Performing attribution modeling for arbitrary analytics parameters

Patent metadata

Field	Value
Publication number	US-11347809-B2
Application number	US-201816189784-A
Country	US
Kind code	B2
Filing date	Nov 13, 2018
Priority date	Nov 13, 2018
Publication date	May 31, 2022
Grant date	May 31, 2022

Abstract

The present disclosure relates to performing attribution modeling in real time using touchpoint data that correspond to arbitrary analytics parameters (e.g., a user-specified dimension) and are retrieved from a database using an attribution model. For example, in one or more embodiments, a system stores raw data in an analytics database that comprises an aggregator and a plurality of nodes. In particular, each node stores touchpoint data associated with a different user. Upon receiving a query, the system can, in real time, retrieve subsets of the touchpoint data that correspond to a user-specified dimension in accordance with an attribution model. The system then combines the subsets of touchpoint data using the aggregator and generates the digital attribution report using the combined data.

First claim

What is claimed is:

1. In a digital medium environment for collecting and analyzing analytics data about network communications, a method for generating digital attribution reports in real time comprising:
storing data that is received from a plurality of client devices associated with a plurality of users in an analytics database comprising an aggregator and a plurality of nodes, wherein each node corresponds to a given user and storing the data within a node comprises utilizing a processing unit of the node to store a user ID and touchpoint data associated with the given user within a data storage unit of the node;
receiving a query to generate a digital attribution report for a user-specified dimension based on an attribution model; and
in response to receiving the query and in real time:
retrieving, using nodes of the plurality of nodes, subsets of touchpoint data corresponding to the user-specified dimension in accordance with the attribution model;
combining, using the aggregator, the subsets of touchpoint data corresponding to the user-specified dimension in accordance with the attribution model;
generating the digital attribution report using the combined subsets of touchpoint data; and
providing the digital attribution report for display.

2. The method of claim 1 , wherein the user-specified dimension comprises a dimension other than distribution channels.

3. The method of claim 2 , wherein the user-specified dimension comprises at least one of internal campaigns, product finding methods, internal search terms, pages, page types, products, product types, or product brands.

4. The method of claim 1 , wherein the attribution model comprises a user-specified attribution model.

5. A non-transitory computer readable storage medium comprising instructions that, when executed by at least one processor, cause a computing device to:
store data that is received from a plurality of client devices associated with a plurality of users in an analytics database comprising an aggregator and a plurality of nodes, wherein each node corresponds to a given user and storing the data within a node comprises utilizing a processing unit of the node to store a user ID and touchpoint data associated with the given user within a data storage unit of the node;
receive a query to generate a digital attribution report for a user-specified dimension based on an attribution model; and
in response to receiving the query and in real time:
retrieve, using nodes of the plurality of nodes, subsets of touchpoint data corresponding to the user-specified dimension in accordance with the attribution model;
combine, using the aggregator, the subsets of touchpoint data corresponding to the user-specified dimension in accordance with the attribution model;
generate the digital attribution report using the combined subsets of touchpoint data; and
provide the digital attribution report for display.

6. The non-transitory computer readable storage medium of claim 5 , wherein:
the query to generate the digital attribution report for the user-specified dimension based on the attribution model comprises a user-specified event, and
the subsets of touchpoint data corresponding to the user-specified dimension retrieved in accordance with the attribution model comprise one or more touchpoints called for by the attribution model based on the user-specified event.

7. The non-transitory computer readable storage medium of claim 6 , wherein: the user-specified event is an event other than orders or revenue.

8. The non-transitory computer readable storage medium of claim 7 , wherein: the user-specified event comprises one of custom events, units, visits, cart additions, or cart removals.

9. The non-transitory computer readable storage medium of claim 5 , wherein:
an instance of touchpoint data comprises an indication of a touchpoint and a timestamp associated with the touchpoint, and
the instructions, when executed by the at least one processor, cause the computing device to store the touchpoint data in the analytics database by storing, in each node, instances of touchpoint data chronologically based on the timestamp associated with each touchpoint of a corresponding user.

10. The non-transitory computer readable storage medium of claim 5 , wherein the instructions, when executed by the at least one processor, cause the computing device to, retrieve, using the nodes of the plurality of nodes, the subsets of touchpoint data corresponding to the user-specified dimension in accordance with the attribution model by filtering, at each node, a subset of touchpoints for a corresponding user that correspond to the user-specified dimension in accordance with the attribution model.

11. The non-transitory computer readable storage medium of claim 5 , wherein the analytics database further comprises a plurality of intermediate aggregators, wherein each intermediate aggregator is associated with, and aggregates data from, a different subset of nodes of the plurality of nodes.

12. The non-transitory computer readable storage medium of claim 11 ,
further comprising instructions that, when executed by the at least one processor, cause the computing device to aggregate, using each intermediate aggregator, the subsets of touchpoint data from the subset of nodes corresponding to each intermediate aggregator to generate sets of aggregated touchpoint data,
wherein the instructions, when executed by the at least one processor, cause the computing device to combine, using the aggregator, the subsets of touchpoint data by combining the sets of aggregated touchpoint data from the plurality of intermediate aggregators.

13. The non-transitory computer readable storage medium of claim 5 , further comprising instructions that, when executed by the at least one processor, cause the computing device to:
receive a second query to generate a second digital attribution report for the user-specified dimension based on a second attribution model;
in response to receiving the second query and in real time:
retrieve, using the nodes of the plurality of nodes, second subsets of touchpoint data corresponding to the user-specified dimension in accordance with the second attribution model;
combine, using the aggregator, the second subsets of touchpoint data corresponding to the user-specified dimension in accordance with the second attribution model; and
generate the second digital attribution report using the combined second subsets of touchpoint data; and

provide the second digital attribution report for display simultaneously with the digital attribution report.

14. A system comprising:
a memory component comprising an analytics database that stores data received from a plurality of client devices associated with a plurality of users, the analytics database comprising:
an aggregator; and
a plurality of nodes, wherein each node comprises a data storage unit and a processing unit that chronologically stores touchpoint data associated with a corresponding user within the data storage unit and stores a user ID of the corresponding user within the data storage unit;

at least one server; and
at least one non-transitory computer readable storage medium comprising instructions that, when executed by the at least one server, cause the system to:
receive a query to generate a digital attribution report for a user-specified dimension based on an attribution model; and
in response to receiving the query and in real time:
send, to the plurality of nodes, a request for touchpoint data corresponding to the user-specified dimension based on the attribution model;
use the attribution model, at the

Assignees

• Adobe Inc

Inventors

• Paulsen Trevor
• Andrus Ivan
• Purser Nathan

Classifications

• G06Q30/0242

  Determining effectiveness of advertisements · CPC title

• G06F16/337

  Profile generation, learning or modification · CPC title

• G06Q30/0201 Primary

  Market modelling; Market analysis; Collecting market data · CPC title

• G06F16/35

  Clustering; Classification · CPC title

• G06F16/9038 Primary

  Presentation of query results · CPC title