Case Studies

Case Study

Bidstream Optimizer is a powerful product, one that helps our clients achieve a variety of busines goals. Some of the most common Bidstream Optimizer strategies implemented by our clients include the following:

Bidstream Optimizer can execute on these strategies quickly and with minimal disruption. Results are immediate. Let's look at some examples of these strategies at work.

1. Maximizing the revenue for a given infrastructure

Limitations on infrastructure capacity can hinder growth. Often a client will find themselves with the untapped demand, but it lies fallow until they can expand. Bidstream Optimizer can monetize this demand with no increase in infrastructure cost by intelligent filtering of the bidstream. Bid requests with minimal potential for revenue are filtered out, leaving a more potent bidstream flowing through the existing infrastructure. Let's look at an illustration:

BASELINE CONSERVATIVE AGGRESSIVE
AD Filter Setting 0% 20% 60%
Revenue
Incoming Revenue $113,294 $141,617 $283,235
Revenue Retention Rate 100% 99% 78%
Retained Revenue $113,294 $141,008 $220,753
Cost
Incoming QPS 42,432 53,040 106,080
Filter Rate 0% 20% 60%
QPS Cost $63,648 $63,648 $63,648
Profit
Profit After Filtering $49,646 $77,360 $157,105
% Increase in Profit 0% +56% +216%

In the example above, the greater the filter rate, the greater the QPS (and potential revenue!) the client can expose themselves to. Filtering cuts back dramatically on costs, but only moderately on revenue, increasing profit with every unproductive bid request that's filtered out.

2. Minimizing infrastructure costs

Other clients may not have as many opportunities for revenue growth, but instead want to cut down on the cost of their existing bidstream.

BASELINE CONSERVATIVE AGGRESSIVE
AD Filter Setting 0% 20% 50%
Revenue
Incoming Revenue $226,588 $226,588 $226,588
Revenue Retention Rate 100% 99% 85%
Retained Revenue $226,588 $225,613 $192,146
Cost
Incoming QPS 84,864 84,864 84,864
Filter Rate 0% 20% 50%
QPS Cost $127,296 $101,837 $63,648
Profit
Profit After Filtering $99,291 $123,776 $128,498
% Increase in Profit 0% +25% +29%

In the example above, the greater the filter rate, the lower the bidstream cost (QPS) the client incurs. As in the case of maximizing revenue, filtering cuts back dramatically on costs, but only moderately on revenue, allowing for a dramatic scaleback in infrastructure.