Maximizing Growth with LinkedIn Predictive Audiences

  • Dani Shaked

LinkedIn’s cutting-edge Predictive Audiences (PA) harness the power of artificial intelligence to revolutionize audience segmentation. By analyzing first-party data, lead gen form completions, and conversion data from websites, the platform’s AI model extracts demographics, firmographics, and behavioral attributes to predict users likely to exhibit similar conversion behavior.

Unlike traditional lookalike audiences, PA goes beyond fixed methodologies. It continuously learns and evolves as campaigns progress, utilizing a myriad of data points, including website audiences, video ad audiences, company lists, and contact lists. With the impending discontinuation of lookalike audiences in February 2024, PA emerges as a dynamic and sophisticated solution.

Embarking on the Predictive Analytics Journey

To leverage the power of PA effectively, ensure that your seed audience data is recent, high-quality, and comprises more than 300 records with high-value conversions. Avoid using lower-funnel conversions for seeding. When creating the audience, stick to no more than 200 times your seed source size and align your content for optimal conversion chances.

Keeping specific and measurable goals in mind, run your campaign for at least three months to accumulate valuable learnings. These insights can be fed back into the AI algorithm to refine and enhance its predictive capabilities. Conduct tests with different formats, creative elements, and against other campaigns to continually optimize your strategy.

The Crucial Role of Data-Driven Targeting

In the realm of successful marketing campaigns, data-driven targeting is paramount, especially when utilizing predictive audiences. The value of informed targeting decisions cannot be overstated. Agility is key—be ready to adjust your strategy based on collected data and embrace technology that facilitates scalable and speedy adjustments.

Predictive audiences offer several advantages for marketers:

  1. In the increasingly complex realm of B2B buying, Predictive Audiences simplifies the challenge of identifying the right customers by utilizing LinkedIn’s AI and your data to create tailored, high-intent audience segments.
  2. Streamlining the audience optimization process, Predictive Audiences ensures efficient utilization of resources even under budget and time constraints.
  3. Adhering to the 95-5 Rule, Predictive Audiences focuses on bottom-funnel efforts to target the small percentage of the audience actively in the market, resulting in higher-intent leads, improved ROI, and reduced wastage.

Practical Tips and Best Practices

  1. Initiate with customer models: Start with audiences resembling existing customers, utilizing CRM data or engagement with customer-specific content. Utilize audience insights to refine targeting based on data, and test different audience sizes to find the right balance between reach and precision.
  2. Align with lead gen objectives: Integrate the lead generation objective to enhance campaign performance with Predictive Audiences. Regularly monitor performance metrics and adjust strategies based on data-driven insights.

In conclusion, LinkedIn’s Predictive Audiences offer a dynamic and forward-thinking approach to audience segmentation, providing a powerful tool for marketers to unlock faster growth in today’s competitive landscape.

Dani Shaked
About the author
Dani is super passionate about tech, startups, marketing, and making it all work together to move the needle in the right direction.
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