Skip to main content

         This documentation site is for previous versions. Visit our new documentation site for current releases.      

Optimize ad spend with AI-driven Paid Media Strategies (8.2)

Updated on May 3, 2021

Pega users leverage their next-best-action (NBA) strategies on Paid Channels using Paid Media Manager – and we have made it simple for them to hit the ground running, and leverage the full power of Pega’s AI.

With the latest release of Pega Infinity™, users now have out-of-the-box, AI-driven Paid Media Strategies. These strategies leverage adaptive models to determine the increased likelihood for an individual to convert if they click on a paid ad, then use this expected value to drive the willingness to pay for a click; per offer, and per customer.

But what if a customer does not respond? Do not worry, Pega has you covered there too. Our pre-built, adaptive learning algorithms automatically adjust in real-time, re-calculating the likelihood that the customer will accept the offer even without a click, and automatically re-prioritizing the bidding strategy accordingly. That way, you can bid more where it matters – like for customers where a click significantly increases their propensity to accept, and less where it does not.


Paid Media Strategies in Pega Next-Best-Action Designer

For more information, see the "Paid Media Manager" chapter of the Pega Marketing User Guide on the Pega Marketing product page.

  • Previous topic Enhance engagement with Customer Funnel Analysis (8.2)
  • Next topic Empower business users to easily define eligibility rules (8.2)

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

Did you find this content helpful?

Want to help us improve this content?

We'd prefer it if you saw us at our best. is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us