Marketing Optimization using What-If & R Linear Programming

ujwalynit — Fri, 01 Sep 2017 09:54:48 GMT

Marketing Optimization using Linear Programming

CMOs need to make complex decisions about budget allocation and marketing investment. Deciding which campaigns will receive funding is never easy, especially with multiple factors and obligations that need to be taken into account.

This dashboard helps marketing managers to optimize the 'Return on Marketing Investment' (ROMI) across four channels. TV Ads, SEO , Adwords and Facebook. Based on the set parameters and rules , the dashboard gives a R Linear Programming Solutions that optimizes the ROMI.

R Libraries used: linprog - for linear programming, grid, gridExtra,gtable - for plotting the results as a table

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Re: Marketing Optimization using What-If & R Linear Programming

ujwalynit — Wed, 08 Nov 2017 13:21:49 GMT

R Code:

my_df <- `dataset`

library(linprog)

ROI <- c(my_df$`TVROI Value`/100,my_df$`SEOROI Value`/100,my_df$`ADWORDSROI Value`/100,my_df$`FacebookROI Value`/100)
bVect <- c(my_df$`Total Budget`, 0, 0, -200000, -80000, -60000, 220000, 0, my_df$`Customer Base`)
AMatrix <- rbind(
c(1,1,1,1), # TOTAL
c(0.6,-0.4,-0.4,0.6), # SEO + AdWords > 60%
c(-0.2,-0.2,-0.2,0.8), # FB < 20%
c(-1,0,0,0), # Min TV
c(0,0,0,-1), # Min FB
c(0,-1,0,0), # Min SEO
c(0,1,0,0), # Max SEO
c(0,-3,1,0), # Adwords <= 3 SEO
c(my_df$`TV Reach Value`,my_df$`SEO Reach Value`,my_df$`Adwords Reach Value`,my_df$`Facebook Reach Value`) # Campaign reach
)

lpsol <- solveLP(ROI, bVect, AMatrix, TRUE)

OptROI <- paste0("$", formatC(as.numeric(lpsol$opt), format="f", digits=0, big.mark=","))
TVSpend <- paste0("$", formatC(as.numeric(lpsol$solution[1]), format="f", digits=0, big.mark=","))
SEOSpend <- paste0("$", formatC(as.numeric(lpsol$solution[2]), format="f", digits=0, big.mark=","))
AdwordsSpend <- paste0("$", formatC(as.numeric(lpsol$solution[3]), format="f", digits=0, big.mark=","))
FacebookSpend <- paste0("$", formatC(as.numeric(lpsol$solution[4]), format="f", digits=0, big.mark=","))

plot_df <- data.frame(Description=c('Optimum ROI','TV Spend','SEO Spend','Adwords Spend','Facebook Spend'),
Value=c(OptROI,TVSpend,SEOSpend,AdwordsSpend,FacebookSpend))

library(gtable)
library(gridExtra)
library(grid)
tt <- ttheme_minimal(
core=list(bg_params = list(fill = blues9[1:5], col=NA),
fg_params=list(fontface=1,fontsize=20)),
colhead=list(fg_params=list(col="navyblue", fontface=1,fontsize=20)))

g <- tableGrob(plot_df[1:5,], rows = NULL,theme=tt)
g <- gtable_add_grob(g,
grobs = rectGrob(gp = gpar(fill = NA, lwd = 2)),
t = 2, b = nrow(g), l = 1, r = ncol(g))
g <- gtable_add_grob(g,
grobs = rectGrob(gp = gpar(fill = NA, lwd = 2)),
t = 1, l = 1, r = ncol(g))
grid.newpage()
grid.draw(g)

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Marketing Optimization using What-If & R Linear Programming

Re: Marketing Optimization using What-If & R Linear Programming