In marketing campaigns, marketers send campaign ads to selected customers
("test group") and putting aside the
randomly selected some group of customers
("control group") from the campaign. The idea is to determine the effectiveness of the compaign by comparing the sales generated from the "
test group" and "
control group".
For example, an ecommerce website has segmented customers to send "50% discount on clothing" campaign and they send this campaign to only 50k of them (“test group”), put aside a randomly-selected 5k customers (“control group”) who will not receive it. Once the campaign is over, they will determine the effectiveness of the campaign by comparing the additional revenues generated by the test group with those generated by the control group.
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Campaign Result : Test vs. Control |
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Test vs. Control Methodology |
Total Revenue from Campaign = $1,125 + $63 = $1,187.5
Profit from Campaign = $1,187.5 - $687.5 = $500
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Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he has worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and Human Resource.
Really useful!! Thank you!
ReplyDeletea
ReplyDeleteThank you :)
ReplyDeleteWhat is this term called ??
ReplyDeleteAre their other methods to create the control group where it is not random and the control groups "looks like" the test
ReplyDeleteyou can take out stratified samples for control making sure that it has the same feature distribution as compared to the test group
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