To get a better understanding of the users on a list — who they are and how they engage with your messages — use Audience Insights. Audience Insights displays actionable behavioral and demographic audience data from lists you’re already using, so you can gain deeper understanding of distinct user groups and learn how they’re interacting with your brand.
For example, Audience Insights can help you understand where the users on a given list are located, the locales they prefer, and the mobile devices and email domains they use. Additionally, it can tell you whether those users are doing things such as making purchase or unsubscribing. With this information, you can make more fully informed decisions about which lists to use with which campaigns.
You can also add custom insights for any conversion event and user profile field to your Audience Insights panel, so you can gain specific information about the selected users that is relevant to your business.
In this article
- Viewing Audience Insights
- Available insights for a list
- Custom insights
- Using insights to improve customer engagement
Viewing Audience Insights
Audience Insights is available for all of your lists, but it provides the best data for lists of users that have received and engaged with campaigns.
Iterable can only generate demographic data for users whose
profiles contain the user profile field(s) for that insight. For example, the
Brand Affinity™️ data requires
brandAffinityLabel on the user's profile.
To see insights for a list:
Navigate to Audience > Lists.
Select a list and click Refresh results if the list is static.
Click View insights.
Available insights for a list
For the selected list, Audience Insights displays behavioral and demographic data, as well as a list of places the list is being used in Iterable (campaigns, journeys, and other list definitions).
Fields with fewer than five results won't show any data.
To see how a list is performing, and how its performance varies for different date ranges, use the Behavioral section of Audience Insights. Behavioral metrics are generated from conversion events stored on user profiles. Currently, these metrics include total and unique purchases, revenue, average order value, conversion rate, and unsubscribe rate.
In addition to the standard insights listed below, you can also add custom behavioral insights based on conversion events that exist in this project.
Here's the behavioral data displayed by Audience Insights, and how it's calculated:
|Insight name||What it means||How it's calculated|
|Total purchases||How many total purchases the users in this list made.||Total purchases per user.|
|Unique purchases||How many unique purchasers in this list.||Total unique purchasers.|
|Revenue||The total amount spent by users.||Total spend.|
|Average order value||The average amount spent on one order, in dollars.||(Revenue) / (Total purchases)|
|Conversion rate||The percent of users in the list that have a conversion or purchase event for any campaign.||(Total purchase events + Total conversion events) / (Number of users to whom each campaign is sent)|
|Unsubscribe rate||The percent of users in this list who unsubscribed from marketing messaging.||(Total unsubscribed) / (Total sent)|
If a user converts multiple times on the same campaign, it counts as one conversion in the conversion rate. However, if a user converts on multiple campaigns, a conversion is counted for each.
For example, consider a scenario where you've selected a list of 1,000 users to whom you've sent three campaigns—two email campaigns and one SMS campaign. Iterable counts 3,000 total sends, because each list of 1,000 users received three campaigns. Each user counts as an individual send for a campaign, even if the selected lists contain all the same users.
Let's say the two email campaigns are configured to track
purchase events, and
the SMS campaign is tracking a custom
app_download event. If 250 users make a
purchase from the first email campaign, 300 make a purchase from the second
email campaign, and 50 of the SMS users download your app, the conversion rate
for those users is calculated as 20% (250 + 300 + 50 / 1,000 + 1,000 + 1,000).
View highest converting campaigns
To see the five campaigns with the highest conversion rates for this list of users, check out the Highest converting campaigns area.
To change the date range for the listed campaigns, use the All Time dropdown. The list updates to show the campaigns with the highest conversions per delivery during that time frame.
You can use this engagement data to fine-tune future messages, which can result in higher engagement and more conversions for these users. For example, you might find that the users in this list engage more with campaigns promoting weekly sales than with newsletters, and then adjust your newsletter to include a promotional offer.
- If two campaigns have the exact same conversion rate (to two decimal places), Iterable shows the campaign that was created more recently.
- The conversion rates in Highest converting campaigns are determined by the same calculation as the Conversion rate metric in the behavioral area.
Filter the highest converting campaign results
To find campaigns that resulted in the most conversions for the selected conversion event type, pick a conversion event from the All conversions dropdown in the Highest converting campaigns section.
For example, you could select Email opens to see the five email campaigns with the highest total opens for users in this list. Then, evaluate these campaigns to determine what influenced the favorable response, and use this information to to help craft future campaigns that will resonate with this specific audience.
Custom conversion events show at the top of the list in the dropdown. Iterable system events appear below your custom conversion events. Conversion events that are disallowed in Iterable (in your project settings) are not included in the list.
View metrics for a date range
To show metrics for a specific date range, use the date picker (found next to the Behavioral heading in the All Time dropdown). The date range you select only applies to your session of Audience Insights—the next user to view insights will see All Time.
