In this tutorial, we analyze the retail expansion strategy for In-N-Out Burger using R.

In this tutorial, we analyze the retail expansion strategy for In-N-Out Burger using R.

In this tutorial, we evaluate retail store locations using real-world city data. The analysis includes median household income, population, and competitor count.

Taylor Swift encourages people to vote in the Presidential election during her #VMAs speech: “If you’re over 18 please register to vote for something else that is important — the Presidential election.” The Tweet had millions of likes and retweets. Did Taylor Swift’s endorsement of Kamala Harris spark a rise in 'register to vote' searches in key swing regions?

Taylor Swift encourages people to vote in the Presidential election during her #VMAs speech: “If you’re over 18 please register to vote for something else that is important — the Presidential election.”

Taylor Swift encourages people to vote in the Presidential election during her #VMAs speech: “If you’re over 18 please register to vote for something else that is important — the Presidential election.”

data source:bls.gov

Data:https://www.bls.gov/web/laus/laumstrk.htm

Data source: www.bls.gov

Estimated time to download data manually and build a map - more than 10 mins if you were to use Tableau (see the example here: https://public.tableau.com/app/profile/zhenning.xu/viz/Solar_search/Sheet1) Estimated time to scrape Google Trends data and build a customized map to show two layers of information using R - 30 seconds to 1 min

This updated map uses a customized function and shows both the state names and the values for each location.

Interactive mapping with labels

The assessment report is created for free using R, RStudio, and Plotly. R is extremely useful when it comes to documentation. There are definitely many other choices available. However, using R may allow us to save time for future assessments. Some results are included for documentation purposes. It is recommended that you read the graphs and the descriptions only.

Amazon 2nd

My 3rd week lab submission.

This Christmas tree is designed using the ggplot2 package available in R.

This calendar is made using the package "calendR". See the tutorial here:https://r-coder.com/calendar-plot-r/

MKTG4000, csub

Kmeans clustering using the dataset consumer_segmentation.csv

For the BPA Faculty research symposium on Feb 28, 2020

For the BPA Faculty research symposium on Feb 28, 2020

For the BPA Faculty research symposium on Feb 28, 2020

For the BPA Faculty research symposium on Feb 28, 2020

The goal of this project is to create a dashboard (app) to provide an interface that can be used to make predictions based on natural language processing algorithms. This slide deck consists of slides pitching the algorithm and the app.

Playing basketball is my hobby. I enjoy playing it even though I am not good at it at all! Watching NBA games is a luxury for me.However, valuing player’s performance predicting a future star seems to be pretty interesting! The goal of this case analysis is to present a solution to scrap NBA data and to analyze using basic viausaliation techniques. Which player has the best performance? I just found something very counterintuitive!!! Will do some more analysis when I have some free time this summer!

It is tough to make good predictions. The numerous factors or variables, independent and dependent, involved in many sporting events contribute to the unpredictability. However, using carefully-selected variables, it is still possible to make marketing promotions more accountable. The goal of this case study is to analyze if bobblehead promotions increase attendance at Dodgers home games. Using the fitted predictive model we can predict the attendance for the game in the forthcomming season and we can predict the attendance with or without bobblehead promotion.

This YouTube video event is designed to challenge undergraduate students to interview a marketing manager or promote a new idea or a product. This year, we got 4 YouTube video submissions. Among them, three are from Jimmy Xu's Intro to Marketing class, and one is from Professor Carl Blue’s Technology Management class.

In this tutorial, I introduce the tool by accessing it directly through a web browser to extract data and analyze it in R.  In particular, the main package used will be “gtrendsR” (intro to this package available at https://github.com/PMassicotte/gtrendsR)