Using Alteryx to Blend Historical Social Data

[DanielleR]

Author:

Jennifer Jensen

Role:

Sr. Analyst

Company:

McGarrybowen

Collaborators:

Inna Meerovich, RJ Summers

Using Alteryx to Blend Historical Social Data

Originally Published: 2016 Excellence Awards Entry

Use Case Overview:

mcgarrybowen is a creative advertising agency that is in the transformation business. From the beginning, mcgarrybowen was built differently, on the simple premise that clients deserve better. So we built a company committed to delivering just that. A company that believes, with every fiber of its being, that it exists to serve clients, build brands, and grow businesses.

Describe the problem you needed to solve:

Mcgarrybowen creates hundreds of pieces of social creative per year for Fortune 500 CPG and Healthcare brands, on platforms including Facebook and Twitter. The social media landscape is constantly evolving especially with the introduction of video, a governing mobile-first mindset, and interactive ad units like carousels, but yet the capabilities for measuring performance on the platforms have not followed as closely.

Our clients constantly want to know, what creative is the most effective, drives the highest engagement rates, and the most efficient delivery? What time of day, day of week is best for posting content? What copy and creative works best? On other brands you manage, what learnings have you had?

But, therein lies the challenge. Answers to these questions aren’t readily available in the platforms, which export Post-Level data in raw spreadsheets with many tabs of information. Both Facebook and Twitter can only export 90 days of data at a time. So, to look at client performance over longer periods of time and compared to their respective categories, and derive performance insights that drive cyclical improvements in creative – we turned to Alteryx.

Describe the working solution:

Our Marketing Science team first created Alteryx workflows that blended multiple quarters and spreadsheet tabs of social data for each individual client. The goal was to take many files over several years that each contained many tabs of information, and organize it onto one single spreadsheet so that it was easily visualized and manipulated within Excel and Tableau for client-level understanding. In Alteryx, it is easy to filter out all of the unnecessary data in order to focus on the KPIs that will help drive the success of the campaigns. We used “Post ID,” or each post’s unique identifying number, as a unifier for all of the data coming in from all tabs, so all data associated with a single Facebook post was organized onto a single row. After all of the inputs, the data was then able to be exported onto a single tab within Excel.

After each client’s data was cleansed and placed into a single Excel file, another workflow was made that combined every client’s individual data export into a master file that contained all data for all brands. From this, we can easily track performance over time, create client and vertical-specific benchmarks, and report on data efficiently and effectively.

Single Client Workflow

Multi-Client Workflow

Describe the benefits you have achieved:

Without Alteryx, it would take countless hours to manually work with the social data in 90 day increments and manipulate the data within Excel to mimic what the Alteryx workflow export does in seconds. With all of the saved time, we are able to spend more time on the analysis of these social campaigns. Since we are able to put more time into thoughtful analysis, client satisfaction with deeper learnings has grown exponentially. Not only do we report out on past performance, but we can look toward the future and more real-time information to better analyze and optimize.