Your featured placement position is not simply determined by who sets the highest rate. We use a scoring system that combines your rate with your resource's quality and performance history.
Each time a buyer loads a category page, search result, or filter combination, we calculate an ad score for every resource that has featured placement enabled. The ad score is:
Ad score = your featured rate × your resource's relevance score
The relevance score is the same score used by our Relevance Algorithm, essentially a measure of how well your resource converts impressions into purchases. If you haven't already, we'd highly recommend reading the Relevance Algorithm article to understand how this score works, as it directly affects your ad performance.
The resources with the highest ad scores fill the available featured spots on that page.
This system rewards creators who make great products. A resource that converts well will have a high relevance score, which means it needs a lower rate to achieve the same ad score as a resource that converts poorly.
Example:
Even though Resource B is paying triple the rate, Resource A still wins the placement because its quality makes each impression more valuable. Resource A's creator is also keeping more of each sale.
This is intentional. We want our featured spots to show resources that buyers actually want to buy, not just the ones with the biggest advertising budget. Better products at lower rates will outperform weaker products at higher rates.
Under the old system, there were 5 fixed slots per category, and those same 5 resources showed regardless of what search or filter criteria a buyer was using. This meant that most of the time there were empty ad slots, especially when buyers narrowed their search.
The new system works differently. Featured resources are calculated per page load, for each specific combination of category, search terms, and filters. Your resource only competes for placements where it matches the buyer's criteria. This means: