This section defines the filters which are often used as basic or advanced filter options in audience group filters.
The following are the types of common filter options.
Duration
This filter lets you build an audience group with conditions based on dates, days, and period range. The duration filter is further classified into specific dates and relative days.
Assume that you want to get customers who made payment through Credit Card for the amount greater than or equal to $500 in a specific period.
The following are some points to remember before using duration filter options.
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Specific Dates
This filter lets you get customers who have done activities before, after, and between dates (select manually from the list).
The following table provides an example of how the specific dates are evaluated for each option.
Specific Dates | Value | Dates Considered |
Before | before 01-10-2020 | In this scenario, you get customers who have done activities before 01-10-2020 then the before filter will start fetching data from October 01, 00:00 hours till the first activity date of customers. |
After | after 01-10-2020 | In this scenario, you can get customers who have done activities after 01-10-2020 then the after filter will start fetching data from October 01, 00:00 hours up to the last activity date of customers. |
Between | between 01-10-2020 to 09-10-2020 | In this scenario you can get customers who have done activities between 01-10-2020 to 09-10-2020 then the between filter will start fetching data from October 01, 00:00 hours to October, 09, 23:59 hours. |
Relative Days
This filter lets you get customers who have done activities in the last x days, next x days, current day, calendar weeks, or calendar months, and more.
The following table provides an example of how the relative days are evaluated for each option.
Relative days | Value | Days Considered |
In the last x | last 1 day last 2 days | In this scenario, if October 7 is the current date then the last 1 day filter will fetch data from October 6, 00:00 hours to 23:59 hours, excluding the current date’s (October 7) data. |
In this scenario, if October 7 is the current date then the last 2 days filter will fetch data from October 5, 00:00 hours to October 6, 23:59 hours, excluding the current date’s (October 7) data. | ||
last 1 week last 2 weeks | In this scenario, if October 7 is the current date then the last one week filter will fetch data from September 28, 00:00 hours to October 4, 23:59 hours. | |
In this scenario, if October 7 is the current date then the last 2 weeks filter will fetch data from September 21, 00:00 hours to October 4, 23:59 hours. | ||
last 1 month last 2 months | In this scenario, if October 7 is the current date then the last 1 month filter will fetch data from September 1, 00:00 hours to September 30, 23:59 hours. | |
In this scenario, if October 7 is the current date then the last 2 months filter will fetch data from August 1, 00:00 hours to September 30, 23:59 hours. | ||
In the next x | Next 1 day Next 2 days | In this scenario, if October 7 is the current date then the next 1 day filter will fetch data from October 8, 00:00 hours to 23:59 hours, excluding the current date’s (October 7) data. |
In this scenario, if October 7 is the current date then the next 2 days filter will fetch data from October 8, 00:00 hours to October 9, 23:59 hours. excluding the current date’s (October 7) data. | ||
Next 1 week Next 2 weeks | In this scenario, if October 7 is the current date then the next 1 week filter will fetch data from October 12, 00:00 hours to October 18, 23:59 hours. | |
In this scenario, if October 7 is the current date then the next 2 weeks filter will fetch data from October 12, 00:00 hours to October 25, 23:59 hours. | ||
Next 1 month Next 2 months | In this scenario, if October 7 is the current date then the next 1 month filter will fetch data from November 1, 00:00 hours to November 30, 23:59 hours. | |
In this scenario, if October 7 is the current date then the next 2 months filter will fetch data from November 1, 00:00 hours to December 31, 23:59 hours. | ||
In current x | Current day | This filter will not get you the current day's data. Therefore, recommended not to use this filter. |
Current week | In this scenario, if October 7 is the current date then the current week filter will fetch data from October 5, 00:00 hours to October 11, 23:59 hours. | |
Current month | In this scenario, if October 7 is the current date then the current month filter will fetch data from October 1, 00:00 hours to October 31, 23:59 hours. | |
Between days | Between the last 20 to the next 30 days | In this scenario, if October 7 is the current date then between the last 20 to the next 30 days the filter will fetch data from September 17, 00:00 hours to November 6, 23:59 hours, excluding the current date’s (October 7) data. |
Between the last 30 to last 20 days Note: 'From' value must be greater than the 'To' value. | In this scenario, if October 7 is the current date then between the last 30 to last 20 days the filter will fetch data from September 7, 00:00 hours to September 17, 23:59 hours, excluding the current date’s (October 7) data. | |
Between the next 20 to next 30 days | In this scenario, if October 7 is the current date then between the next 20 to the next 30 days the filter will fetch data from October 27, 00:00 hours to November 6, 23:59 hours, excluding the current date’s (October 7) data. | |
Exactly x days ago | Exactly 20 days ago | In this scenario, if October 7 is the current date then the exactly 20 days ago filter will fetch data from September 17, 00:00 hours to 23:59 hours, excluding the current date’s (October 7) data. |
Exactly after x days | Exactly after 20 days | In this scenario, if October 7 is the current date then the exactly after 20 days filter will fetch data from October 27, 00:00 hours to 23:59 hours, excluding current date’s (October 7) data. |
Store Hierarchy
This option lets you filter customers by store(s) at which the transaction is made. You can also select stores by zones and concepts.
