How does Liveintent work

Using Advertising Audiences

learning goals

After completing this lesson, you will be able to do the following tasks:

  • Identify Advertising Audiences use cases
  • Prepare your data for audience creation
  • Create target groups in your account

Interesting facts about advertising audiences

With Advertising Audiences, marketers can easily reach customers through their most visited channels, be it Facebook, Google, Instagram, or others. And best of all: Advertising Audiences uses first party data and thus offers advertisers a significant advantage. Advertising Audiences enables you to provide customized experiences and target audiences based on the valuable information you already have.

Suggestions for target groups

Data can be recorded from all available lists or data extensions. You can create a Salesforce report and create a new data extension using data import or even use Social Studio topic profiles. The following action-based target group suggestions are intended to support you in finding sensible approaches for your company.

  • Customers have just opted for email or SMS.
  • The customers have visited your store.
  • The customers have reached a certain milestone or an anniversary (e.g. anniversary of registration as a customer or birthday of the customer).
  • Customers have interacted with your brand through social media.
  • Customers responded to an email (opened it or clicked on it).
  • Customers have reached out to customer support with a complaint.
  • The customers have reached a certain customer loyalty status.
  • The customers have made their first purchase or a subsequent purchase.
  • You haven't heard from customers in a while.

Next, test different strategies based on the information you have about your customers.

Suppression target audience
Target group addressed
Similar target group
Disgruntled customers (based on social media or customer support operations)
Current customers (recommendation based on purchase. Has a house been bought, do customers need furniture?)
VIP customers / customers from loyalty programs
Existing customers (have already interacted with email or SMS)
Customers with the highest turnover
Customers who recently bought something that they rarely buy (e.g. a house, car, etc.)
Customers who did not respond to an important email
Seasonal buyer profile (purchases are only made in the period before public holidays, sales etc.)

Suppression audiences that are regularly updated improve the customer experience. When a customer takes advantage of an offer, makes a purchase, or reports a problem to customer service, advertising campaigns can be stopped quickly.

Data is everything - do you remember?

Now that you know what data you want to use, let's make sure the data is useful to you. But first, let's turn briefly to the subject of security. Data never leaves Marketing Cloud in its original format. All shared data is transmitted to the ad network via a secure API using a hash method called SHA-256. The same algorithm is also used by Facebook and other platforms. So if a suitable user is active on this platform and won your company's ad, your ad will be shown to that user. After this general note on the security of your data, let's take a look at the data usage of the individual channels.

  • Facebook and Instagram
    • The data matching is based on standard or extended data points. The more attributes that can be mapped, the higher your match rate because the 1: 1 relationship is maintained.
      • Standard, unique attributes: Email, phone, mobile advertiser ID or Facebook application user ID
      • Extended compliance data points: First name or initials, last name, city, state, county, date of birth, year of birth, age, zip code and / or gender
    • A minimum of 20 matches is required, but the match rate is only displayed for 1000 or more users.
  • Twitter
    • Matching with Twitter user IDs based on email, device ID or Twitter handle / ID
    • A minimum of 500 matches are required and users must have been active within the last 30 days.
  • Google Ads ecosystem
    • default: Comparison of data with registered users on the basis of every Google property based on the email
    • Google Customer Match: Match for matches based on email address, mobile ID, and phone number
    • A minimum of 1000 matches are required.
  • LinkedIn
    • Comparison of data based on the email
    • A minimum of 300 matches is required, but we recommend over 10,000 matches for best performance.
  • Pinterest
    • Comparison of data based on the email
    • A minimum of 100 matches are required.
  • Salesforce Audience Studio
    • Comparison of data based on email and telephone number

Before creating your audience, it is important to review your data to make sure it meets the basic requirements for each channel. Here are some other best practices for the data you use for your target audience.

  • Limit the number of columns in tables and remove all unnecessary data to avoid long processing times.
  • Use the appropriate data type and field length, but avoid lengths of over 100 characters.
  • All data extensions used for target groups must contain an e-mail field with the field type for e-mail data, even if this is left blank.
  • If the data includes phone numbers, you should include the country code (such as +1 for the United States).

Extended match

The extended match is the dream of every dating agency. A match is when the target network recognizes the contact information transmitted in the target group and can confirm a 1: 1 match. Both Facebook and Google allow the use of multiple tags so that more matches can be found. What are the advantages of this? The match rates of target groups only increase with more qualifiers. Higher match rates with better qualifiers mean more suitable people will see your ad.

Create a target audience

Do you remember Linda from Cloud Kicks? Linda plans to create a target audience with top customers to suppress. It can lower advertising costs with it - why should she also advertise for customers who already know and love her brand?

First, Linda navigates to the overview page and chooses Create a new audience out. Then she sets "Top Purchasers" as the name for the target group and enters a description. Next, she selects the Cloud Kick Facebook account as aim out and checks that at Ad account the correct account is selected. Then she clicks on Configure.

Under configuration chooses Linda Data extensions and looks for your already created data extension "Top Purchasers". With Facebook accounts, Linda has to confirm where Cloud Kicks got the data from. Under Data Source (1) There are three options to choose from: "From users" (first party data), "From partner (s)" (third party data) and "From users and partner (s)" (combination of first and third party data). Since this data comes from her Marketing Cloud account, Linda chooses From users out. Next, it maps the data extension attributes to the Facebook tags (2) too. Don't forget: the more identifiers, the better the match.

After that, she will add her email under the check box to receive a notification when the condition is met Any event occurs. is fulfilled for this target group.

Linda checks her configuration and finally chooses Activate out. Now she has to choose between the two audience activation options Update manually and Schedule an update decide. Since Linda likes to be efficient, she selects "Schedule Update" and then specifies that the target audience should be updated daily. Then she clicks on Activate.

Once activated, it will take a while for match scores to appear. Give the target audience between 24 and 48 hours to stabilize before using them.

Two days later, Linda's patience is rewarded, and her team can now start using the target group created.


Hopefully you will not be disappointed: This is not about prominent doppelgangers, but about similarities among customers. When creating a Facebook-based target group in Marketing Cloud (MC), you have the option of creating similar target groups. How does this work? Facebook compares the data in the MC audience with its users and creates a new audience that is similar to the individuals from your original list. Two options are available for the comparison.

  • Optimize for similarity:This is where the 1% of users with the greatest agreement are determined.
    • Pros: Greater similarity to your current customers
    • Disadvantages: Smaller target group
  • Optimize for reach: Here the 5% of users with the highest agreement are determined.
    • Advantages: Larger target group
    • Disadvantages: The target audience may not contain the ideal customers.

Linda knows this feature can help Cloud Kicks target people who are similar to its most loyal customers. Now that she has a stable target group, she switches to the "Top Purchaser" target group and clicks on Add

Linda enters a name for the similar audience that chooses Optimize for similarity and then put that country firmly. Then she clicks on Finished.

After creating the audiences, Linda is now ready for her next task, creating a lead capture campaign on Facebook.