Yield optimization of cross-screen advertising placement
The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system permits targeting of advertising content to consumers on TV and mobile devices that can be operated from within a multi-channel video programming distributor's environment. The system is able to use hard and soft constraints to come up with a number of possible targets for an advertising campaign and can then provide tools for optimizing those targets. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which a user can adjust various constraints and optimize a distributor's revenue yield from advertising.
1. A method of optimizing revenue for allocation of advertising content, the method comprising:
matching advertising campaign descriptions with advertising inventory for a plurality of digital advertising slots, wherein the inventory is relevant to a target demographic defined by consumer data from cross-screen viewing behavior and device information about a first set of digital devices associated with a first consumer and a second set of digital devices associated with a second consumer, wherein the matching is subject to one or more hard constraints, thereby producing two or more advertising targets;
calculating iteratively the possible revenue from allocating the advertising content across the two or more advertising targets, subject to a plurality of soft constraints; and
providing an advertiser with an optimal advertising target, wherein providing the advertiser with the optimal advertising target includes targeting the first consumer to receive an item of advertising content in at least one advertising slot in the plurality of digital advertising slots.
2. The method of claim 1 , wherein providing the advertiser with the optimal advertising target includes providing an indication of a digital advertising yield that is optimized via segmentation and demand pairing.
3. A method for optimizing allocation of video advertising content, the method comprising:
receiving a pricepoint and one or more campaign descriptions from an advertiser, wherein each of the campaign descriptions comprises a schedule for delivery of an item of advertising content across two or more digital devices, one or more hard constraints, and a target audience, wherein the target audience is defined by one or more demographic factors;
identifying device information about a first set of digital devices associated with a first consumer and a second set of digital devices associated with a second consumer;
defining a pool of consumers based on the device information about the first set of digital devices and the second set of digital devices, demographic and online behavioral data on each consumer of the pool of consumers, and similarities between the consumers of the pool of consumers, and wherein the pool of consumers comprises consumers having at least a threshold similarity to a member of the target audience;
identifying one or more advertising targets, wherein each of the one or more advertising targets comprises a sequence of slots in electronic advertising inventory consistent with one or more of the campaign descriptions and the one or more hard constraints, and has an overall cost consistent with the pricepoint;
identifying a consumer identifier that links two of more devices of a particular consumer of the pool of consumers;
carrying out an optimization of allocation of the advertising content of the one or more campaign descriptions to the one or more advertising targets based on one or more soft constraints, thereby producing a list of one or more solutions, ranked according to their likely advertising revenue yield, wherein a solution comprises a match of the campaign description to the sequence of slots in the electronic advertising inventory as likely to be viewed by the pool of consumers, wherein execution of the campaign includes targeting the particular consumer and selecting at least one of the two of more devices of the particular consumer to receive the item of advertising content in the sequence of slots; and
communicating the list of one or more solutions to the advertiser.
4. The method of claim 3 , wherein the hard constraints comprise one or more of: regulatory requirements and restrictions imposed by the advertiser.
5. The method of claim 3 , wherein the soft constraints comprise one or more advertiser preferences.
6. The method of claim 3 , performed by a multi-channel video programming distributor.
7. The method of claim 3 , wherein the optimization of allocation is an iterative process.
8. The method of claim 3 , wherein the optimization of allocation is an interactive process.
9. A computer system comprising a processor configured to execute instructions for performing the method of claim 3 .
10. A non-transitory computer-readable medium encoded with instructions for causing a computer system to perform the method of claim 3 .
11. The method of claim 3 , wherein carrying out the optimization of allocation of the advertising content of the one or more campaign descriptions includes:
running a plurality of simulations of matching advertising campaigns with inventory slots; and
providing at least one result of the plurality of simulations that will result in an amount of advertising revenue that is above a threshold revenue amount.
12. The method of claim 11 , wherein the plurality of simulations are run in an environment that is isolated from one or more external inputs.
13. The method of claim 11 , wherein running the plurality of simulations of matching advertising campaigns with inventory slots includes:
identifying data relating to advertising campaign details and advertising copy details;
identifying data variables and restrictions for the advertising inventories subject to a revenue optimization model; and
producing an output to show the campaigns and advertising copies that meet the one or more hard constraints.
14. The method of claim 13 , wherein the data relating to advertising campaign details and advertising copy details includes at least one regulated broadcasting restriction code.
15. The method of claim 13 , wherein running the plurality of simulations of matching advertising campaigns with inventory slots further includes:
integrating at least one user-selected weights to campaign completion, targeting, and priorities for a variety of campaigns.
16. The method of claim 13 , wherein running the plurality of simulations of matching advertising campaigns with inventory slots further includes filtering out any advertisements that do not meet the one or more hard constraints.
17. The method of claim 3 , wherein carrying out the optimization of allocation of the advertising content of the one or more campaign descriptions includes:
comparing a set of user data for the first consumer to at least one other set of data for a member of a particular market segment.
18. The method of claim 17 , wherein the first consumer and the member of the particular market segment are both associated with a same market segment.
19. The method of claim 17 , wherein carrying out the optimization of allocation of the advertising content of the one or more campaign descriptions includes:
identifying a similar behavior for the first consumer and the member of the particular market segment;
determining a granular difference between the first consumer and the member of the particular market segment; and
determining how the granular difference between the first consumer and the member of the particular market segment affects an advertising performance.