How to Use LinkedIn Predictive Audiences for Lead Generation

LinkedIn has long been a great platform for B2B marketing and lead generation, offering advertisers precise targeting options based on professional attributes like company name, job title, industry, and company size. However, with changing digital marketing trends and increasing competition, marketers need smarter ways to reach the right audience efficiently.

That’s where LinkedIn Predictive Audiences come in.

Our paid media team wanted to put LinkedIn’s predictive audiences to the test to see if they truly improve reach in a meaningful way without sacrificing quality. Are these AI-powered audiences as effective as LinkedIn claims? Do they actually help advertisers generate better leads?

In this post, we’ll break down what LinkedIn Predictive Audiences are, why they matter, and how you can use them to optimize your lead generation strategy. Plus, we’ll share insights from our own testing, along with best practices to help you get the most out of this feature.

Predictive Audiences is an AI-driven targeting feature in LinkedIn, released in 2023 to help advertisers scale their campaigns without losing precision. Instead of relying solely on traditional targeting methods, this feature allows LinkedIn’s machine learning algorithms to analyze your existing audience data and identify similar users who are likely to engage with your campaign.

Predictive vs Lookalike Audiences on LinkedIn

With LinkedIn discontinuing Lookalike audiences in early 2024, marketers have been shifting toward predictive audiences. This audience type is a more dynamic, AI-driven audience targeting solution. But what’s the difference, and why does it matter for your LinkedIn campaigns?

Lookalike audiences helped marketers find new prospects by identifying LinkedIn members with similar characteristics to an existing audience (such as website visitors or uploaded contact lists). While effective, this method relied on static data and didn’t expand in real time.

Predictive audiences, on the other hand, take things a step further. By leveraging LinkedIn’s AI, this feature analyzes behavioral signals and conversion data to identify users who are not just similar but more likely to take action based on current trends.

Main Differences:

• AI-Powered vs Static Matching: Lookalike audiences expanded research based on past similarities, while Predictive audiences dynamically expanded, using machine learning to refine targeting over time.

• Future-Focused Targeting: Instead of mirroring existing audiences, Predictive audiences anticipate who is most likely to convert, optimizing ad performance and budget efficiency.

• More Customization and Scalability: With Predictive audiences, advertisers can use multiple first-party data sources to create highly personalized audience segments.

This move from Lookalike to Predictive audiences reflects a broader trend in digital marketing: AI-powered, data-driven personalization. Instead of relying on historical trends, LinkedIn now helps marketers proactively reach the right audience at the right time. Leveraging Predictive audiences can lead to more efficient ad spend, better engagement, and higher-quality leads.

How LinkedIn Predictive Audiences Works

Predictive Audiences uses LinkedIn’s first-party data, behavioral signals, and AI models to find professionals who exhibit traits and behaviors similar to those in your existing audience. Advertisers can create predictive audiences based on:

• Website Visitors: Users who have visited your website but haven’t yet converted.

• Lead Gen Form Submissions: Individuals who have engaged with your previous LinkedIn lead forms.

• Customer Lists: Existing customers or high-value prospects you upload to LinkedIn.

• Engagement Audiences: Users who have interacted with your LinkedIn content, such as video views or ad clicks.

Once LinkedIn analyzes these data sources, it builds a predictive audience of new users who are statistically more likely to engage, making it easier to scale your campaign without guessing who to target.

Why Predictive Audiences Matter for Lead Generation

For advertisers looking to expand reach and improve campaign efficiency, Predictive Audiences offers a unique advantage. Instead of manually refining audience segments, LinkedIn’s AI automates the process by finding high-intent users who share characteristics with your best leads.

Here’s why that matters:

• Increases Scale Without Losing Precision – Predictive Audiences help advertisers go beyond predefined targeting criteria while still ensuring that new prospects are highly relevant.

• Improves Lead Quality – By leveraging LinkedIn’s AI-driven predictions, advertisers can attract more qualified leads instead of wasting budget on broad targeting.

• Reduces Cost-Per-Lead (CPL) – More relevant targeting often leads to higher engagement rates and a better return on ad spend (ROAS).

• Adapts to Changing Audience Behavior – Unlike static audience lists, Predictive Audiences update dynamically as LinkedIn gathers new engagement data.

By using this feature, advertisers can ensure that their campaigns reach the right people at the right time, maximizing lead generation results while minimizing wasted spend.

Setting up LinkedIn Predictive Audiences is a straightforward process, but to get the best results, you’ll need to ensure your data is structured correctly and that you’re using a high-quality seed audience. Here’s a step-by-step guide to help you get started.

Step 1: Choose Your Data Source

Before creating a predictive audience, think about the specific behavior you want to replicate. The effectiveness of LinkedIn’s AI-driven predictions depends on the quality and relevance of your source audience.

• If your goal is lead generation, use a seed audience of high-quality leads or current customers who have previously converted.

• If you want to target website visitors, set up LinkedIn’s Insight Tag and create an audience of users who have engaged with key pages (e.g., product pages or pricing pages).

• If your objective is brand engagement, you can use lists of users who have interacted with your LinkedIn posts, video ads, or lead forms.

Step 2: Prepare Your Audience List

Once you’ve determined your data source, you’ll need to upload an audience list that meets LinkedIn’s requirements.

• Your list should contain between 300 and 300,000 records.

