The Waterfall Model is a sequential method of selling ad inventory in which publishers offer impressions to multiple demand partners one after another until the ad space is filled. Each demand source is ranked by priority, typically based on historical performance or average CPM.

If the first network declines an impression, it cascades down to the next until a buyer accepts it—hence the name “waterfall.” While once the industry standard, this model often resulted in revenue loss because higher-paying bids from lower-priority partners were missed.

Header bidding and unified auctions have largely replaced the waterfall approach by allowing all demand sources to compete simultaneously. Nonetheless, understanding the waterfall remains important for legacy systems and revenue analysis.

Win Rate measures the percentage of auctions an advertiser wins compared to the total number of auctions they participate in. It is calculated as: (Won Impressions ÷ Total Bid Requests) × 100.

A high win rate indicates competitive bidding and good alignment between bid values and market prices. Conversely, a low win rate may suggest underbidding, poor targeting, or strong competition in specific inventory segments.

For instance, if a campaign bids on 100,000 impressions and wins 25,000, its win rate is 25 percent. By analyzing win rate data, advertisers can adjust bids, targeting, or budgets to improve delivery efficiency and reach performance goals more effectively.

The Winning Bid is the highest bid that successfully secures an ad impression during a real-time auction. Once all bids are submitted via demand-side platforms, the ad exchange compares them and awards the impression to the bidder offering the highest value according to the auction model—first-price or second-price.

For example, if one advertiser bids €2.40 and another €2.10 in a first-price auction, the €2.40 bidder wins and pays their full bid. In a second-price system, they would pay just above €2.10. The winning bid determines both the final cost and which creative appears to the user.

Tracking winning bid data helps advertisers refine bidding strategies, analyze market competition, and identify optimal price points for future campaigns.

Whitelisting in digital advertising refers to the process of defining and approving specific domains, placements, or traffic sources for ad delivery. It is the counterpart to blacklisting and is used to ensure that campaigns only run in brand-safe, relevant, and compliant environments.

Advertisers can whitelist at various levels: domain, app, publisher ID, or even by deal ID within a private marketplace. For instance, a luxury goods advertiser might whitelist premium lifestyle websites while excluding low-quality or generic placements.

Whitelisting enhances accountability and reduces wasted impressions, providing both advertisers and publishers with higher transparency and a safer advertising ecosystem.

A Whitelist is a curated list of approved websites, apps, or publishers where an advertiser permits their ads to appear. It is a critical tool for maintaining brand safety, transparency, and performance quality. By running campaigns only on verified and reputable inventory, advertisers minimize exposure to fraud, low-quality content, or inappropriate environments.

For example, a premium brand may whitelist a group of verified publishers that align with its values and audience demographics. Programmatic platforms like TwinRed allow whitelists to be applied automatically at campaign level, ensuring every impression originates from a trusted source.

Maintaining a whitelist helps balance scale with control, protecting reputation while preserving performance consistency across campaigns.