In marketing, there’s no one-size-fits-all. Different customers have different preferences. And that’s exactly why segmentation becomes critical for meaningful engagement. The numbers speak for themselves:
- Segmented campaigns achieve 14.31% higher open rates and generate 101% more clicks than their non-segmented counterparts.[i]
- Businesses that implement predictive segmentation see revenue increases of up to 88%.[ii]
- Companies that segment their customers are 60% more likely to truly understand their audience’s challenges and concerns.[iii]
Yet, many marketers stop their segmentation at the surface, grouping contacts by basic demographics like age, location, or job title. While these filters offer a starting point, they often miss the nuances that drive real impact.
That’s where Marketo Predictive Audiences comes in. Powered by AI, this feature goes beyond the basics to help you identify high-value segments and personalize campaigns at scale. But how does it work, and when to use it?
Let’s find out.
What is Predictive Audiences in Marketo?
Marketo Predictive Audiences is an advanced capability that transforms how marketers segment audiences. It uses artificial intelligence and machine learning models to analyze customer behavior and predict their actions, such as register or unsubscribe.
Based on this data, marketers decide who to send the campaign to so as not to overload the database. This takes the guesswork out of the equation and introduces efficiency in campaign management.
How Does Predictive Audiences Work?
Predictive Audiences analyzes data from multiple sources, including email opens to click throughs, website visits, and event attendance, to determine the likelihood of future responses of the individual.
Based on this, the Marketo system assigns each contact a likelihood score for the following:
Register for an Event
It predicts the contacts who are most likely to register for an event or complete a form. You can check the model accuracy and variables used by Adobe Sensei for this under ‘Models and Insights > Likelihood to Register.’

Attend if Registered
It predicts the probability of a contact actually attending the event they registered for. The reliability and variables can be checked under ‘Models and Insights > Likelihood to Attend.’
Unsubscribe
It predicts the contacts who are most likely to unsubscribe after another message. Its variables and accuracy can be found at ‘Models and Insights > Likelihood to Unsubscribe.’
Lookalike of Previous Program Member
It identifies the contacts similar to those who have engaged in past campaigns to replicate high-performing audiences for new campaigns. You can check the model’s reliability and variables under ‘Models and Insights > Lookalike.’
Use Cases of Marketo Predictive Audiences
Maximize Registrations and Attendance
Predictive Audiences helps you build a highly targeted audience for sending invites. It offers intelligent recommendations on what and how to adjust the campaign to get the highest engagement. This helps increase the conversion rate while reducing the number of email sends.
Minimize Opt-Outs
Marketing to exhausted subscribers is a recipe for unsubscribes. By intelligently identifying signs of audience fatigue, Predictive Filters help you create a specialized list of contacts who should temporarily receive fewer communications. This increases the lifetime value of each member by keeping them engaged at the right level and frequency.
Scaling Success Across Campaigns
When running event series like webinars, you need an efficient way to replicate initial successes. After a successful pilot with a small user group, Predictive Audiences automatically finds similar users who are likely to respond just as positively. This helps you quickly identify your next ideal audience and extend your success to larger groups.
When and How to Use Predictive Audiences for Campaigns
Setting up Predictive Audiences is easy. Simply activate the feature in your Marketo admin section. Once enabled, you can incorporate predictive filters into your Smart Lists and Smart Campaigns just as you would any standard condition.
Here are some important guidelines to use Predictive Audiences in your campaigns with AI:
Works With Existing Programs: You can add predictive filters to campaigns created before enabling the feature.
Batch Campaigns Only: These filters aren’t compatible with trigger-based campaign flows.
No Cloning or Moving: Campaigns using predictive filters cannot be cloned or relocated.
Five Filter Maximum: Each Smart List can incorporate up to five predictive filters.
Automatic Safeguards: If a filter encounters an error, Marketo automatically stops the campaign and sends an alert.
Capacity Limitations: These campaigns can process up to 1 million contacts, with a platform limit of 50 active Predictive Audiences programs running simultaneously.
Real World Example of Predictive Audiences in Action
A marketing agency launched a webinar campaign using Predictive Audiences. They had a large mailing list. But upon applying the ‘Likelihood to Register’ and ‘Likelihood to Attend’ filter, their:
- Audience size dropped by 90%
- Open and conversion rates increased
- Campaign achieved the same number of registrations with less spam
The AI feature provided them with better control over the database, which prevented over-emailing while achieving the same result.
In another scenario, the agency used the ‘Lookalike of Previous Program Member’ filter to recreate a campaign that worked well a few months earlier. But this time, it didn’t perform well because predictive models do not factor in variables like:
- Deployment timing
- Offer revisions
- Subscriber weariness
This experiment provides a valuable lesson: Predictive Audiences should only be used as guidance, not a replacement. If you are running your campaigns with AI, make sure they are supervised by experts and not left on autopilot.
Pitfalls to Avoid When Using Predictive Audiences in Marketo
Pitfall 1: Filter Overload
Adding every available filter without purpose dilutes effectiveness. Instead, select only those directly supporting your campaign goals.
Pitfall 2: Neglecting Context
Different campaign types require different segmentation approaches. A technical webinar needs a different audience targeting than a promotional offer. Adjust your strategy accordingly.
Pitfall 3: Unrealistic Expectations
The system requires quality data to generate quality insights. If your database contains incomplete or inaccurate information, your predictive results will reflect these limitations.
Pitfall 4: Skipping Performance Analysis
Implement regular testing and measurement protocols. The system learns from data, and marketers should learn from outcomes.
Final Thoughts
Predictive Audiences is a powerful implementation of AI in campaign management. It is particularly valuable for organizations with large databases, as it significantly reduces email volume while streamlining workflows. By protecting your database health, enhancing conversion rates, and optimizing resource allocation, Predictive Audiences enables marketers to achieve more with less.
Have you tried it yet?