-3733-80cf-b31a35c46da7)
- [Last page visit date](https://app.synerise.com/analytics/aggregates/3ff1c746-488c-3f4f-b0ef-2ca09f0b593a)
- [Call center calls duration](https://app.synerise.com/analytics/aggregates/36bf88a6-e646-36cd-957e-a87c5f32a11e)
- Metrics
- [Bought products](https://app.synerise.com/analytics/metrics/077074e8-db7c-4e46-bd2e-24e292bee839)
- [Returned products](https://app.synerise.com/analytics/metrics/5772cbe8-5cef-4659-b049-383747f4a355)
- [Product page visits](https://app.synerise.com/analytics/metrics/ec561bb7-8227-4f56-9d9c-6979437fed51)
- [Page visits](https://app.synerise.com/analytics/metrics/4afbcbc7-ab8f-4bc9-8b73-2547b2dfeee2)
- [Number of searched items](https://app.synerise.com/analytics/metrics/e40f03f4-58d3-4156-9a41-776b3b2c2b24)
- Reports
- [History of bought products](https://app.synerise.com/analytics/reports/08639f32-0d6c-4b4b-a78e-4eec7a8d00cb)
- [History of returned products](https://app.synerise.com/analytics/reports/9e92b281-ef93-4cfb-9fd0-916334ef8df9)
- [Top visited brands](https://app.synerise.com/analytics/reports/2de0ad6c-3fb4-434f-8de9-1bf6b6528504)
- [Top searched queries](https://app.synerise.com/analytics/reports/1c09d8b2-fdfe-465a-b030-78f3593860e9)
- Trends
- [Page visits](https://app.synerise.com/analytics/trends/1bfa16b9-9518-4c1a-af12-9c4671048800)
- [Call center calls](https://app.synerise.com/analytics/trends/d813b0ae-aa02-4cb1-929b-de75fdbb46ac)
- [Dashboard](https://app.synerise.com/analytics/dashboards/33651c9f-666e-4a48-aa6d-7dc1cfd0d9f8?clientId=0)
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.
## Generated events
This use case does not generate any events.
## Read more
---
- [Aggregates](/docs/crm/aggregates)
- [Dashboards](/docs/analytics/analytics-dashboard)
- [Expressions](/docs/crm/expressions)
- [Metrics](/docs/analytics/metrics)
- [Behavioral Data Hub](/docs/crm)
- [Reports](/docs/analytics/reports)
- [Trends](/docs/analytics/trends)
# Personalized products on landing page
Synerise allows you to prepare a dedicated landing page containing a **personalized offer of recommended products**. You can send it via email or web push to people who were on the site but did not buy anything or didn't even add anything to their cart. This will allow you to attract their attention again after leaving the site. Also you can add a tab in the menu, like **Chosen for you**, which will redirect to such a landing page with an offer suited for a particular user.
## Example of use - Home appliances industry
Our client wanted to activate customers, who left an e-store but did not add anything to the shopping cart. They used automation to send an email message directing to the landing page with personalized recommendations after a customer had finished the session.
<!-- Downloading the AI campaign --> {% recommendations2 campaignId=cg3HBgRC5P2h %} {% for p in recommended_products2 %} <li data-snr-ai-product-id="{{p.productRetailerPartNo}}"> <a class="snrs-AI--item-link" href="{{p.link}}" title="{{p.title}}"> <img src="{{ p.imageLink }}" class="products-slider__item-image snrAI-product-image snrAI-product-image-{{p.productRetailerPartNo}}" width="90" alt="{{p.title}}" id="snrAI-image-{{p.productRetailerPartNo}}"> <h3 class="snrs-AI-product--product-name"> <span class="snrs-AI-product--name-first">{{p.title}}</span> </h3> </a> </li> {% endfor %} {% endrecommendations2 %}
**Decision Hub > Reports**.
2. From the list, select the report you created for exporting.
3. Click the **Preview** tab.
4. Click **Download CSV**.
5. Open the file in text editor and remove rows from it until 10 are left. This copy is only needed as a file sample for creating the Data Transformation.
## Create data transformation diagram
---
In this part of the process, we define the rules of modifying data before sending it to the SFTP server. Each report exported from Synerise has a column named `Value`, which contains the value of metric used in the report. For the purposes of this use case, we will change the name of this column to `number of clicks`.
The data transformation diagram which is the output of this part of the process is used later to [automate sending the data](/use-cases/export-report-sftp#create-a-workflow).
1. Go to 
**Automation > Data Transformation > Create transformation**.
2. Enter the name of the transformation.
3. Click **Add input**.
### Add file with sample data
The **Data input** node allows you to add a data sample. In further steps, you define how the data must be modified. Later, when this transformation is used in the Automation workflow, the system uses the rules created with the sample data as a pattern for modifying actual data.
