Managing Molio’s Viral Data

The Client

Molio is a content creation, media campaign management, and analytics firm based in Salt Lake City. Since its inception, Molio has consistently developed several successful campaigns (including the wildly successful viral campaigns for Orabrush and Poo-Pourri) and has received accolades and awards from all over the ad industry.

To consistently crank out winning campaigns, Molio uses YouTube to rapidly test and refine content. Eventually, the campaign is expanded onto other platforms, such as other websites and TV, where it continues to be fine-tuned based on feedback from viewers. This agile method of content development, deemed “Reverse Marketing” by Molio, significantly reduces risk and exponentially boosts ad efficacy.

 

The Problem

As its business expanded, Molio began experiencing serious growing pains in the form of data management issues.

As it distributed to more websites and TV stations, managing and analyzing data became significantly more challenging. Most platforms did not offer the same in-depth analytics provided by YouTube and usually provided disparate data formats.

These problems limited Molio’s ability to quickly respond to consumer feedback and threatened to cripple Molio’s entire Reverse Marketing strategy. With Molio’s growing list of clients, a solution was necessary to better manage and analyze the flood of data.

 

Our Solution

In early June of 2016, Scott Adams, a Xerva project manager and a team with years of experience in developing data analytics solutions met with Molio’s operations team to discuss how to improve their data feeds. In this conversation, Molio explained how they needed the ability to capture large amounts of data from YouTube, Facebook, and AdWords, in near real-time to be able to analyze different ad’s effectiveness. To maintain Molio’s competitive edge, it was critical to evaluate the performance across each of these platforms.

Following this initial meeting, Scott turned to Xerva’s team of architects and developers. The team performed some preliminary tests on Molio’s feeds and determined that a data warehouse would be the best solution, giving Molio access to a place where all the data could be dumped and stored.

The design plan took about a week. The solution consisted of a data warehouse and custom apps to access and merge the data. The custom apps were necessary for several reasons:

-Facebook imposes strict time limitations on calls to API (less than a second)-Facebook restricts the number of calls for data to five accounts

-Facebook restricts the number of calls for data to five accounts

-Facebook limits size of data pull, but does not publish the cap

-Facebook only allows 1 breakdown (dimension) to be pulled at a time except for Age&Gender and Device&Placement-Tableau does not work well with multiple fact tables

-Tableau does not work well with multiple fact tables

 

Scott and his team concluded that it would be necessary to build three independent apps for Facebook to overcome the five ad account limit for data calls. After proving this process to Facebook, the initial status designation of the app was upgraded from “Developer” to “Basic”. The “Basic” app status allowed for up to 25 accounts to be accessed, as a result only one app was necessary.

To overcome Tableau’s limitations on handling the presentation of multiple data tables, Xerva merged the Facebook and AdWords feed within the data warehouse.

A week after the initial meeting with Molio, Xerva presented the proposed solution. Molio signed off on it, and development began immediately.

Development took just over a month. The applications and data warehouse were delivered to Molio in late July, a mere seven weeks from the initial meeting. The solution provided Molio the ability to present real-time data from all of their campaigns in Tableau.

Xerva continues to work with Molio in a supporting capacity, as their needs evolve.