Abraham Mathew

In a previous post, I discussed how to generate PPC keywords in R. In this post I will provide another example of how to perform this task. Let’s say that I am a auto insurance company that only operates in the state of Illinois. I’m planing on bidding on keywords in Bing and Google which have the name of each city in Illinois followed by ‘auto insurance.’ Using just the sprintf function and a data structure with the Illinois cities, I can generate the desired keywords using the following code. Some of you are probably wondering why an advertiser would bid on keywords that contain each city in Illinois. Well, there are very few instances in which it would make sense to actually bid on keywords that contain city names or zip codes. Just because you can, doesn’t mean you should.

DF <- read.csv("http://www.census.gov/tiger/tms/gazetteer/zips.txt",
               header = FALSE)
str(DF)
head(DF)

DF[ ,c(1,5,6,7,8)] <- NA
head(DF)
df <- DF[,colSums(is.na(DF))<nrow(DF)]  #removes all NA values
names(df) <- c("zip", "state", "city")
head(df)
il = subset(df, state=="IL")
ilcity = unique(tolower(il$city))
ilcity = as.character(ilcity)
ilcity = gsub("(^|[[:space:]])([[:alpha:]])", "\\1\\U\\2", ilcity, perl=TRUE)
ilcity
dt = c("%s auto insurance")
dat = sprintf(dt, ilcity)

Paid search marketing refers to the process of driving traffic to a website by purchasing ads on search engines. Advertisers bid on certain keywords that users might search for, and that determines when and where their ads appear. For example, an individual who owns an auto dealership would want to bid on keywords relating to automobiles that a reasonable people would search for on a search engine. In both Google and Bing, advertisers are able to specify which keywords they would like to bid for and at what amount. If the user decides to bid on just a small number of keywords, they can type that information and specify a bid. However, what if you want to bid on a significant number of keywords. Instead of typing each and every keyword into the Google or Bing dashboard, you could programmatically generate the keywords in R.

Let’s say that I run an online retail establishment that sells mens and womens streetwear and I want to drive more traffic to my online store by placing ads on both Google and Bing. I want to bid on about a number of keywords related to fashion and have created a number of ‘root’ words that will comprise the majority of these keywords. To generate my desired keywords, I have a written a function which will take every single permutation of the root words.

root1 = c("fashion", "streetwear")
root2 = c("karmaloop", "crooks and castles", "swag")
root3 = c("urban clothing", "fitted hats", "snapbacks")
root4 = c("best", "authentic", "low cost") 

myfunc <- function(){
      lst <- list(root1=c(root1), root2=c(root2), root3=c(root3),
            root4=c(root4))
      myone <- function(x, y){
            m1 <- do.call(paste, expand.grid(lst[[x]], lst[[y]]))
            mydf <- data.frame(keyword=c(m1))
      }
      mydf <- rbind(myone("root4","root1"), myone("root2","root1"))
      }

mydat <- myfunc()
mydat

write.table(mydat, "adppc.txt", quote=FALSE, row.names=FALSE)

This isn’t the prettiest code in the world, but it gets the job done. In fact, the same results could have achieved using the following code, which is much more efficient.

root5 = c("%s fashion")
root6 = c("%s streetwear")
adcam1 = sprintf(root5, root2)
adcam2 = sprintf(root6, root2)
df = data.frame(keywords=c(adcam1, adcam2))

write.table(df, "adppc.txt", quote=FALSE, row.names=FALSE)

If you have any suggestions for improving my R code, please mention it in the comment section below.