Leading retailer increases budget utilization 57% with predictive bid automation

The opportunity: Scaling advertiser performance across a leading retail media network

A top retailer operates a sophisticated commerce media network with Koddi, connecting brands with millions of shoppers across its digital properties. Its sponsored product listings program enables advertisers to reach consumers across its site, even within AI-powered chatbots.

Though the network was established and scaled, the retailer faced a familiar challenge: how could it drive more advertising revenue and improve advertiser outcomes from each ad impression without compromising quality?

In this program, advertisers sometimes managed bids manually, requiring ongoing adjustments to respond to changes in campaign performance, competition, and available inventory. A bid that performed well one day could become less competitive as shopper demand and auction dynamics shifted.

Bidding too conservatively could mean missing valuable opportunities to reach shoppers and leaving available budgets unspent, but bidding too aggressively could increase costs without generating sufficient returns.

The retailer needed a more sophisticated approach to bidding that could capture additional opportunities while maintaining a focus on return on ad spend (ROAS).

The solution: Outcome Automation balances advertiser outcomes with network growth

The retailer partnered with Koddi to bring intelligent, outcome-based bidding to its commerce media network, expanding automation across its program.

Koddi’s predictive bidding technology continuously evaluates campaign performance, anticipates future advertising opportunities, and determines how to compete for those opportunities based on each advertiser’s goals and available budget.

Predicting future performance to make smarter bidding decisions

Koddi’s bid automation is built around a continuous feedback loop that connects historical performance, recent campaign activity, and expected future outcomes. Throughout the day, the technology evaluates signals such as click-through rates, conversions, revenue, auction competitiveness, and available budgets. Rather than treating all historical performance equally, Koddi incorporates more recent signals to respond to changing marketplace conditions without overreacting to individual clicks or conversions.

Using these insights, Koddi forecasts upcoming advertising opportunities, estimates how different bids may influence clicks and conversions, and calculates the expected revenue associated with those opportunities. The system then determines which bids are most likely to help advertisers achieve their goals based on the opportunities and budgets remaining throughout the day.

For advertisers, this means bids are informed by where performance is expected to go, rather than relying exclusively on where it has been.

Balancing advertiser returns with budget utilization

Koddi’s automated bidding is designed to support both advertiser returns and network revenue growth. The technology first evaluates which bidding opportunities are compatible with an advertiser’s target ROAS. Within those constraints, it looks for opportunities to increase traffic and budget utilization.

For example, an advertiser significantly exceeding its ROAS target may have room to bid more competitively and capture additional shoppers while continuing to achieve its desired return. Conversely, when a campaign falls below its target, the technology can reduce bidding aggressiveness to prioritize efficiency.

For the retailer, this creates opportunities to increase media revenue by helping advertisers make more effective use of the budgets they’ve already committed.

Giving advertisers more results with less manual management

Koddi simplifies campaign management by allowing advertisers to establish their performance goals while automation manages ongoing bid optimization.

Advertisers can return periodically to evaluate results, refine their ROAS goals, and make strategic decisions about their investment rather than repeatedly adjusting individual bids.

For a retail media network supporting hundreds or thousands of campaigns, this creates an opportunity to deliver sophisticated optimization at scale without requiring a proportional increase in manual campaign management.

The results: More advertiser budgets activated and more campaigns achieving their goals

The retailer demonstrated how predictive bidding could improve budget utilization and advertiser outcomes.

Budget utilization increased 57%. Across ad groups using automation, aggregate budget utilization improved, helping advertisers put more of their available investment to work.

26% more ad groups achieved their ROAS goals. A greater number of ad groups met their return targets after adopting automated bidding, demonstrating the potential for outcome-based optimization to improve goal attainment.

Results varied across advertisers, with some campaigns experiencing higher advertising costs and others achieving improvements in ROAS. These findings provided valuable insights into how bidding strategies could be further refined to balance efficiency, competitiveness, and scale.

What’s next

Koddi continues to evaluate performance and refine bidding strategies to help advertisers balance return on investment, budget utilization, and competitive positioning.

For commerce media networks, predictive bidding creates an opportunity to grow media revenue by making better use of existing inventory and advertiser budgets, while giving advertisers greater control over the outcomes they want to achieve.