4. On the pop-up, click **Add example**.
5. Upload the file prepared in [this step](/use-cases/export-report-sftp#prepare-a-file-with-sample-data).
6. Change the default delimiter to `;`.
**Automation Hub > Workflows > New workflow**.
2. Enter the name of the workflow.
### Define the launch date
3. As the trigger node, add **Scheduled Run**.
4. In the configuration of the node:
1. Leave the **Run trigger** option at default (**all time**).
2. From the **Timezone** dropdown list, select the time zone consistent with the timezone selected for your workspace.
3. Define the frequency of the workflow. In this use case, it's every day at 6:00 AM.
The workflow will automatically launch everyday at 6:00 AM.
**AI Hub > (AI Recommendations) Models > Add recommendation**.
2. Enter the name of the recommendation (it is only visible on the list of recommendations).
3. In the **Type & Items feed** section, click **Define**.
4. From the **Items feed** dropdown list, select a product feed.
6. Choose the **Top items** recommendation type.
8. Click **Apply**.
9. In the **Items** section, click **Define**.
10. Click **Add slot**.
11. Define the minimum and maximum number of products that will be recommended to the user.
In our example, it is from 3 (minimum) to 3 (maximum).
12. Optionally, add a **Static filter**.
**Experience Hub > In-app messages > Create new**
2. Enter a meaningful name for the in-app campaign.
### Define the audience
---
1. In the **Audience** section, click **Define**.
2. Select the **Everyone** tab.
3. Click **Apply**.
### Define content
---
1. In the **Content** section, click **Define**.
2. Click **Create message** and from the list of template folders, select **Predefined templates**.
3. Select **Memo game**.
**Result:** You are redirected to the code editor.
**Automation Hub > Workflows > New workflow**.
2. Enter the name of the workflow.
### Define the Audience node
---
Choose the **Audience** node as the trigger. In this step, you will select the group of customers who have visited the `decorations` category exactly 7 days before but did not make a purchase since then.
1. Start the workflow with the **Audience** node.
2. In the configuration of the node, set the **Run trigger** option to **repeatable**.
3. Set the interval to 1 per day.
4. Choose the day and time when the process starts. Choose 8 A.M. to provide plenty of time for the time optimizer to choose the best time for a particular customer.
5. Select the time zone.
6. In **Define audience**, choose **New Audience** and click **Define conditions**.
1. As the first condition, from **Choose filter** dropdown menu, choose `page.visit` event.
2. Click the **+ where** button, choose **product:category**, and then select **Equal**. As the value, enter the name of the category. In our case it is `decorations`.
3. Set the time range to **Last 1 day before 7 days**.
4. As the second condition, from **Choose filter** dropdown menu, choose the `product.buy` event.
5. Click the **+ where** button, choose **category**, and then select **Equal**. As the value, enter the category `decorations`.
6. Set the time range to **Last 8 days** to exclude the customers who have not made a purchase since the last visit in a specific category.
7. Change the **Profiles matching funnel** option to **Profiles not matching funnel** by clicking the **matching** word.
8. Click **Apply**.
**> New prediction** and select **Use Predefined scenarios**.
**Automation Hub > Workflows > New workflow**.
2. Enter the name of the workflow.
### Define the Profile Event trigger node
---
At this stage, we will configure conditions that launch the workflow. As a trigger, we will use the `nps.send` event.
1. As the first node of the workflow, add **Profile Event**. In the configuration of the node:
1. Enter the following title to the node: `nps survey`.
2. From the **Choose event** dropdown menu, choose the `nps.send` event.
2. Confirm by clicking **Apply**
{ "time": "2023-02-15T15:24:49Z", "action": "nps.sent", "label": "", "client": { "id": 5092159999, "email": "e0097757-d1e2-44ac-ba3c-d97979a354c1@anonymous.invalid", "uuid": "e0097757-d1e2-44ac-ba3c-d97979a354c1" }, "params": { "eventCreateTime": "2023-02-15T15:25:08.861Z", "name": "John", "surname": "Doe", "location": "Warsaw", "age": "23", "feedback": "Great customer serviece and product selection." } }[
{
"insertId": "{{ currentStep.actionId }}",
"json": {
"name": "{{ automationPathSteps['nps survey'].event.params.name }}",
"surname": "{{ automationPathSteps['nps survey'].event.params.surname }}",
"location": "{{ automationPathSteps['nps survey'].event.params.location }}",
"feedback": "{{ automationPathSteps['nps survey'].event.params.feedback }}"
}
}
]
