# US 2022/0284451 A1 · Methods and apparatus for electronic mapping of customer data

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- Number: US 2022/0284451 A1
- Document ID: US20220284451A1
- Status: Published application
- Kind: A1
- Application number: 17/192,806
- Filed: 2021-03-04
- Published: 2022-09-08
- Earliest claimed: 2021-03-04
- Assignees: Walmart Apollo, LLC
- Applicants: Walmart Apollo, LLC
- Inventors: Dong Xu; Peng Yang
- Web page: https://patentgrep.com/patent/US20220284451A1

## CPC

- G06Q 30/0201: Market modelling; Market analysis; Collecting market data
- G06F 16/215: Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
- G06F 16/219: {Managing data history or versioning (querying versioned data G06F16/2474; querying temporal data G06F16/2477)}
- G06F 16/2477: {Temporal data queries}
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

This application relates to apparatus and methods for mapping identifiers to customer data over temporal intervals. Various applications may then operate on the mapped customer data to generate output data, such as digital item advertisements. In some examples, a computing device receives a first identifier of a first type, and a plurality of second identifiers of a second type. The computing device obtains customer data, such as sales and browsing data, associated with each of the second identifiers, and generates a confidence score for each of the second identifiers based on the corresponding customer data. Further, the computing device generates mapping data that maps the first identifier to one of the plurality of second identifiers based on the confidence scores. In some examples, the computing device determines the mapping data based on temporal intervals associated with the first identifier and each of the plurality of second identifiers.

## Claims

### Claim 1

A system comprising:
a database; and
a computing device communicatively coupled to the database and configured to:
receive a first identifier of a first type, and a plurality of second identifiers of a second type;
determine customer data associated with each of the plurality of second identifiers of the second type;
generate a confidence score for each of the plurality of second identifiers based on each second identifier's corresponding customer data;
determine that the confidence score is beyond a threshold;
in response to determining that the confidence score is beyond the threshold, generate mapping data that maps the first identifier to one of the plurality of second identifiers based on the confidence scores; and
store the mapping data within the database.

### Claim 2 (depends on 1)

The system of claim 1, wherein generating the confidence score further comprises:
generating a session confidence score based on corresponding customer data characterizing session data;
generating a sales confidence score based on corresponding customer data characterizing sales data; and
generating the confidence score based on the session confidence score and the sales confidence score.

### Claim 3 (depends on 2)

The system of claim 2, wherein generating the confidence score further comprises:
determining, based on the customer data, a length of time from when activity associated with each of the plurality of second identifiers was first captured to when activity associated with each of the plurality of second identifiers was last captured;
generating an active period score based on the length of time; and
generating the confidence score based on the active period score.

### Claim 4 (depends on 2)

The system of claim 2, wherein generating the confidence score further comprises:
determining, based on the customer data, a length of time since activity associated with each of the plurality of second identifiers was last captured;
generating a recent activity score based on the length of time; and
generating the confidence score based on the recent activity score.

### Claim 5 (depends on 2)

The system of claim 2, wherein generating the confidence score further comprises:
applying a first weight to the session confidence score;
applying a second weight to the sales confidence score; and
generating the confidence score based on the weighted session confidence score and the weighted sales confidence score.

### Claim 6 (depends on 1)

The system of claim 1, wherein the computing device is further configured to determine a temporal interval of the customer data associated with each of the plurality of second identifiers of the second type, wherein the mapping data is generated based on the temporal intervals.

### Claim 7 (depends on 6)

The system of claim 6, wherein the plurality of second identifiers comprises a first value and a second value, wherein the computing device is further configured to determine that a temporal interval of the first value ends before a temporal interval of the second value.

### Claim 8 (depends on 6)

The system of claim 6, wherein the plurality of second identifiers comprises a first value and a second value, wherein the computing device is further configured to determine that a temporal interval of the first value includes a temporal interval of the second value.

