System and method for digital advertising campaign optimization
A technique for dynamically adjusting a digital advertising campaign during an active campaign flight is discussed. Using feedback from a digital survey over an exposed audience of user populations, brand lift may be calculated on a per ad creative and/or per site basis. User characteristics derived from content consumption patterns may be used to optimize ongoing campaigns and formulate target audiences and target creative formats for new campaigns.
1. A method for optimizing a digital advertising campaign, comprising:
initiating a digital advertising campaign for an advertiser, the digital advertising campaign displaying one or more ad creatives on one or more digital properties during an advertising campaign flight;
acquiring performance data from the one or more digital properties regarding the display of the ad creatives during the campaign flight, at least some of the performance data acquired through the use of a site-specific Ad Tag;
identifying one or more users that have viewed at least two ad creatives being displayed in the digital advertising campaign;
providing a digital survey during the campaign flight of the digital advertising campaign to more than one user, answers of the users to the digital survey forming a plurality of survey results;
providing the plurality of survey results and the performance data as input to a survival analysis, a Markov chain Monte Carlo simulation, a collaborative filtering and a relative importance algorithm;
calculating programmatically, via the survival analysis, the Markov chain Monte Carlo simulation, the collaborative filtering and the relative importance algorithm, a success value for at least some of the ad creatives displayed during the campaign flight for which performance data was acquired, the success value being a relative value indicative of a displayed ad creative providing an attribute previously specified by the advertiser; and
adjusting an allocation of a display of the ad creatives among the plurality of digital properties based on the calculated success value for at least some of the ad creatives.
2. The method of claim 1 wherein at least some of the performance data is acquired through the use of a Software Development Kit or is provided by a third party.
3. The method of claim 1 wherein the performance data includes ad impressions for individual ad creatives being served to a digital property.
4. The method of claim 1 wherein the plurality of users taking the digital survey include a control group not exposed to at least some of the plurality of ad creatives.
5. The method of claim 1 further comprising:
increasing an allocation of ad creatives in the ongoing campaign flight that exhibit a pre-determined level of results.
6. The method of claim 1 further comprising:
decreasing an allocation of ad creatives in the ongoing campaign flight that fail to exhibit a pre-determined level of results.
7. A non-transitory medium holding processor-executable instructions for optimizing a digital advertising campaign, the instructions when executed causing at least one computing device to:
initiate a digital advertising campaign for an advertiser, the digital advertising campaign displaying ad creatives on one or more digital properties during an advertising campaign flight;
acquire performance data from the one or more digital properties regarding the display of the ad creatives during the campaign flight, at least some of the performance data acquired through the use of a site-specific Ad Tag;
identify one or more users that have viewed at least two ad creatives being displayed in the digital advertising campaign;
provide a digital survey during the campaign flight of the digital advertising campaign to more than one user, answers of the users to the digital survey forming a plurality of survey results;
provide the plurality of survey results and the performance data as input to a survival analysis, a Markov chain Monte Carlo simulation, a collaborative filtering and a relative importance algorithm;
calculate programmatically, via the survival analysis, the Markov chain Monte Carlo simulation, the collaborative filtering and the relative importance algorithm, a success value for at least some of the ad creatives displayed during the campaign flight for which performance data was acquired, the success value being a relative value indicative of a displayed ad creative providing an attribute previously specified by the advertiser; and
adjust an allocation of a display of the ad creatives among the plurality of digital properties based on the calculated results provided by at least some of the ad creatives.
8. The medium of claim 7 wherein at least some of the performance data is acquired through the use of a Software Development Kit or is provided by a third party.
9. The medium of claim 7 wherein the performance data includes ad impressions for individual ad creatives being served to a digital property.
10. The medium of claim 7 wherein the plurality of users taking the digital survey include a control group not exposed to at least some of the ad creatives.
11. The medium of claim 7 wherein the instructions when executed further:
increase an allocation of ad creatives in the ongoing campaign flight that exhibit a pre-determined level of results.
12. The medium of claim 7 wherein the instructions when executed further:
decrease an allocation of ad creatives in the ongoing campaign flight that fail to exhibit a pre-determined level of results.