Lists of users who haven't received many campaigns may not show much Audience Insights data—especially for shorter date ranges.
To view demographic data for this list, check out the Demographics section of Audience Insights. This data is generated from user profile fields stored on each user's profile, and includes information about devices, domains, Brand Affinity, locales, and location.
In addition to the standard demographic insights, you can add custom demographics insights based on user profile fields that exist in this project.
Use this information to compare lists and understand if different demographic characteristics are associated with different levels of engagement. Then, adjust your marketing strategy as needed.
Here's the demographic data displayed by Audience Insights:
|Insight name||What it means||How it's calculated|
|Brand Affinity||Percentage breakdown of Brand Affinity score for users in this list. Requires the ||(Brand Affinity score category) / (Total # of Brand Affinity scores)|
|Email domains for users in this list||Percentage breakdown of different email domains used by the users in this list. Requires the ||List of domains by type.|
|Devices||The type of device used. The ||List of devices by type.|
|Locale||The locales stored on the users' profiles. Requires the ||(Each locale) / (Total # of locales).|
To see where the users in a list are located geographically, scroll to the
bottom of the Demographics area. This map is populated with location dots
that represent the geographical locations of users in this list. The locations
are based on the
city user profile field.
See where this list is used
To learn where a list is being used in Iterable (in campaigns, journeys, and other lists), scroll to the bottom of the Audience Insights panel.
- Name - The name and ID of the campaign, journey, or list.
- Medium - The message medium for the campaign or journey.
- Type - The reference type (campaign, journey, list).
- Status - The status of the campaign or journey.
- Last modified - The date, time, and user who last modified the list, as well as when the list was originally created.
In addition to Iterable's default insights, you can add custom insights for any conversion event or user profile field in your project so you can see data that's relevant to your business goals.
For example, to learn if these users open your emails and subscribe to your newsletter, add a custom behavioral insight for the Email Open conversion event, and another for the custom conversion event you use to track newsletter subscriptions.
- Iterable processes data for the insight when you add it, but the insight may not appear right away. If you don't see insight data, check back in an hour or so!
- Disallowed conversion events and hidden user profile fields (configured in project settings) do not show in the custom insight dropdowns.
Adding custom insights
There is a maximum limit of four custom behavioral insights and four custom demographic insights. If you've reached the maximum number of custom insights in a section, you must remove an insight to add another.
Custom insights are shared across all lists in your project, which means you could see insights added by other users in your project.
To start adding custom insights:
With Audience Insights open, go to the Behavioral or Demographic area.
Click Add event (behavioral) or Add user profile field (demographic).
Choose how you would like the data to display:
- Show with chart - Displays the insight in a round chart.
- Show as table - Displays the insight in a table layout, with the user profile field description on the left and the value on the right.
- Show total count - Displays the insight as a whole number.
- Show as rate - Displays the insight as a rate per user, which can be a whole number or a decimal. A user is only ever counted once, even if they convert multiple times on the same conversion event.
Select the conversion event or user profile field you want for your custom insight. Your insights begin to process. Check back in an hour to see your custom insight data.
How custom insights are calculated
Custom insights are determined using the calculations in the table below.
|Custom insight||How it's calculated|
|Show total count (total events)||All occurrences of the conversion event, for this list of users, in the set time range.|
|Show as rate (events per user)||(Number of users who converted on the conversion event) / (Number of users in the list)|
|Show with chart||(Users whose profiles contain the user profile field) / (Total users in the list)|
|Show as table||The user profile field name and the number of users whose profiles contain the user profile field.|
Removing custom insights
You might remove an insight because you don't need it anymore, or you are at the limit for the section and want to add another.
To remove a custom insight, hover over it and click X.
If an insight doesn't have an X in the corner, it's a default insight and can't be removed.
Using insights to improve customer engagement
With Audience Insights, user data can help you make informed decisions and improve the effectiveness of your marketing campaigns. Check out these use cases for ideas!
Examine trends to help identify churn risks
To identify potential churn risks, take a look at metrics like conversion rate and Brand Affinity score. Do you notice particular lists with lower-than-average conversion rates? You might want to send them specialized campaigns. Similarly, are there lists of users who have neutral or negative Brand Affinity scores? Consider sending those users campaigns containing incentives, like a discount code, to increase their brand engagement.
Use location data for precise campaign timing
With location data, you can see the geographical locations of the users in the selected list. This can help you craft relevant messaging for the users depending on where they live, local current events, regional preferences, and more.
Follow unsubscribes and adjust campaign send frequency
If you notice that a particular list is unsubscribing at a higher-than-average rate, those users could be receiving too many messages. You may want to look at how often that list is receiving campaigns (in the Where is this used? area), and adjust based on your findings.