**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Last 30 days purchased product SKUs`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **30**.
5. From the **Choose event** dropdown list, select the **Bought product** event.
6. As the event parameter, select **$sku**.
7. Click the **+ where** button:
- From the **Choose parameter** dropdown list, select the **$sku** parameter.
- From the **Choose operator** dropdown list, select **Is not empty**.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Last price drop event data`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **100 000**.
5. From the **Choose event** dropdown list, select the **results.priceDrop** event.
6. As the event parameter, select **eventdata**.
7. Click the **+ where** button:
- From the **Choose parameter** dropdown list, select the **eventdata** parameter.
- From the **Choose operator** dropdown list, select **Is not empty**.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Remove from cart all`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **100**.
5. From the **Choose event** dropdown list, select the `product.removeFromCart` event.
6. As the event parameter, select **$sku**.
7. Define the period to the last **30 days**.
8. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Favorite products with lower price - SKUs`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the **product.addToFavorite** event.
6. As the event parameter, select **$sku**.
7. Click the **+ where** button and add the following conditions:
- `$sku` **Is not empty** — ensures the SKU parameter exists.
- `finalUnitPrice` **Is not empty** — ensures the price parameter exists.
- `$sku` **Not in array** → select the aggregate **Last 30 days purchased product SKUs**. This excludes products that the customer has already bought.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Favorite products with lower price - prices`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the **product.addToFavorite** event.
6. As the event parameter, select **finalUnitPrice**.
7. Click the **+ where** button and add the same conditions as in the SKU aggregate:
- `$sku` **Is not empty**.
- `finalUnitPrice` **Is not empty**.
- `$sku` **Not in array** → select the aggregate **Last 30 days purchased product SKUs**.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Cart products with lower price - SKUs`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the **product.addToCart** event.
6. As the event parameter, select **$sku**.
7. Click the **+ where** button and add the following conditions:
- `$sku` **Is not empty** — ensures the SKU value exists.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Cart products with lower price - prices`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the **product.addToCart** event.
6. As the event parameter, select **$finalUnitPrice**.
7. Click the **+ where** button and add the following conditions:
- `$finalUnitPrice` **Is not empty** — ensures the price value exists.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Mobile app viewed products - SKUs`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the **product.view** event.
6. As the event parameter, select **sku**.
7. Click the **+ where** button and add the following conditions:
- `sku` **Is not empty** — ensures the SKU parameter exists.
- `sku` **Not in array** → select the aggregate **Last 30 days purchased product SKUs**. This excludes products the customer has already bought.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Mobile app viewed products - prices`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the **product.view** event.
6. As the event parameter, select **finalUnitPrice**.
7. Click the **+ where** button and add the following conditions:
- `sku` **Is not empty**.
- `sku` **Not in array** → select the aggregate **Last 30 days purchased product SKUs**.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Desktop website viewed products - SKUs`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the `page.visit` event.
6. As the event parameter, select **product:retailer_part_no**.
7. Click the **+ where** button and add the following conditions:
- `product:retailer_part_no` **Is not empty** — ensures the product ID exists.
- `product:retailer_part_no` **Not in array** → select the aggregate **Last 30 days purchased product SKUs**. This excludes products the customer has already bought.
- `product:price:amount` **Is not empty** — ensures the price parameter exists.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Behavioral Data Hub > Live Aggregates > Create aggregate**.
2. As the aggregate type, select **Profile**.
3. Enter the name of the aggregate, for example `Desktop website viewed products - prices`.
4. Click **Analyze profiles by** and select **Last Multi** and size: **1000**.
5. From the **Choose event** dropdown list, select the `page.visit` event.
6. As the event parameter, select **product:price:amount**.
7. Click the **+ where** button and add the following conditions:
- `product:retailer_part_no` **Is not empty**.
- `product:retailer_part_no` **Not in array** → select the aggregate **Last 30 days purchased product SKUs**.
- `product:price:amount` **Is not empty**.
