Advertising venues and optimization

1. A system that provides an online advertising platform, the system comprising:

a first non-transitory machine-readable medium storing data characterizing performance characteristics of a plurality of impression inventory units, wherein an impression inventory represents one or more advertisement serving opportunities; and

a second non-transitory machine-readable medium storing instructions executable by one or more data processors to:

group the impression inventory units based at least in part on the performance characteristics of the impression inventory units;

determine an initial bid price for an advertising campaign based at least in part on a historical conversion rate for a set of the impression inventory units and a bidding goal associated with the advertising campaign;

execute a plurality of real-time bidding transactions for the advertising campaign on at least some of the impression inventory units, each transaction comprising a bid price based at least in part on the initial bid price;

if a number of success events for the advertising campaign reaches a threshold, determine an optimized bid price for the advertising campaign based at least in part on the number of success events and a number of impressions resulting from the execution of the real-time bidding transactions; and

if the number of success events for the advertising campaign does not reach the threshold, determine that the advertising campaign cannot be competitive on the set of impression inventory units by (i) determining a maximum cost-per-mille (CPM) value based at least in part on the number of success events and the number of impressions resulting from the execution of the real-time bidding transactions, and (ii) comparing the maximum CPM value to an estimated average price of the impression inventory units on which the plurality of real-time bidding transactions were executed.

2. The system of claim 1 , wherein the performance characteristics are measured using one or more of the following revenue models: cost-per-mille, cost-per-click, cost-per action, click-through-rate, and cost-per-conversion.

3. The system of claim 1 , wherein the instructions to group the impression inventory units comprise instructions executable by the one or more data processors to:

examine data characterizing performance characteristics of at least some of the impression inventory units; and

based at least in part on results of the examination, identify, as a group, a cluster of impression inventory units that share similar performance characteristics.

4. The system of claim 1 , wherein the instructions to group the impression inventory units comprise instructions executable by the one or more data processors to:

examine data characterizing impression volume associated with at least some of the impression inventory units; and

based at least in part on results of the examination, identify, as a group, a cluster of impression inventory units that have an aggregate impression volume that exceeds a threshold.

5. The system of claim 4 , wherein the second non-transitory machine-readable medium further stores instructions executable by the one or more data processors to:

rank order groups of impression inventory units based at least in part on one or more of the following: the respective aggregate impression volumes and a financial metric.

6. The system of claim 1 , wherein the success events include one or more of conversion events and click events.

7. A system that provides an online advertising platform, the system comprising:

a first non-transitory machine-readable medium storing first data characterizing a set of venues, each venue including a set of impression inventory units that share similar performance characteristics, wherein an impression inventory represents one or more advertisement serving opportunities, each venue having an estimated aggregate impression volume that exceeds a threshold;

a second non-transitory machine-readable medium storing second data characterizing member-specific prior executed transactions on the platform; and

a third non-transitory machine-readable medium storing instructions executable by one or more data processors to:

accept, from a first member, a specification of an advertising campaign, the specification including one or more bidding goals;

determine an initial bid price for the advertising campaign based at least in part on the second data;

iteratively execute a first plurality of real-time bidding transactions for the campaign on one or more of the venues to determine a first bid valuation for the campaign that satisfies the specification, at least some of the first plurality of transactions comprising a bid price based at least in part on the initial bid price;

if a number of success events for the advertising campaign reaches a threshold, determine an optimized bid price for the advertising campaign based at least in part on the number of success events and a number of impressions resulting from the execution of the real-time bidding transactions; and

if the number of success events for the advertising campaign does not reach the threshold, determine that the advertising campaign cannot be competitive on the set of impression inventory units by (i) determining a maximum cost-per-mille (CPM) value based at least in part on the number of success events and the number of impressions resulting from the execution of the real-time bidding transactions, and (ii) comparing the maximum CPM value to an estimated average price of the impression inventory units on which the plurality of real-time bidding transactions were executed.

8. The system of claim 7 , wherein the third non-transitory machine readable medium stores instructions executable by the one or more data processors to:

examine the second data to generate a rank ordered set of venues for the first member; and

wherein the real-time bidding transactions are executed on a first venue of the ranked ordered set that is the highest ranked venue of the ranked ordered set.

9. The system of claim 7 , wherein the success events include one or more of conversion events and click events.

10. The system of claim 7 , wherein the third non-transitory machine readable medium stores instructions executable by the one or more data processors to:

examine the second data to generate a rank ordered set of venues for the first member; and

execute a second plurality of real-time biding transactions for the campaign on the first venue of the ranked ordered set to determine a second bid valuation for the first campaign that satisfies the specification.

11. The system of claim 10 , wherein the second bid valuation is capped in accordance with a maximum cost-per-mille revenue model.

12. The system of claim 10 , wherein the instructions to execute the second plurality of first campaign transactions comprises instructions executable by the one or more data processors to:

iteratively execute the second plurality of campaign transactions until a second events criteria is satisfied.

13. The system of claim 12 , wherein the second events criteria includes a comparison of a number of success events and a confidence threshold.

14. The system of claim 13 , wherein the success events include one of conversion events and click events.

15. The system of claim 10 , wherein the third non-transitory machine-readable medium stores instructions executable by the one or more data processors to:

apply a cadence modifier to the second bid valuation.

16. The system of claim 15 , wherein the cadence modifier includes at least one of a recency component and a frequency component.