### Claim 9

A method by a computing device comprising:
receiving a first identifier of a first type, and a plurality of second identifiers of a second type;
determining customer data associated with each of the plurality of second identifiers of the second type;
generating a confidence score for each of the plurality of second identifiers based on each second identifier's corresponding customer data;
determining that the confidence score is beyond a threshold;
in response to determining that the confidence score is beyond the threshold, generating mapping data that maps the first identifier to one of the plurality of second identifiers based on the confidence scores; and
storing the mapping data within a database.

### Claim 10 (depends on 9)

The method of claim 9 further comprising:
generating a session confidence score based on corresponding customer data characterizing session data;
generating a sales confidence score based on corresponding customer data characterizing sales data; and
generating the confidence score based on the session confidence score and the sales confidence score.

### Claim 11 (depends on 10)

The method of claim 10 further comprising:
determining, based on the customer data, a length of time from when activity associated with each of the plurality of second identifiers was first captured to when activity associated with each of the plurality of second identifiers was last captured;
generating an active period score based on the length of time; and
generating the confidence score based on the active period score.

### Claim 12 (depends on 10)

The method of claim 10 further comprising:
determining, based on the customer data, a length of time since activity associated with each of the plurality of second identifiers was last captured;
generating a recent activity score based on the length of time; and
generating the confidence score based on the recent activity score.

### Claim 13 (depends on 10)

The method of claim 10 further comprising:
applying a first weight to the session confidence score;
applying a second weight to the sales confidence score; and
generating the confidence score based on the weighted session confidence score and the weighted sales confidence score.

### Claim 14 (depends on 10)

The method of claim 10 further comprising determine a temporal interval of the customer data associated with each of the plurality of second identifiers of the second type, wherein the mapping data is generated based on the temporal intervals.

### Claim 15 (depends on 14)

The method of claim 14 wherein the plurality of second identifiers comprises a first value and a second value, the method further comprising determining that a temporal interval of the first value ends before a temporal interval of the second value.

### Claim 16 (depends on 14)

The method of claim 14 wherein the plurality of second identifiers comprises a first value and a second value, the method further comprising determining that a temporal interval of the first value includes a temporal interval of the second value.

### Claim 17

A non-transitory computer readable medium having instructions stored thereon, wherein the instructions, when executed by at least one processor, cause a device to perform operations comprising:
receiving a first identifier of a first type, and a plurality of second identifiers of a second type;
determining customer data associated with each of the plurality of second identifiers of the second type;
generating a confidence score for each of the plurality of second identifiers based on each second identifier's corresponding customer data;
determining that the confidence score is beyond a threshold;
in response to determining that the confidence score is beyond the threshold, generating mapping data that maps the first identifier to one of the plurality of second identifiers based on the confidence scores; and
storing the mapping data within a database.

### Claim 18 (depends on 17)

The non-transitory computer readable medium of claim 17, further comprising instructions stored thereon that, when executed by the at least one processor, further cause the device to perform operations comprising:
generating a session confidence score based on corresponding customer data characterizing session data;
generating a sales confidence score based on corresponding customer data characterizing sales data; and
generating the confidence score based on the session confidence score and the sales confidence score.

### Claim 19 (depends on 17)

The non-transitory computer readable medium of claim 17, further comprising instructions stored thereon that, when executed by the at least one processor, further cause the device to perform operations comprising:
determining, based on the customer data, a length of time from when activity associated with each of the plurality of second identifiers was first captured to when activity associated with each of the plurality of second identifiers was last captured;
generating an active period score based on the length of time; and
generating the confidence score based on the active period score.

### Claim 20 (depends on 17)

The non-transitory computer readable medium of claim 17, further comprising instructions stored thereon that, when executed by the at least one processor, further cause the device to perform operations comprising:
determining, based on the customer data, a length of time from when activity associated with each of the plurality of second identifiers was first captured to when activity associated with each of the plurality of second identifiers was last captured;
generating an active period score based on the length of time; and
generating the confidence score based on the active period score.