March 2019
Beginner to intermediate
464 pages
10h 57m
English
Content preview from Hands-On Data Science for Marketing
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Engagement rates by offer type
Different types of offers will work differently for different customers. In this section, we are going to look into what types of offers worked best for the engaged customers. Take a look at the following code:
## - Engagement Rates by Offer Type ##engagementRateByOfferType <- df %>% group_by(Renew.Offer.Type) %>% summarise(Count=n(), NumEngaged=sum(Engaged)) %>% mutate(EngagementRate=NumEngaged/Count*100.0)
As you can see from this code, we are grouping by the Renew.Offer.Type column, where we have four different types of offers. Then, in the summarise function, we count the total number of records using the n() function, and we count the number of engaged customers by summing over the encoded column, Engaged ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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