Systems and methods for predicting occurrences of consumers returning purchased devices

Patent metadata

Field	Value
Publication number	US-9852433-B2
Application number	US-201313923605-A
Country	US
Kind code	B2
Filing date	Jun 21, 2013
Priority date	May 8, 2013
Publication date	Dec 26, 2017
Grant date	Dec 26, 2017

Abstract

Systems and methods are provided for reducing consumer electronic device returns. According to various aspects, a server receives ( 505 ) usage data of an electronic communication device by a consumer. The server examines ( 510 ) existing usage indicating correlations between various usage factors of additional devices and return incidents of the additional devices, and calculates ( 515 ) individual probabilities of return for the various usage factors and a total probability of return for the electronic communication device. In embodiments, if any of the individual probabilities or the total probability meets or exceeds a threshold probability, the server contacts ( 535 ) at least one of the electronic communication device or the consumer.

First claim

The invention claimed is:

1. A computerized method in a server device for predicting device return, the method comprising:
retrieving, from memory, a set of device data associated with each of a plurality of electronic communication devices belonging to a plurality of consumers, each of the set of device data including (i) usage factors of the corresponding electronic communication device, and (ii) whether a return incident occurred for the corresponding electronic communication device;
correlating, by a processor as a set of stored correlations, the return incidents of the plurality of electronic communication devices to a portion of the usage factors of the plurality of electronic communication devices;
calculating, based on the set of stored correlations, a set of coefficients respectively associated with the portion of the usage factors;
receiving, from an electronic communication device belonging to a consumer different from the plurality of consumers, a usage data set associated with usage of the electronic communication device by the consumer;
identifying, from a first portion of the usage data set a first usage factor of the portion of the usage factors correlated to the return incidents of the plurality of electronic communication devices;
identifying, from a second portion of the usage data set, a second usage factor of the portion of the usage factors correlated to the return incidents of the plurality of electronic communication devices;
calculating (i) a first individual return probability for the first usage factor based on the first portion of the usage data set and a first coefficient of the set of coefficients associated with the first usage factor, and (ii) a second individual return probability for the second usage factor based on the second portion of the usage data set and a second coefficient of the set of coefficients associated with the second usage factor;
calculating, based on the first individual return probability and the second individual return probability, a probability that the consumer will return the electronic communication device;
determining that the probability is greater than a threshold probability; and
in response to determining that the probability is greater than the threshold probability, remotely installing software code on the electronic communication device, wherein the software code comprises an upgrade or an update patch.

2. The method of claim 1 , further comprising:
determining that the consumer did not return the electronic communication device; and
updating the set of stored correlations to reflect that contacting the consumer resulted in the consumer not returning the electronic device.

3. The method of claim 1 , wherein the usage data indicates at least one of:
battery charging activity, radio power drain, display power drain, call frequency, data transfer rate, processor activity, email server connection attempts, software application activity, idle time, region information, model information, or build information.

4. A server device for predicting device return, the server device comprising:
a communication module configured to communicate with electronic devices via at least one network connection;
a memory storing (i) a set of computer-executable instructions, and (ii) a set of device data associated with each of a plurality of electronic communication devices belonging to a plurality of consumers, each of the set of device data including (i) usage factors of the corresponding electronic communication device, and (ii) whether a return incident occurred for the corresponding electronic communication device; and
a processor interfacing with the communication module and the memory, and configured to execute the computer-executable instructions to cause the processor to:
correlate, as a set of stored correlations, the return incidents of the plurality of electronic communication devices to a portion of the usage factors of the plurality of electronic communication devices,
calculate, based on the set of stored correlations, a set of coefficients respectively associated with the portion of the usage factors,
receive, via the communication module from an electronic communication device belonging to a consumer different from the plurality of consumers, a usage data set associated with usage of the electronic communication device by the consumer,
identify, from a first portion of the usage data set, a first usage factor of the portion of the usage factors correlated to the return incidents of the plurality of electronic communication devices,
identify, from a second portion of the usage data set, a second usage factor of the portion of the usage factors correlated to the return incidents of the plurality of electronic communication devices,
calculate (i) a first individual return probability for the first usage factor based on the first portion of the usage data set and a first coefficient of the set of coefficients associated with the first usage factor, and (ii) a second individual return probability for the second usage factor based on the second portion of the usage data set and a second coefficient of the set of coefficients associated with the second usage factor,
calculate, based on the first individual return probability and the second individual return probability, a probability that the consumer will return the electronic communication device,
determine that the probability is greater than a threshold probability, and
in response to determining that the probability is greater than the threshold probability, remotely install software code on the electronic communication device via the communication module, wherein the software code comprises an upgrade or an update patch.

5. The server device of claim 4 , wherein to calculate the first individual return probability, the processor is configured to multiply (1) data associated with the first portion of the usage data set with (2) the first coefficient associated with the first usage factor.

6. The server device of claim 4 , wherein the processor is further configured to execute the computer-executable instructions to further cause the processor to:
identify recurrences of the usage factors in the set of device data, and
update the set of coefficients respectively associated with the portion of the usage factors based on the recurrences.

7. The server device of claim 4 , further comprising:
a user interface;
wherein the processor is further configured to execute the computer-executable instructions to further cause the processor to:
cause the user interface to present a graphical representation of the probability.

8. The server device of claim 4 , wherein to correlate the return incidents, the processor is configured to:
identify at least one of the usage factors as associated with at least some of the return incidents.

Assignees

• Motorola Mobility Llc
• Google Technology Holdings LLC

Inventors

• Patel Neal H
• Varian Hal R
• Oldham Jeffrey D

Classifications

• G06Q30/016

  After-sales · CPC title

• G06Q30/014

  Providing recall services for goods or products · CPC title

• G06Q10/0837

  Return transactions · CPC title

• G06Q10/06375

  Prediction of business process outcome or impact based on a proposed change · CPC title

• G06Q30/0201 Primary

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