Store
You can filter customers by store(s) at which they made transactions.
You can select stores using any of the following options.
- upload list: Lets you upload store IDs using a CSV file. Select the upload list from the drop-down list. If you do not have the CSV file, then download the sample CSV file, add store IDs, and upload it.
- enter values: Lets you search for stores manually. On the search box, enter a store name, and select the store name from the suggested list. You can add more than one store.
- based on attributes: Lets you select store(s) based on attributes. You can select stores by attributes - store name, type, and store external ID, area, and more. After selecting a store attribute, select the values of each attribute from the suggested list. For example, to filter stores by city, select the store city from the attributes list, and in the store city list, select your preferred city's name.
Zone
You can filter customers by store(s) in your preferred zone(s) at which they made transactions.
You can select stores of the selected zone(s) using any of the following options.
- any store: Selects all stores of a specific zone.
- stores with these attributes: Lets you select stores of your preferred zone(s) by store attributes such as store channel, store type, external ID, store name, store area, and more. After selecting a store attribute, select the values of each attribute from the suggested list. For example, to filter stores of a zone by city, select the store city from the attributes list, and in the store city list, select your preferred city's name.
Concept
You can filter customers by store(s) in your preferred concept(s) at which they made transactions.
You can select stores of the selected concept(s) using the following options.
- any store: Selects all stores of a specific concept.
- stores with these attributes: Lets you select stores (of the selected concept(s)) with your preferred store attributes such as store channel, store type, external ID, store area, store name, and more. After selecting a store attribute, select the values of each attribute from the suggested list. For example, to filter stores of a concept by city, select the store city from the attributes list, and in the store city list, select your preferred city's name.
Product
This option enables you to filter customers who purchase product(s) with the specific attribute(s).
Product Category
This option enables you to filter only those customers who purchased a specific product. You can filter the results further using either any product or products with these attributes. To get customers who purchased by the category of the product, select the product category from the drop-down list.
You can select the product category using any of the following options.
any product: Selects all products of the selected product category(s).
products with these attributes: Lets you select product(s) with your preferred product categories - brand name, image URL, price, style, and more. In a product category, you can further select the values of each product category from the suggested list. For example, to filter a product using a product attribute, brand name, select the brand name from the attributes list and select the brand name value based on the selected brand name.
Product Sub Category
This option enables to filter only those customers who purchased the product(s) from a specific sub-category and select sub-category from the drop-down list.
You can select the sub-category using any of the following options.
- any product: Selects all products of the selected product sub-category.
- products with these attributes: Lets you select product(s) with your sub-category choice - brand name, image URL, price, style, and more. In a product sub-category, you can further select each product attribute’s values from the suggested list. For example, to filter a product using product attributes, select the color from the attributes list, and select the type of color based on the selected product color.
Product Item Code
This option enables you to filter only those customers who purchased product(s) with a specific item code.
You can select an item code using any of the following options.
- upload list: Lets you upload store ID using a CSV file. Select the upload list from the drop-down list. If you do not have the CSV file, then download the sample CSV file, add store IDs, and upload it.
- enter values: Lets you search for stores manually. On the search box, enter the product name and select the item code from the suggested list. You can add more than one store.
- based on attributes: Lets you select item code(s) based on attributes. You can select item code by attributes - brand name, image URL, price, style, and more. You can further select the values of each store attribute from the suggested list. For example, to filter a product using item code attributes, select the color from the attributes list, and select the type of color based on the selected item code color.