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
2. Enter the name of the aggregate.
3. Click **Analyze profiles by** and select **Last**.
4. From the **Choose event** dropdown list, select the `subscription.status` event.
5. As the event parameter, select **segment_enabled**.
5. Click **+where** and choose the **segment_enabled** parameter.
9. From the **Choose operator** dropdown list, select **Equal**.
6. As the value set up `1` (it means that it is active).
6. Define the period from which the aggregate will look up event data - in this case, it is **Lifetime**.
7. Click **Save**.
**Decision Hub > Segmentations > New segmentation**.
2. Enter the name of the segmentation.
3. Click **Choose filter**.
4. From the dropdown list, select the [aggregate you created before](/use-cases/subscription#create-an-aggregate).
5. As the logical operator, select **Equal**.
6. In the text field, enter `true`.
7. Save the segmentation.
**AI Hub > Regular Promotions > Add promotion**.
2. Select the **For selected items** option.
3. In the **Audience** section:
4. Choose the [segment created previously](/use-cases/subscription#create-a-segmentation).
5. Click **Apply**.
4. In the **Content** section:
2. Add the name in the **Display name**.
2. In the **Price** field, enter `0`.
3. In the **Long description** add the names and SKU's of products which price should be reduced to zero (in this case coffees).
4. Define the name and description of the promotion.
3. Confirm the settings by clicking **Apply**.
4. In **Type & limits** section:
1. Choose the **Custom** type.
2. Choose the **Multibuy** sub-type.
4. Define the number of usages per activation as `1`.
6. Define distribution period in the **Schedule** section and publish the promotion to apply all changes and run the promotion.
7. After buying the subscription the promotion created above should be activated on the client side - **for 30 times** (because it is the promotion for 30 coffees). Check the [first](https://hub.synerise.com/api-reference/loyalty-and-engagement#operation/ActivateAPromotion) or [second](https://hub.synerise.com/api-reference/loyalty-and-engagement#operation/BatchActivate) option which help you in activation of the promotion in our documentation.
## Create a workflow that tracks redemptions
---
In this step create a workflow that generates the event which informs that user collecting his daily coffee. In this workflow, after the promotion is redeemed by customer who has subscription - `client.removePoints` event is generated. This event is the trigger of the described workflow, which removes a customer from the segment for one day (they will not be able to use this subscription two times a day).
1. Go to **Automation Hub > Workflows > New workflow**.
2. Enter the name of the workflow.
### Define the Profile Event trigger node
---
At this stage, you configure the workflow to be triggered by a `client.removePoints` event.
1. As the first node of the workflow, add **Profile Event**. In the configuration of the node:
1. From **Choose event** dropdown menu, choose `client.removePoints` event.
2. Click the + where button, from the **Choose parameter** dropdown menu, choose **promotionUuid**.
3. From the **Choose operator** dropdown, choose **Equal (String)**.
4. In the next field, type the UUID of the promotion that you created earlier.
2. Confirm by clicking **Apply**.
### Define the Generate Event node
---
At this stage, an event is generated which is then used to exclude this profile from the segmentation of customers who did not pick up a coffee on this day.
1. As the second node of the workflow, add **Generate Event**.
2. In the **Event name**, enter `subscription.status`.
4. In the **Body** section, define the parameters of this event. In this case it is: ``` {"segment_enabled": "0"} ``` This removes the customer from the segment of customers eligible for a coffee on this day.
5. Click **Apply**.
### Add the finishing node
---
9. Add the **End** node.
10. In the upper right corner, click **Save & Run**.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
2. Enter the name of the aggregate.
3. Click **Analyze profiles by** and select **Last**.
4. From the **Choose event** dropdown list, select the **Visited page** event.
5. As the event parameter, select **og:title**
6. Click the **+ where** button.
7. From the **Choose parameter** drop-down list, select the **product:retailer_part_no** parameter.
5. From the **Choose operator** dropdown list, select **String** and **Is not empty**.
6. Using the date picker in the lower-right corner, set the time range to **Custom > Last 12 hours**. Confirm your choice with the **Apply** button.
7. Click **Save**.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
2. Enter the name of the aggregate.
3. Click **Analyze profiles by** and select **Last**.
4. From the **Choose event** dropdown list, select the **Visited page** event.
5. As the event parameter, select **og:image**
6. Click the **+ where** button.
7. From the **Choose parameter** drop-down list, select the **product:retailer_part_no** parameter.
5. From the **Choose operator** dropdown list, select **String** and **Is not empty**.
6. Using the date picker in the lower-right corner, set the time range to **Custom > Last 12 hours**. Confirm your choice with the **Apply** button.