8. Define the period to the last **30 days**.
9. Save the aggregate.
**Data Modeling Hub > Snippets > Add snippet**.
2. Enter the name of the snippet, for example `Price drop detection logic`.
3. Paste the following Jinjava code:
{%- set final_objects_for_alert=[] -%}
{%- set added_objects=[] -%}
{%- set last_add_fav_skus=[] -%}
{%- set last_add_fav_prices=[] -%}
{%- aggregate 1227553d-114a-3c19-b618-6c3afc9d7a32 -%}
{%- for items in aggregate_result -%}
{%- do last_add_fav_skus.append(items) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- aggregate 1227553d-114a-3c19-b618-6c3afc9d7a32 -%}
{%- for price in aggregate_result -%}
{%- do last_add_fav_prices.append(price) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- for added in last_add_fav_skus -%}
{%- do added_objects.append({'sku': added, 'price': last_add_fav_prices[loop.index0]}) -%}
{%- endfor -%}
{%- set final_price_alert_fav_skus=[] -%}
{%- for item in added_objects -%}
{%- catalogitemv2.(item.sku) allowEmpty=True -%}
{%- set object = catalog_result -%}
{%- if object.availability == 'true' -%}
{%- set _catalog_price = catalog_result.get('effectivePrice') -%}
{%- set catalog_price = _catalog_price | float -%}
{%- set item_price = item.price|float -%}
{%- set is_discounted = item_price > catalog_price -%}
{%- if is_discounted -%}
{%- do final_price_alert_fav_skus.append(item) -%}
{%- endif -%}
{%- endif -%}
{%- endcatalogitemv2 -%}
{%- endfor -%}
{%- set added_objects=[] -%}
{%- set last_add_fav_skus=[] -%}
{%- set last_add_fav_prices=[] -%}
{%- aggregate 34f469d8-f83d-32e5-b0e1-10f73b0a0179 -%}
{%- for items in aggregate_result -%}
{%- do last_add_fav_skus.append(items) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- aggregate 4148b6aa-4488-39d1-81b8-a29ed5b23424 -%}
{%- for price in aggregate_result -%}
{%- do last_add_fav_prices.append(price) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- for added in last_add_fav_skus -%}
{%- do added_objects.append({'sku': added, 'price': last_add_fav_prices[loop.index0]}) -%}
{%- endfor -%}
{%- set final_price_alert_cart_skus=[] -%}
{%- for item in added_objects -%}
{%- catalogitemv2.(item.sku) allowEmpty=True -%}
{%- set object = catalog_result -%}
{%- if object.availability == 'true' -%}
{%- set _catalog_price = catalog_result.get('effectivePrice') -%}
{%- set catalog_price = _catalog_price | float -%}
{%- set item_price = item.price|float -%}
{%- set is_discounted = item_price > catalog_price -%}
{%- if is_discounted -%}
{%- do final_price_alert_cart_skus.append(item) -%}
{%- endif -%}
{%- endif -%}
{%- endcatalogitemv2 -%}
{%- endfor -%}
{%- set added_objects=[] -%}
{%- set last_add_fav_skus=[] -%}
{%- set last_add_fav_prices=[] -%}
{%- aggregate 51d1daac-8483-351f-ae01-ea0b5455fba0 -%}
{%- for items in aggregate_result -%}
{%- do last_add_fav_skus.append(items) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- aggregate 51d1daac-8483-351f-ae01-ea0b5455fba0 -%}
{%- for price in aggregate_result -%}
{%- do last_add_fav_prices.append(price) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- for added in last_add_fav_skus -%}
{%- do added_objects.append({'sku': added, 'price': last_add_fav_prices[loop.index0]}) -%}
{%- endfor -%}
{%- set final_price_alert_desktop_skus=[] -%}
{%- for item in added_objects -%}
{%- catalogitemv2.(item.sku) allowEmpty=True -%}
{%- set object = catalog_result -%}
{%- if object.availability == 'true' -%}
{%- set _catalog_price = catalog_result.get('effectivePrice') -%}
{%- set catalog_price = _catalog_price | float -%}
{%- set item_price = item.price|float -%}
{%- set is_discounted = item_price > catalog_price -%}
{%- if is_discounted -%}
{%- do final_price_alert_desktop_skus.append(item) -%}
{%- endif -%}
{%- endif -%}
{%- endcatalogitemv2 -%}
{%- endfor -%}
{%- set added_objects=[] -%}
{%- set last_add_fav_skus=[] -%}
{%- set last_add_fav_prices=[] -%}
{%- aggregate adb929ff-f56c-37d6-b5d8-61d88449d2e1 -%}
{%- for items in aggregate_result -%}
{%- do last_add_fav_skus.append(items) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- aggregate adb929ff-f56c-37d6-b5d8-61d88449d2e1 -%}
