SEO Skunkworks @ Uber

[Updated] US firearm sales in 2020

My original exploratory analysis on the topic can be found at Firearm Sales: How are Americans coping with 2020? This post is a quick #rstats follow-up to visualize the final tally for 2020 data. Load libraries library(tidyverse) library(lubridate) library(scales) Download & parse data df_raw <- read_csv("") df <- df_raw df_clean <- df %>% filter(month >= "2016-01" & month < "2021-01") %>% select(month, state, handgun, long_gun) %>% arrange((month)) %>% mutate(month = as....

March 5, 2021 · Christopher Yee

Visualizing FB spend: image vs video creative

Objective: plot the comparison of total Facebook spend between image and video creatives for a small sample of DTC brands. The original piece without any visualization (e.g. tabulated data) can be found here but the main takeaway: Though it can be tempting to go all in on video assets, I intend to use this data as added inspiration to continue investing in and testing Images. Load modules import pandas as pd import numpy as np import matplotlib....

February 10, 2021 · Christopher Yee

10 Lessons Learned from 10 Years of Search Marketing

July 2020 marked the 10 year anniversary for my blog. If you asked me a decade ago what I would be blogging about now my answer would be SEO. I never would have guessed it would shift to data science and data visualization topics. To end this chaotic year on a high note I want to share the top 10 things I learned over the course of my career in search engine marketing....

December 31, 2020 · Christopher Yee

2020 US Elections: calculating win thresholds

The 2020 US presidential election is coming down to the wire and I thought it would be fun to share how I calculate the answer to the following question: What is the distribution of the remaining ballots that Biden/Trump needs to win the electoral college votes for a given state? If we join this data point with Biden vs Trump mail-in ballot rates, or any other information for that matter, then it returns a fairly decent estimate on how thin/wide the margins will be for the US presidential race....

November 6, 2020 · Christopher Yee

From deterministic to probabilistic SEM bid optimization

The goal of every search engine marketing (SEM) advertiser is to maximize their returns at the lowest possible cost. Campaign performance is primarily tuned by adjusting the maximum cost per click (CPC) bid for each ad. However, finding the “perfect” CPC bid can be a moving target since the auction is constantly in flux. The “sleeper” problem Imagine an extreme (but likely) scenario where ad spend is significantly over the allocated budget for the month....

October 1, 2020 · Christopher Yee