• For best results, LinkedIn recommends including the following data fields:

  • First Name

  • Last Name

  • Email Address

  • Job Title

  • Employee Company

  • Country

The more data you provide, the better LinkedIn can match your audience. Higher match rates result in more accurate predictive audiences, leading to better campaign performance.

💡 Our audience lists ranged from 40,000 to 75,000 contacts, and we achieved a match rate of 75%.

Step 3: Upload Your Data to LinkedIn

1. Navigate to LinkedIn Campaign Manager and go to the Matched Audiences section.
   
   
2. Select Company or Contact List, depending on your data source.
   
   
3. Select your List Type → Upload a List.
   
   
4. Upload your CSV file and ensure it follows LinkedIn’s formatting guidelines.
5. Wait for LinkedIn to process the list, which may take a few hours.

Step 4: Create a Predictive Audience

Once your audience list is processed, you can use it as a seed audience to generate a predictive audience.

1. In Campaign Manager, go to Matched Audiences and select Create Audience.
   
   
2. Choose Predictive Audience and select the source audience you just uploaded.
   
   
3. LinkedIn will analyze your data and generate an AI-powered audience of users who exhibit similar behaviors.

Step 5: Wait for Audience Processing

• Predictive audiences can take up to 48 hours to fully populate.

• Once ready, the audience will appear in your Matched Audiences list, and you can use it in your LinkedIn ad campaigns.

  • Keep in mind that LinkedIn allows a maximum of 100 predictive audiences per account, so plan your strategy accordingly.

To test LinkedIn’s Predictive Audiences, we took a high-quality contact list and used it as the foundation for modeling a larger, AI-driven audience. Our goal was to determine if Predictive Audiences could reduce cost-per-lead (CPL) while maintaining lead quality (comparison results found below) in a lead generation campaign using document ads.

We started by uploading a seed list of high-value contacts, ensuring that it included the essential fields (name, job title, email, company, country) for optimal match rates. Since Predictive Audiences works by identifying users with similar behaviors, we wanted to provide a strong, high-intent dataset as our foundation.

We then designed a document ad campaign, leveraging downloadable guides and playbooks as lead magnets. These types of content have consistently performed well in past LinkedIn campaigns, helping to drive engagement and collect quality leads.

Once the Predictive Audiences were added, we further refined our campaign with targeting exclusions and additional filters based on historical performance.

• Key exclusion: We ensured that our seed audience was excluded from this campaign. This prevented wasted spend by ensuring we weren’t targeting users who were already on our list to begin with. We also layered in our CRM leads as exclusions to ensure our campaigns were focused on driving new leads.

Testing Bid Strategies

To optimize our budget, we experimented with different LinkedIn bid strategies:

1. Manual Bidding (our primary strategy) – This allowed us to set and adjust bids strategically to maximize performance and control CPL.

2. Maximum Delivery – LinkedIn automatically adjusts bids to spend the full budget and maximize reach.

3. Cost Cap Bidding – LinkedIn dynamically adjusts bids to stay within a predefined maximum cost per result.

📌 Key takeaway: Manual bidding significantly outperformed Max Delivery, as we could fine-tune bids and stretch our daily budget further.

What We Learned

The results from our first month of testing Predictive Audiences were exceptional:

• Cost Per Lead (CPL) Comparisons:

  • $46.86 – Predictive Audience CPL (Jan ‘25)

  • $85.27 – Contact List Retargeting CPL (Jan ‘25)

  • $76.92 – Previous Playbook Campaign CPL (Dec ‘24)

• Performance Metrics from Predictive LinkedIn Ads campaign:

  • 39% lower CPL than our previous playbook campaign

  • 45% lower CPL than retargeting a contact list

  • 87% of leads qualified as MQLs

📌 Key Learning: Predictive Audiences delivered outstanding results early on. However, performance dropped off as the most engaged users within the audience were targeted.

Adjusting Our Strategy for Long-Term Success

One of the biggest takeaways was that ad fatigue set in quickly once the most engaged prospects had already interacted with our campaign. To counteract this:

• We now refresh the document ad copy every 6 weeks to keep engagement high.

• We also rotate new lead magnets (guides, playbooks, whitepapers) to ensure continued audience interest.

From our testing, we discovered several best practices to optimize LinkedIn Predictive Audiences for lead generation:

Ad Copy & Creative Best Practices

• Keep ad copy between 100–220 characters to avoid truncation while providing enough context.

• Use 4 to 7 different creatives per campaign.

  • LinkedIn allows up to 7 ad impressions per user in 48 hours, so more creatives improve campaign reach.

Bidding & Budgeting Strategies

• Start with manual bidding for better cost control.

• We started with a low bid (~$6) and increased it based on daily spending and performance.

  • Our best-performing audience sizes ranged from 50K to 100K users—audiences larger than 500K were less effective.

Optimizing Lead Quality

• For B2B campaigns, enable the email verification option in LinkedIn lead forms.

  • This may slightly lower lead volume, but it significantly improves lead quality and reduces fake submissions.

Our Predictive Audience campaign exceeded expectations, delivering higher-quality leads at a lower CPL. However, ongoing audience refreshes and content updates are important to maintaining performance over time.

LinkedIn Predictive Audiences are a powerful way to expand your campaign reach while keeping lead quality high. Whether you’re looking to optimize your ad strategy, lower your CPL, or scale your lead generation efforts, we can help.

Want to see how Predictive Audiences can work for your business? Contact us today to discuss your LinkedIn ad strategy and start driving better results!