7. Click **Save**.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
2. Enter the name of the aggregate.
3. Click **Analyze profiles by** and select **Last**.
4. From the **Choose event** dropdown list, select the **Visited page** event.
5. As the event parameter, select **og:url**
6. Click the **+ where** button.
7. From the **Choose parameter** drop-down list, select the **product:retailer_part_no** parameter.
5. From the **Choose operator** dropdown list, select **String** and **Is not empty**.
6. Using the date picker in the lower-right corner, set the time range to **Custom > Last 12 hours**. Confirm your choice with the **Apply** button.
7. Click **Save**.
**Experience Hub > Web Push > Templates > Create new**.
2. Click **Drag&drop builder**.
3. Enter the name of the template.
4. In the **Title** field, define the title you want to display in the web push.
5. In the **Message** field, define the copy you want to appear in the web push. In our case it will be an insert with [aggregate returing the product title, created in the previous step](#aggregate-returning-the-title-of-the-last-visited-product). Enter the following code:
{% aggregate ae5d9077-d723-3649-8233-08fab406ec53 %}{{aggregate_result[0]}}{% endaggregate %}{% aggregate 87eba5f7-40ab-3b24-98df-ae2ac6263474 %}{{aggregate_result[0]}}{% endaggregate %}{% aggregate 71293b39-ea01-310c-b887-3cb91b6645e3 %}{{aggregate_result[0]}}{% endaggregate %}
**Automation Hub > Workflows > New workflow**.
2. Enter the name of the workflow.
### Define the trigger node
---
1. As the first node, add the **Profile Event**. In the settings of the node, select the **session.end** event.
2. Click **Apply**.
### Configure the Delay node
---
1. Add the **Delay** node. In the node settings:
1. In the **Delay** field, type `2`.
2. From the **Unit** dropdown list, choose **Hour**.
2. Click **Apply**.
### Configure the Send Web Push node
---
1. Add the **Send Web Push** node. In the node settings:
1. In the **Content** section, from the **Webpush template** dropdown, select [the template you created in the previous step](#create-a-web-push-template).
2. In the **Schedule** section, set the **Webpush lifespan (TTL)** according to your business needs.
3. You can describe campaigns with [additional parameters](/docs/campaign/Webpush/creating-webpush-campaigns#adding-custom-parameters).
2. Click **Apply**.
### Add the finishing node
---
1. Add the **End** node to the **Send Web Push** node.
2. In the upper right corner, click **Save & Run**.
## Prerequisites
---
- Implement [Synerise tracking code](/developers/web/installation-and-configuration) on your website.
- Implement [OG Tags](/developers/web/og-tags) on your website.
- [Prepare a product feed](/docs/ai-hub/recommendations-v2/item-feed-requirements) with attributes to be used in item comparison recommendations.
- [Configure an item catalog for recommendations](/docs/settings/configuration/ai-engine-configuration/engine-configuration-for-recommendations). Enable the item comparison recommendations.
- Meet the minimum data requirements of interactions and events.
At least 10,000 item page visits for **Item comparison recommendations**.
## 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 **Item comparison**.
3. Click **Apply**.
4. In the **Compare attributes** section, click **Define**.
5. Click **Choose**.
6. Select the item attributes from the list of all available attributes to be compared in the recommendations.
6. Click **Apply**.
7. In the **Items** section, click **Define**.
1. Click **Add slot**. You can name the slot for later reference.
2. In the **Number of items** subsection, set the minimum and maximum number of items to `3`.
**AI Hub > (AI Predictions) Models > New prediction**.
2. Enter a meaningful name for the prediction.
2. In the **Select prediction type** window that appears, click **Lookalikes**.
3. Click **Apply**.
### Create a source segmentation
A source segmentation is a group of model customers to whom you compare the target group of customers in order to find similar customers in the target group. In this scenario, customers who made a purchase during past marketing campaign will be the source segmentation.
1. In the **Audience** section, click **Define**.
2. In the **Source segmentation** sub-section, click **Choose segmentation**.
3. On the dropdown list, click **Create new**.
4. In the **Segmentation name** field, enter a meaningful name of the segmentation.
5. Click **Netx step**.
5. Click **Choose filter**:
1. From the dropdown list, select the [`push.view`](/docs/assets/events/event-reference/mobile-push#pushview) event.
2. Click the **+ and where** button and select `id`.
3. As the logical operator, select **Equal**.
4. Type the campaign ID.
6. Click **+ Add funnel step**.
7. Click **Choose filter**:
1. From the dropdown list, select the [`transaction.charge`](/docs/assets/events/event-reference/items#transactioncharge) event.
8. In the lower-right corner, click the clock icon.
**Result**: **Completed within** section will appear.
9. Type `2` and from the dropdown list, select **Days**.
9. Using the date picker in the lower-right corner, select the **Lifetime** value.
6. Save the segmentation by clicking **Create segmentation**.
