Methods and systems for determining user engagement based on user interactions during different advertisement slots

Patent metadata

Field	Value
Publication number	US-10051326-B2
Application number	US-201615391660-A
Country	US
Kind code	B2
Filing date	Dec 27, 2016
Priority date	Dec 27, 2016
Publication date	Aug 14, 2018
Grant date	Aug 14, 2018

Abstract

Systems and methods are described herein for determining a level of user engagement based on user interactions. A media guidance application is configured to retrieve a first record of a first plurality of user inputs, including input type, received during a first advertisement slot. A second advertisement slot, that overlaps the first advertisement slot, is selected and second record of a second plurality of user inputs received during the second advertisement slot, including input type, is retrieved. A level of user engagement for the first advertisement slot is determined based on the comparison between the first record and the second record.

First claim

What is claimed is:

1. A method for determining user engagement based on user interactions, the method comprising:
selecting a first advertisement slot, wherein the first advertisement slot has a first start time and a first end time;
retrieving a first record of a first plurality of user inputs from a first plurality of users received during the first advertisement slot, wherein the first record indicates an input type for each of the first plurality of user inputs;
selecting a second advertisement slot, wherein the second advertisement slot has a second start time and a second end time, and wherein at least one of the second start time and the second end time falls between the first start time and the first end time;
retrieving a second record of a second plurality of user inputs from a second plurality of users received during the second advertisement slot, wherein the second record indicates an input type for each of the second plurality of user inputs;
determining a first frequency of each input type of the first plurality of user inputs during the first advertisement slot;
determining a second frequency of each input type of the second plurality of user inputs during the second advertisement slot;
generating a first metric that describes the first frequency of each input type of the first plurality of user inputs during the first advertisement slot;
generating a second metric that describes the second frequency of each input type of the second plurality of user inputs during the second advertisement slot;
assigning to the first advertisement slot the first metric and to the second advertisement slot the second metric; and
determining a level of user engagement for the first advertisement slot based on the first metric and the second metric by:
comparing the first frequency of each input type in the first plurality of user inputs with a corresponding second frequency of each input type in the second plurality of user inputs;
calculating respective percent differences between the first frequency of each input type in the first plurality of user inputs and the corresponding second frequency in the second plurality of user inputs; and
determining the level of user engagement for the first advertisement slot based on the respective percent differences.

2. The method of claim 1 , further comprising:
receiving, from a user, the first plurality of user inputs, wherein each user input in the first plurality of user inputs comprises an identification code;
transmitting, to a database, a plurality of queries requesting an input type for each input in the first plurality of user inputs, wherein each query in the plurality of queries includes a respective identification code for each input in the first plurality of user inputs;
receiving, from the database, a respective input type for each input in the first plurality of user inputs; and
storing for each input in the first plurality of user inputs an associated input type.

3. The method of claim 1 , wherein determining the first frequency of each input type of the first plurality of user inputs during the first advertisement slot comprises:
identifying, for the first plurality of user inputs, a plurality of different input types;
iterating, for each input type in the plurality of different input types, through the first plurality of user inputs; and
updating a respective frequency count for each input type in the plurality of different input types when an input of the first plurality of user inputs matches a respective input type.

4. The method of claim 1 , wherein generating the first metric that describes the first frequency of each input type of the first plurality of user inputs during the first advertisement slot comprises generating a vector comprising a data structure that includes a plurality of different input types and a corresponding frequency of user inputs for each input type of the plurality of different input types.

5. The method of claim 1 , further comprising:
determining that one or more users of the first plurality of users are disregarding media content during the first advertisement slot; and
in response to the determining, updating the first metric with an amount of time that the one or more users have been disregarding the media content.

6. The method of claim 1 , wherein selecting a second advertisement slot comprises:
identifying a plurality of advertisement slots, wherein at least one of the second start time and the second end time falls between the first start time and the first end time;
determining a respective product category associated with each advertisement slot of the plurality of advertisement slots;
comparing a product category associated with the first advertisement slot with the respective product category associated with each advertisement slot of the plurality of advertisement slots; and
selecting the second advertisement slot based on the comparing.

7. The method of claim 1 , wherein assigning the first advertisement slot the first metric and the second advertisement slot the second metric comprises:
generating a data structure for storing the first metric, wherein the data structure includes a first field for each input type associated with the first metric and a second field for a frequency corresponding to a respective input type that is associated with the first metric; and
storing with metadata associated with the first advertisement slot a link to the data structure.

8. The method of claim 1 , wherein the first plurality of users and the second plurality of users share a common characteristic.

9. The method of claim 8 , wherein the common characteristic is based on at least one of demographics and media content preferences.

10. A system for determining user engagement based on user interactions, the system comprising:
control circuitry configured to:
select a first advertisement slot, wherein the first advertisement slot has a first start time and a first end time;
retrieve a first record of a first plurality of user inputs from a first plurality of users received during the first advertisement slot, wherein the first record indicates an input type for each of the first plurality of user inputs;
select a second advertisement slot, wherein the second advertisement slot has a second start time and a second end time, and wherein at least one of the second start time and the second end time falls between the first start time and the first end time;
retrieve a second record of a second plurality of user inputs from a second plurality of users received during the second advertisement slot, wherein the second record indicates an input type for each of the second plurality of user inputs;
determine a first frequency of each input type of the first plurality of user inputs during the first advertisement slot;
determine a second frequency of each input type of the second plurality of user inputs during the second advertisement slot;
generate a first metric that describes the first frequency of each input type of the first plurality of user inputs during the first advertisement slot;
generate a second metric that describes the second frequency of each input type of the second plurality of user inputs during the second advertisement slot;
assign to the first advertisement slot the first metric and to the second advertisement slot the second metric; and
determine a level of user engagement for the first advertisement slot based on the first metric and the second metric by:
comparing the first frequency of each input type in the first plurality of user inputs with a corresponding second frequency of each input type in the second plurality of user inputs;
calculating respective percent dif

Assignees

• Rovi Guides Inc

Inventors

• Maughan Benjamin H
• Stathacopoulos Paul
• Matthews Sean

Classifications

• H04N21/4532

  involving end-user characteristics, e.g. viewer profile, preferences (monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18) · CPC title

• H04N21/8455

  involving pointers to the content, e.g. pointers to the I-frames of the video stream · CPC title

• H04N21/25883

  being end-user demographical data, e.g. age, family status or address (arrangements for identifying locations of users in broadcast systems H04H60/52) · CPC title

• H04N21/812

  involving advertisement data (advertising per se G06Q30/02) · CPC title

• H04N21/4667 Primary

  Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections · CPC title