- Examples of segmenting by built-in dates
- Segmenting by a custom date
- Date Options Explained
Segmenting contacts by date means you can send your time-sensitive campaigns with more precision ( Broadcast and Automation Campaigns) and you can perform more accurate marketing analyses (performed through any of Segment Explorer, Products Report, Cohort Report, Orders Report, Campaign Performance dashboards).
Ometria allows you to create very specific contact groups based on the date of an event. For example, with the built-in date: Date of first order → you can create a segment of all contacts who made their first purchase last year.
Below are examples showing some cool things you can analyse with date-based contact segmentation.
Examples of segmenting by built-in dates
When do contacts unsubscribe the most?
If you send a timely newsletter to your audience, you can find out if there are specific days of the week that people are unsubscribing in high numbers. Then use the insight to make changes to your campaign calendar.
In the Segment Explorer dashboard select Filter Customers. In the pop up that opens,
Fig 1: Segment Contacts that unsubscribe on Mondays
- Segment contacts by Date unsubscribed. Select Add Condition> Customer Attributes> Date unsubscribed
- Select ‘day of week is’ in the drop-down list
- Select a day from the drop-down to check unsubscribes.
- Apply filter and note the number of Contacts in the dashboard. Repeat with another day.
Who, or what groups of people, placed orders in a specific year?
You might want to explore the segment of customers who first placed orders in 2017 and analyse differences between current customers and year-old customers.
This can be done from the Orders Report>Filter Customers.
Fig 2: Segment contacts that laced orders last year
- Add Purchase Activity> Date of First Order as the condition.
- If you select ‘year is’ from the drop-down, you can type in the year in the field next to it. In this case, 2017 and Apply Filter. Ometria will filter the orders in the Orders Report for the segment of contacts who placed orders in 2017.
This is a straightforward way to apply a customer-filter over an entire year without manually specifying start and end dates.
What days of the year are customers shopping the most?
You may want to find out which days of the month do sales spike up. Black Fridays and Christmas are prime shopping periods of the year. But surely there are specific days in every month when orders peak.
Go to Segment Explorer>Filter Customers.
Fig 3: Segment contacts that placed orders last year
Select Customer Attribute> Date of First Order. Then choose 'Day of month' is. Enter any day of the month. The day that has the maximum orders can be used when structuring your campaign calendar.
How many contacts are being acquired over time?
Depending on your marketing analytics needs, you might want to track how many contacts are being created in Ometria over time and identify trends in contact acquisition. To do that, you can segment contacts by a specific date range in which the contact records were created in Ometria.
Go to Segment Explorer> Filter Customers.
Fig 4: Segment contacts by the date they were created in Ometria
Select Customer Attribute> Date created in Ometria.
Fig 5: There are many time-dependent options available, including between to enter a date range.
In the time-dependent options available, select 'between' and pick your start and end dates. Apply filter to analyse the segment.
Note: Contacts in Ometria are created from a variety of sources, e.g. Shopify/Magento/Custom store data, Data APIs, CSV uploads, forms, third-party email click-throughs, etc.
Segmenting by a custom date
You can create contact groups/segments based on custom dates too, e.g. relationship anniversary, child’s birthday etc.
[ Note: If you are already collecting (or would like to collect) additional date information for your contacts and want to trigger using these dates - for example “relationship anniversary”, “child’s birthday”, (or any other date you want to assign) - please contact email@example.com, so we can help you set up your custom fields.]
The ability to filter contacts or existing segments by custom dates means that you can bump up your analytics capabilities by several notches.
All you have to do is select the custom date field from the filtering pop-up. Add Condition>Customer Attributes> (custom date field).
Fig 6: Segment contacts that laced orders last year
There is a wide range of options available to filter around a date. See below. You have full flexibility to group customers by date in whichever way you want.
Date Options Explained
Fig 7: Different options to segment around a date
Following is an explanation of each of the date options that appear when filtering on a date event.
The 'date event selected', mentioned frequently in this section, refers to the date event you have selected to filter on, for example, Date first ordered, Date Subscribed, or Date last opened an email, etc.