{%- for price in aggregate_result -%}
{%- do last_add_fav_prices.append(price) -%}
{%- endfor -%}
{%- endaggregate -%}
{%- for added in last_add_fav_skus -%}
{%- do added_objects.append({'sku': added, 'price': last_add_fav_prices[loop.index0]}) -%}
{%- endfor -%}
{%- set final_price_alert_mobile_skus=[] -%}
{%- for item in added_objects -%}
{%- catalogitemv2.(item.sku) allowEmpty=True -%}
{%- set object = catalog_result -%}
{%- if object.availability == 'true' -%}
{%- set _catalog_price = catalog_result.get('effectivePrice') -%}
{%- set catalog_price = _catalog_price | float -%}
{%- set item_price = item.price|float -%}
{%- set is_discounted = item_price > catalog_price -%}
{%- if is_discounted -%}
{%- do final_price_alert_mobile_skus.append(item) -%}
{%- endif -%}
{%- endif -%}
{%- endcatalogitemv2 -%}
{%- endfor -%}
{%- set seen = [] -%}
{%- set excluded = [] -%}
{%- aggregate b5fc6392-65f1-32d3-9ed1-a41f209ea4c5 -%}
{%- for result in aggregate_result -%}
{%- set raw = result|string -%}
{%- set split1 = raw|split('excluded=[') -%}
{%- if split1|length > 1 -%}
{%- set inside = split1[1]|split(']') -%}
{%- for item in inside[0]|split(', ') -%}
{%- set trimmed = item|trim -%}
{%- if trimmed != '' and (trimmed in excluded == false) -%}
{%- do excluded.append(trimmed) -%}
{%- endif -%}
{%- endfor -%}
{%- endif -%}
{%- endfor -%}
{%- endaggregate -%}
{%- set filtered_cart = [] -%}
{%- for item in final_price_alert_cart_skus -%}
{%- if item.sku != '' and (item.sku in excluded == false) and (item.sku in seen == false) -%}
{%- do filtered_cart.append(item.sku) -%}
{%- do seen.append(item.sku) -%}
{%- endif -%}
{%- endfor -%}
{%- set filtered_fav = [] -%}
{%- for item in final_price_alert_fav_skus -%}
{%- if item.sku != '' and (item.sku in excluded == false) and (item.sku in seen == false) -%}
{%- do filtered_fav.append(item.sku) -%}
{%- do seen.append(item.sku) -%}
{%- endif -%}
{%- endfor -%}
{%- set filtered_viewMobile = [] -%}
{%- for item in final_price_alert_mobile_skus -%}
{%- if item.sku != '' and (item.sku in excluded == false) and (item.sku in seen == false) -%}
{%- do filtered_viewMobile.append(item.sku) -%}
{%- do seen.append(item.sku) -%}
{%- endif -%}
{%- endfor -%}
{%- set filtered_viewWeb = [] -%}
{%- for item in final_price_alert_desktop_skus -%}
{%- if item.sku != '' and (item.sku in excluded == false) and (item.sku in seen == false) -%}
{%- do filtered_viewWeb.append(item.sku) -%}
{%- do seen.append(item.sku) -%}
{%- endif -%}
{%- endfor -%}
{%- set new_excluded = [] -%}
{%- if filtered_cart|length > 0 -%}
{%- set new_excluded = filtered_cart -%}
{%- elif filtered_fav|length > 0 -%}
{%- set new_excluded = filtered_fav -%}
{%- elif filtered_viewMobile|length > 0 -%}
{%- set new_excluded = filtered_viewMobile -%}
{%- elif filtered_viewWeb|length > 0 -%}
{%- set new_excluded = filtered_viewWeb -%}
{%- endif -%}
{%- set finalObj = {'emailCartSku': filtered_cart,'emailCartCount': filtered_cart|length,'emailFavSku': filtered_fav,'emailFavCount': filtered_fav|length,'emailViewMobileSku': filtered_viewMobile,'emailViewMobileCount': filtered_viewMobile|length,'emailViewWebSku': filtered_viewWeb,'emailViewWebCount': filtered_viewWeb|length,'excluded': new_excluded} -%}{{ finalObj }}
**Automation Hub > Workflows > New workflow**.
2. Enter the name of the workflow.
### Define the Audience trigger node
---
{
"eventdata": "{% snippet %} SNIPPET_HASH {% endsnippet %}",
"newsletterAgreement": "{{ customer.newsletter_agreement }}",
}
**Automation Hub > Workflows > New workflow**.
2. Enter the name of the workflow.
### Configure the Profile Event trigger for cart path (Priority 1)
---
1. As the first trigger path, add a **Profile Event** node and name it `prio 1: CART`. In the configuration of the node:
1. Enable **Action limit** and set it to **1 time per Workflow**.
2. From the **Choose event** dropdown menu, choose the `results.priceDrop` event.
3. Click the **+ where** button and add the following conditions:
- `newsletterAgreement` **Equal** `enabled`
- `eventdata` **Contain** `emailCartCount=`
- `eventdata` **Not contain** `emailCartCount=0`
4. Confirm by clicking **Apply**.
