Utilizing R to Unlock the Power of Data

Austin Hart
Data Analyst

The field of data changes very quickly. In order to remain on the cutting edge, it is important to  expand your knowledge of the newest technology.

Now more than ever it is easy to gather massive amounts of data. To properly analyze the data collected, you need specialized tools to help keep up with the work load.

The most common choice for an effective data program is the free software environment, R. And for good reason.


Why R?

R is free, user friendly and designed for data.  It is also open source, which means that other R users across the world can contribute to improving its functionality.

With its growing popularity and continual development, R is a staple of data analysis.

What does R have to offer?

Because R is open source and continuing to gain popularity, its packages and features are being improved daily.

R especially excels in the fields of data manipulation and data visualization. Within the software, the widely-used package dplyr has changed how users manipulate data. This package can turn clunky code into fast and easy-to-understand actions such as filter, select and summarize.

And while dplyr is successful in manipulation, R's ggplot2 is unparalleled in terms of graphics creation. In this package, it is easy and seamless to turn your data into organized charts and tables.  

Like ggplot2, HTMLwidgets offers a handful of great visualization features. These packages let the user turn data into beautiful interactive features, such as maps, with just a few lines of code and no knowledge of javascript necessary. The inclusion of these packages allows for data plots to be interactive and easily incorporated on web pages.

This brings us to the last of R's awesome packages. It offers a feature known as Shiny, which allows you to create web apps that users can interact with in a user friendly interface.


How does the KennedyC team use R?

The KennedyC data pipeline starts with the collection of lead data from tracking software, website traffic data from Google Analytics and paid search data from Google Adwords. Using R, our analysts pull in the data from .csv's, or Google APIs.

Once collected, the team employs dplyr to format the data into relevant and organized tables. Using these tables, they can compute statistics relevant to clients. Like cost per lead or percent increase in traffic. The organized data is also used to create plots and graphs using ggplot2.

All of these graphics and statistics are then pumped into a powerpoint file using the package officer. Once completed, the resulting document is easy to read and full of relevant information for clients.  

As an added bonus, our process using R is completely reproducible, meaning that our analysts can create a beautiful report for each client with a simple push of a button.

In addition to the client reporting functions, we also take advantage of what Shiny has to offer. By creating an app, our data team can make the data pipeline, and many other functions, accessible to anyone in the office.

For example, at the push of a button, the paid search team can interactively visualize the geographic performance of their campaigns at the zipcode level thanks to a package called leaflet and the accessibility of Shiny web apps.


Conclusion

With a small learning curve, anyone can get into R and reap the benefits of powerful data analysis. Its possibilities are endless, and its community is strong.

In the world of data, R is quickly rising to the top. Our KennedyC data team can utilize this powerful tool to help your brand analyze massive amounts of data and use that knowledge to make informed decisions about its marketing strategy. Give us a call to learn more.