An ad words ad performance analysis by r
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This document summarizes an analysis of an AdWords advertising campaign performed with R. It describes getting campaign data via the AdWords API, preparing the data by defining MySQL tables, and presenting 5 scenarios for analyzing the daily clicks, conversions, country-level clicks, comparing campaigns, and comparing campaigns to the mean. The goal is to better understand campaign performance by virtualizing the AdWords data in R.
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Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
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QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
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- Quantum Computing QRG
- Big Data Analytics QRG
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- UK Home Computing & The Birth of ARM QRG (coming 2027)
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- Please contact Arthur Morgan at [email protected].
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An ad words ad performance analysis by r
- 1. An AdWords Ad Performance Analysis by R Final project submission By Simon Chen
- 2. Background and goal AdWords, Google’s online advertising program. Try to get basic AdWords Data by API and analyze an ad campaign with R.
- 3. Definition Customer account MCC(My Client Center) account Clicks Conversions
- 4. Data Preparation A MCC’s data of customers by AdWords API https://developers.google.com/adwords/api/docs/reference/v20 1406/ManagedCustomerService
- 5. Data Preparation MCC’s daily data of all ad campaigns last month(2014/10) by AdWords API https://developers.google.com/adwords/api/docs/appendix/repo rts#campaign MCC’s daily data separated by countries last month(2014/10) by AdWords API https://developers.google.com/adwords/api/d ocs/appendix/reports#geo
- 6. Data Preparation Defined three MySQL tables to save the data above. create table CUSTOMER( id bigint not null auto_increment, name varchar(255), primary key (id) ) ENGINE=InnoDB;
- 7. Data Preparation create table DAILY_DATA( idbigint not null auto_increment, customer bigint not null, campaign_name varchar(255), data_date datetime not null, impressionsbigint, clicksbigint, ctr double precision, conversionsbigint, conv_rate double precision, cost double precision, primarykey(id) ) ENGINE=InnoDB; create table DAILY_GEO_DATA( id bigint not null auto_increment, customer bigint not null, campaign_name varchar(255), country varchar(255), data_date datetime not null, impressionsbigint, clicksbigint, ctr double precision, conversionsbigint, conv_rate double precision, cost double precision, primary key (id) ) ENGINE=InnoDB;
- 8. Scenario 1 I want to know the daily clicks of an ad campaign last month(2014/10).
- 9. Scenario 2 I want to know conversions of every day of Weeks.
- 10. Scenario 3 I want to know clicks from every country.
- 11. Scenario 4 I want to compare two similar ad campaigns.
- 12. Scenario 5 I want to compare ad campaigns with the mean.
- 13. Conclusion Virtualizing our AdWords performance data with R will help us understand the operation of ad campaigns more easily.