1. A method comprising: obtaining a first predicted conversion rate for an advertisement appearing on a first publisher property, where the first predicted conversion rate is obtained using a learning model developed from a combination of advertiser and publisher data associated with the advertisement; obtaining a second predicted conversion rate for the advertisement appearing on a second publisher property; computing, by one or more processors, a multiplier using the first and second predicted conversion rates, wherein the multiplier is based on a minimum of (i) a first value specifying a cap on the multiplier and (ii) a function of a probability that a conversion will result from a selection of the advertisement by a user on the first publisher property with respect to a probability that a conversion will result from a selection of the advertisement by a user on the second publisher property; and automatically adjusting a bid of an advertiser associated with the advertisement using the multiplier to equalize a cost-per-conversion for the advertisement between the first and second publisher properties, wherein the cost-per-conversion is an advertising cost to an advertiser to achieve a specified consumer transaction resulting from an advertisement appearing on a publisher property.