Audiences allow you to define cohorts of customers based on their event behaviour and traits that Intilery then keeps up to date over time. Audiences can be built from your core tracking events, traits, or computed traits. These audiences can then be used to target and personalise marketing campaigns.
Building a dynamic audience
When building an audience you can use existing events, traits, or computed traits.
You can build an audience from any of the events that are sent to Intilery. This includes any track, page, or screen calls. You can use select fields of the event to refine the audience on specific event properties as well. Select either required, Not Required or Optional to indicate customers that have, have not or have optionally performed an event. For example, you might want to look at all customers that have viewed a product above a certain price point, but not completed the order.
You can also specify time-windows:
- In range (quick) - simple timescales, e.g., today, yesterday, in the last 24 hours
- In range (relative) - from and to a certain amount of days, weeks, months, years e.g. from 180 days ago to 30 days ago
- In rage (absolute) - from and to a specific date and time e.g., from 02/08/21 at 10:30am to 20/09/2021 at 10:30am
- is before and is after - is before or after a specific date and time.
A common use case is to look at all customers that were active 30 to 90 days ago but have not completed an action in the last 30 days.
You can also build audiences based on custom traits. These traits can be collected from your apps when a customer completes a form, or signs up, using an identify call. You can also check out the Customer Activity Viewer to see examples of these traits.
You can also use computed traits in an audience definition. For example, if you have created a total_revenue computed trait, you can use this to generate an audience of big_spender customers that exceed a certain threshold.
Excluding people in a dynamic audience
When using exclude rules, it’s important to understand what you are telling the system to exclude on.
E.g., I have a Customer Trait called ‘Reward Scheme’. This reward scheme has bands bronze, silver and gold. I am planning to introduce a platinum level in the future, so I want an audience that excludes bronze and silver customers.
To make sure you exclude these customers, you need to use 2 different Exclude criteria, as below:
Exclude Customer (as their reward band is a trait of the customer) when Reward Scheme is bronze
Exclude Customer when Reward Scheme is Silver
Note that if you try to exclude where Customer Reward Scheme is bronze and when Reward Scheme is silver, this makes no sense to the computer as Rewards Scheme can’t be both bronze and silver at the same time. This is why you need to use 2 different Exclude criteria.