System and method for improving the performance of electronic media advertising campaigns through multi-attribute analysis and optimization

• US 20080281627A1
• Filed: 07/25/2008
• Published: 11/13/2008
• Est. Priority Date: 12/15/2000
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.), Paramark, Inc. (Newworldiq, Inc.)
• Original Assignee: Carl Meyer
• Inventors: Weisinger, James R., Kumar, Sachin, Ranka, Sanjay, Chang, E. Diane, Chatwin, Richard E., Lenderman, Jason
• Application Number:
  US12/179,916
• Publication Number:
  US 20080281627A1
• Time in Patent Office: Days
• US Class Current: 705/1
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0243 Comparative campaigns
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

Automated system, methods, algorithms, procedures, and computer software programs and computer program products for improving and optimizing the performance of messaging campaigns, particularly for marketing campaigns in which advertisements or other messages are distributed over an interactive measurable medium such as the Internet. Analysis and Optimization method and procedure, an automated system, and system and method that exploit the underlying multi-attribute structure, as well as other features and advantages. Optimization procedures allocate the ad alternatives or other message to the customer population to optimize business objectives such as maximizing the number of positive responses received. Procedure for generating message allocations that improve and attempt to optimize the campaign performance. Methods ensure that campaign constraints are not violated. Methods can be implemented on a computer that is programmed to retrieve message performance information and to generate recommended message allocations for each stage in a multi-stage messaging campaign to achieve messaging goals.

Claims

1. A method of identifying a relative performance of a set of creatives, wherein a given creative has associated therewith two or more attributes, and each attribute has two or more values, comprising:

defining a set of multiattribute data structures and assigning the creatives to the set such that each creative is assigned to one and only one multiattribute data structure;

receiving data indicative of a performance of the creatives; and

using the performance data, estimating a set of multiattribute parameters β

^m_jk for every attribute m and pair of attribute values j and k, such that if h and i are any pair of creatives, then, identifying β

^m_jj=0 for every attribute m and attribute value j, the equation f(π

_h)−

f(π

_i)=Σ

_mβ

^m_h(m)i(m) either holds as a given or defines an expectation of a difference f(π

_h)−

f(π

_i);

wherein at least one or more of the steps are performed by one or more electronic processing devices.

2. The method as described in claim 1 wherein for any attribute values j, k, and l of a common attribute m:

β

^m_jl=β

^m_jk+β

^m_kl.

3. The method as described in claim 2 further including the step of selecting a given creative as a base, defining β

₁=f(π

₁) and β

^m_j=β

^m_j1 for all attribute values j>

1 and attributes m such that f(π

_i)=β

₁+Σ

_mβ

^m_i(m) for all creatives.

4. The method as described in claim 3 further including processing f(π

_i) into vector notation by creating column vectors f(π

), with entries f(π

_i) for each creative I, and β

, with entries β

₁ and β

^m_j for each attribute m and attribute value j>

1, such that f(π

)=Xβ

, where X is a multiattribute-mapping matrix and β

is a vector of multiattribute parameters.

5. A method of multiattribute analysis for providing automated measurements and reporting of an importance of attributes and attribute values of message alternatives, comprising:

generating a set of message alternatives, wherein each message alternative may be described in terms of the attributes and the attribute values, wherein an attribute is a component of a message alternative and an attribute value is a particular instantiation of the attribute, wherein a given message alternative includes two or more attributes each of which may be assigned two or more attribute values;

providing the message alternatives in response to requests;

determining an importance of the attributes and the attribute values to performance of the message alternatives provided in response to the requests;

providing one or more reports describing the performance of the message alternatives;

wherein at least one or more of the steps are performed by one or more electronic processing devices.

6. The method as described in claim 5 wherein the message alternatives are described in at least one multiattribute data structure.

7. The method as described in claim 5 wherein at least one report identifies a performance of a particular message alternative with respect to at least one other message alternative.

8. The method as described in claim 5 wherein at least one report identifies a performance of a particular attribute of a particular message alternative with respect to at least one other attribute of the particular message alternative.

9. The method as described in claim 5 wherein at least one report identifies a performance of a particular attribute value of an attribute of a particular message alternative with respect to at least one other attribute value of the attribute of the particular message alternative.

10. The method as described in claim 5 further including the step of using the performance data to optimize campaign performance through allocation of message alternatives during a multi-stage message campaign.

11. The method as described in claim 5 wherein a message alternative is a markup language page.

12. The method as described in claim 11 wherein the attribute is a portion of the markup language page.

13. A method of identifying a relative performance of a set of creatives, wherein a given creative has associated therewith two or more attributes, and each attribute has two or more values, comprising:

defining a set of multiattribute data structures and assigning the creatives to the set such that each creative is assigned to one and only one multiattribute data structure;

receiving data indicative of a performance of the creatives; and

using the performance data, estimating values of a set of multiattribute parameters for each of the multiattribute data structures, wherein the values of the set of multiattribute parameters define relative impact of the attribute values on performance of the creatives;

wherein at least one or more of the steps are performed by one or more electronic processing devices.

14. The method as described in claim 13 further including the step of reducing the set of multiattribute data structures to a standard form prior to the estimating step.

15. The method as described in claim 13 further including the step of processing the performance data by a given discounting function prior to the estimating step.

16. The method as described in claim 13 wherein the performance data is associated with a prior stage of a multi-stage campaign and the estimating step is carried out prior to a next stage of the multi-stage campaign.

17. The method as described in claim 13 wherein the multiattribute data structure is a collection of attributes and an attribute is a distinct element of a creative.

18. The method as described in claim 13 wherein the estimating step comprises:

selecting a first creative as a base and setting the attribute values associated with the given creative to a given value;

using a given statistical technique to estimate the values of the multiattribute parameters;

if any values of the multiattribute parameters are negative values, identifying a previously-estimated worst creative as the base and repeating the statistical technique so that the values of the multiattribute parameters are non-negative.

19. The method as described in claim 13 further including displaying a report comparing attributes in a multiattribute structure.

20. The method as described in claim 19 wherein the report identifies a relative importance of an attribute in determining a given performance metric achieved by the creative.

21. The method as described in claim 13 further including displaying a report comparing attribute values for a given attribute.

22. The method as described in claim 21 wherein the report identifies a relative importance of each attribute value in determining a given performance metric achieved by the creative.