Koddi's Outcome Automation delivers new results as AI-powered yield optimization evolves

Outcome Automation empowers commerce media networks to define their own optimization goals and leverage network-specific intelligence to drive the business outcomes that matter most.

For commerce media networks, growth depends on balancing two priorities: delivering stronger outcomes for advertisers and maximizing the revenue potential of every advertising opportunity.

Achieving both becomes increasingly complex as networks scale. Advertisers have different performance goals, shopper behavior and marketplace conditions change constantly, and each network has unique inventory, audiences, and business objectives. Manual bidding can’t keep pace with these variables, while traditional bid automation often relies on standardized approaches that don’t account for the nuances of each marketplace.

These limitations can make it harder for advertisers to reach valuable customers and drive sales, while preventing networks from realizing the full revenue potential of their media programs.

Koddi is continuing to advance its AI-powered yield optimization capabilities to address these challenges. With predictive intelligence and Outcome Automation goals tailored to each network’s unique business, Koddi helps advertisers achieve their performance goals while enabling networks to capture more value from their existing inventory and advertiser investment.

Predicting performance to drive better advertiser outcomes

Outcome Automation is at the center of Koddi’s optimization capabilities. It uses predictive intelligence to align bids with advertiser performance goals, while enabling networks to set specific goals that align with their unique business.

Rather than relying solely on historical campaign performance, Koddi’s Outcome Automation evaluates recent activity, marketplace conditions, expected future opportunities, and available budgets to determine how advertisers should compete for inventory.

The technology continuously adjusts bidding strategies to balance advertiser returns with opportunities to capture additional traffic and spend.

For example, an advertiser exceeding its target may have room to compete more aggressively for valuable impressions while maintaining its desired return. When performance falls below target, bidding can become more conservative to prioritize efficiency.

This approach helps advertisers focus on their desired outcomes while reducing the manual effort required to manage bids. At the same time, for networks, it creates opportunities to grow media revenue by putting more of their existing advertiser budgets to work.

Intelligence that adapts to each marketplace

Every commerce media network has different inventory, advertiser objectives, customer behaviors, and business rules. Koddi’s approach combines predictive models with the first-party signals and marketplace intelligence that make each network unique.

Beyond automated bidding, Koddi continues to advance the intelligence behind ad decisioning, including relevancy models, performance measurement, and experimentation. These capabilities help networks evaluate the value of advertising opportunities and refine optimization strategies as their businesses evolve. 

Our 1-1 intelligence framework means:

• Outcomes are set network by network. Rather than limiting a network towards ROAS-based bid automation, our networks define their own goals. For example, an automotive marketplace may prioritize lead generation, using automation tailored to its longer purchase journey, advertiser objectives, and overall business goals.
• Relevancy is set based on unique signals. We don’t have a one-size-fits-all model: each network’s relevancy is grounded in their unique data to drive stronger performance.
• We take a consultative approach. Model training is an ongoing process. We continuously test new signals, refine their relative importance, and evaluate the underlying data to improve model performance.

For networks expanding into additional placements, formats, and channels, this creates a more scalable foundation for maximizing the value of their media networks. For more, check out our article from Senior Product Manager Sneha Popley on how we set, test, and iterate modeling.

Proven results

A leading retail media network working with Koddi recently expanded predictive bidding across its sponsored listings program to improve advertiser outcomes and budget utilization.

Across hundreds of ad groups, the network achieved:

• 57% higher budget utilization, putting more committed advertiser budgets to work.
• 26% more ad groups meeting their ROAS goals, improving performance against advertiser objectives.
• 50% of eligible ad groups increasing spend after at least 10 days using automation.

As Koddi scaled Outcome Automation across commerce media networks, another activation demonstrated its impact on advertiser outcomes:

• 2x as many units sold, driving more product purchases.
• 2x as many transactions, demonstrating stronger conversion outcomes.
• 1.9x as much advertiser revenue, generating more sales through the network.

Together, these results demonstrate how predictive bidding helps advertisers capture more sales and revenue from existing advertising opportunities while enabling networks to maximize the value of their media programs.

Built for continuous commerce growth without complexity

Outcome Automation allows advertisers to establish performance objectives while Koddi continuously optimizes bidding decisions. Teams can spend more time evaluating results, refining strategy, and identifying growth opportunities without complexity.

Then, better automation means networks can support more advertisers, improve budget utilization, and create a more sophisticated media offering without requiring a proportional increase in operational resources. It all happens while preserving consumer experience, and evolving with each network’s business.

By connecting advertiser objectives, predictive intelligence, and marketplace-specific signals, Koddi helps networks improve performance while building larger, more profitable media businesses.