The date entered is the date you enter in the blank date fields.
Before: The date event selected was before the date entered.
E.g. Date of first order before 21 December 2018:
- means all contacts who first ordered before the 21rst of December 2018, will enter the segment or be filtered in.
After: The date selected was after the date entered.
E.g. Date of first order after 21 December 2018:
- means all contacts who placed their first order after 21/12/18 will be filtered in the segment.
On: The date selected is on the date entered.
E.g. Date of first order on 21 December 2018: means all contacts who placed their first order on the 21rst December 2018, will be filtered in the segment.
A good use for this could be if you further filter on lifecycle stage. So you can find out how many leads were won back on, e.g., Christmas day, Valentine's day or any date you entered, and whether your win-back campaigns were effective.
Between: The date selected was between two entered dates.
E.g. Date of last order between 'y' and 'x':
- means that all contacts whose last order was placed between x and y will enter the segment or be filtered in. Note: the older date should be entered first followed by the later date in the second box.
Before (relative): The date selected was before the date that was 'x' hours/days/weeks ago. (The term relative just means the time is being considered relative to now.)
E.g. Date Last ordered before (relative) 14 days ago
- means all contacts who last ordered before the day that was 14 days ago from now, are filtered in the segment.
This filter marks the reference date as 14 days before today. And then looks back from that date to filter all contacts that last ordered before that date.
After (relative): The date selected was after the date that was 'x' hours/days/weeks ago from now.
E.g. Date Last ordered after (relative) 14 days ago -
- means all contacts who last ordered after the day that was 14 days ago, are filtered in.
Today this filter would include all contacts whose last order was between today and 14 days ago. Tomorrow, it would also include contacts whose last order was between tomorrow and 14 days before tomorrow (or 13 days from today). Relative filters dynamically look back from the current time.
Note that this is not similar to the between option, as that filters between two fixed dates and does not dynamically look back from the current time or now.
E.g. Suppose you are sending a triggered abandoned browse or abandoned basket campaign but you want to exclude customers who had purchased recently from receiving these emails.
Your exclusion segment would look something like:
On (relative): The date selected was on the date that was 'x' hour/days/weeks ago from now.
E.g. the Date Last Ordered was on(relative) 14 days ago -
- means all contacts who last ordered on the day that was 14 days ago from today are filtered in.
Between (relative): The date selected was between 'x' days ago from now and 'y' days ago from now.
E.g the Date Last Orderd was between 28 days and 14 days ago
- means all contacts who ordered between 28 days ago and 14 days ago from now, are filtered in. This filter won't include any contacts who made their last order in the last 14 days or any contacts who made their last order before 28 days ago.
Note that the older date should be entered first and the more recent date should be entered next. So Y should be > X. If you enter the other way round it would not be able to save.
Day of month is: The date selected occurred on the nth day of every month
E.g. Date of First Order - day of month is 23 of the month:
- means that all contacts who first purchased on the 23rd of any month will be filtered in. This could be used to analyse purchase trends on paydays and whether or not to send campaigns before that.
Day of week is: The date event selected occurred in a particular day of the week.
E.g. Date of Last Order/First Order > day of week is Wednesday:
- means all contacts who placed their last order on Wednesdays (any Wednesday) will be filtered in.
This could be very useful in identifying in which day of the week are people most likely to purchase.
Month is: The date event selected occurred in a particular month in the year.
E.g. Date Subscribed month is January:
- means all contacts who have subscribed in January (any Januarys in the past years) will be filtered in.
This could be useful in identifying the ideal months to acquire leads and start engaging them.
Year is: The date event selected occurred in a specific year.
Anniversary is today: The date event selected was a year ago from today.
E.g. Date subscribed Anniversary is today: means all contacts who subscribed a year ago from today can be filtered in.
This could be used to segment while sending a broadcast campaign rewarding them for a year of subscription and offering them an incentive for retention.
Anniversary was: The anniversary of the event selected was 'x' days ago
Which is known: The date event selected is known by Ometria
Which is not known: The date event selected is not known by Ometria