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Implementing a Big Data Solution on Behalf of a Media House

Communications | Analytics Services

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TEKsystems® Analytics Services delivered a big data solution to strengthen the targeted marketing efforts of a media house. 

The client is a media house based in Southern California and is a subsidiary of a major media conglomerate. The company is responsible for producing and distributing motion pictures. 

Social media has enabled businesses and organizations to connect and engage with consumers more closely than ever before. The vast amount of incoming consumer data from social media channels such as Facebook, Twitter or YouTube, provides a tremendous opportunity for businesses to keep a pulse on their target markets and understand audience attitudes, opinions and sentiments. Organizations can learn what messages resonate with specific audience segments; the data could also uncover unmet needs in the marketplace that they could resolve.

Considering how this trend has impacted the entertainment industry specifically, many production houses are leveraging social media analytics to monitor consumer reactions and inform targeted marketing campaigns to enhance the movie-goer experience and subsequently drive revenue.

Although the data offers great promise to a range of industries including entertainment, organizations often struggle to make sense of the high volume of information and translate it into meaningful and actionable insight.

Apache™ Hadoop®, Apache Hive™, Oracle Endeca Information Discovery, SQL

The client, a film production and distribution house was interested in better understanding its audiences and their experiences at the movies. Following the release of new movies, the client would collect data from movie-goers by deploying in-person surveys as part of a two-part approach to collecting data. General information, including name, email address, movie genre preferences and how they heard about the movie, was collected. The second part to the client’s data collection approach was through social media. For example, movie trailers would be released on Facebook or YouTube, and the client could monitor user engagement through comments and “likes.” Additionally, using a Twitter handle, the client would post a URL that would link back to the client’s website, and user engagement could be tracked. The data gathered through this online marketing strategy would be used not only for revenue purposes, but also for determining how to create a positive experience for the consumer.

Data gathered from social media proved to be a valuable tool for the client. In fact, based on commenters’ feedback on a trailer that was posted to Facebook, the client realized consumers wanted a sequel to an old movie, so a sequel was developed. Although a social media campaign offered actionable insights such as this, the data was coming in from various sources so making sense of it was a challenge. Looking at data independently was manageable, but getting a unified view of the big picture could not be done. For example, if the client was interested in analyzing YouTube “likes,” that was calculable. But the client was unable to monitor and quantify more complex metrics—such as how a movie was performing across the movie’s website, Twitter, YouTube and Facebook.

The client wanted to be able to calculate return on social media campaign investments but had no way of doing so. The high volume of data coming in from multiple, disparate sources on a daily basis was disjointed and the client couldn’t view, analyze and segment consumers. A single platform for capturing, processing and analyzing the data would enable the client to make correlations and draw connections; this meaningful consumer insight could then be used to inform decisions and implement more effective targeted marketing strategies.

Lacking the internal expertise, the client sought a third-party partner with expertise in big data initiatives. An end-of-year deadline was in place because the client wanted to be able to calculate revenue related to Thanksgiving and Christmas holidays. The client first partnered with a third-party organization that—after six months on the job—showed no success; finding a new partner to complete the job in the remaining eight weeks before year-end was critical. The new partner of choice would need to be able to take a step back to evaluate the previous vendor’s work and then redesign it. Additionally, because the previous partnership proved to be a poor investment, client stakeholders’ confidence had dwindled. The client needed a stand-out partner they could trust who could help the organization regain confidence in IT.

The client had a high volume of data coming in every day from various sources, including Facebook, Twitter, YouTube, the movie’s website and even sponsored sources. Because the volume was so high, a traditional big data solution would have been an expensive and time-consuming investment. As a result, TEKsystems' Analytics Services practice proposed a custom solution in which we would use Oracle Endeca to derive value from free form text and Apache Hadoop to synthesize the high volume of data. Specifically, the data would be extracted into the Endeca system using CloverETL from Amazon’s Hadoop ecosystem. Upon data extraction we would use Endeca’s inbuilt dashboard technology for building the metrics definition and data presentation. 

The data would be imported from various social media sites into Hadoop. From there, the data would get processed and pushed into Endeca where it would be analyzed, and then finally arrive in a unified single dashboard. This dashboard would provide a holistic picture, indicating performance across the different sites.

Despite having an abundance of data, the client couldn’t make correlations, so our proposed solution ensured the client would be able to more effectively mine through and discover what the data actually meant. For example, Endeca would enable the client to do a free form text search, resembling that of a Google or other search engine search. If the client wanted to know how many people were talking about a specific genre of movies (e.g., family movies), Endeca, a data discovery mechanism, would pull all comments pertaining to that genre. This type of information would be invaluable to informing the client’s marketing strategies.

Additionally, the nature of social media creates various complexities of its own. Consider multiple user accounts across all social media platforms held by a single person. Our solution would enable predictive analysis which would help eliminate potential skewing or inflating of data.

Based on our proposed solution, the client chose TEKsystems to support its efforts to extrapolate more actionable data for its marketing strategies. The client acknowledged that we are a co-development partner with Oracle for Endeca technology, and appreciated our depth of knowledge and understanding associated with the Endeca tool.

In just eight weeks, TEKsystems successfully implemented an on-site and off-shore big data solution that provided a stable system for the client to extract data. Our customized solution enabled the client to holistically view and assess the data, segment consumers and extrapolate information based on certain trends defined by the data. Ultimately, our support provided the client with enhanced movie-goer profiling capabilities that they were unable to achieve before when all the data was disjointed. Critical movie-goer data such as demographics, psychographics and behavior values could now be captured. And the client was finally able to view the data in a meaningful way; the following is a sample of capabilities:

  • Compare two or more movie titles over a period of time
  • Compare two or more community profiles based on similar attributes
  • View how well content, whether a post, image, video or trailer, is performing across social media channels

This improved profiling will increase the effectiveness of targeted marketing efforts by allowing the client to present each of their titles and services to the appropriate movie-goers. 

The success of this engagement was driven by our knowledgeable on-site and off-shore team. The team included two on-site resources with business intelligence (BI), data extraction/transformation/loading (ETL) and user interface (UI) expertise, one dedicated on-site advisory resource and three support staff based at our Hyderabad Solution Center in India.

The TEKsystems Analytics Services team adopted Agile methodology to implement our solution; we held daily scrum meetings and multiple iterations for requirement and testing. Our daily scrums and interactive approach enabled us to achieve the results desired by the client. Because of our iterative and collaborative approach and our efforts to maintain open communication, the client stayed informed of our progress throughout the engagement. Our diligence and commitment to reaching the eight-week deadline enabled us to achieve success in even less time than the previous partner spent on its failed attempt. As a result, we were able to re-establish the client’s confidence in IT.


In traditional BI solutions, our team utilizes Waterfall methodology, which follows a top-down approach: go to the client, define requirements, solidify the requirements, and then results would be provided after implementation. In the social media environment, things change quickly. As such, we determined that following an Agile methodology would enable our success. We took a requirement and implemented it iteratively.


The technical strength and expertise that the team contributed proved critical to our success. The previous partner had more than six months to work on this effort beforehand—and failed. This meant that we not only had to backtrack and evaluate and fix their mistakes, but also work through our solution under a consolidated timeline. Without the right people, knowledge and skill sets, this could not have been achieved.


The Analytics Services team made it a priority to meet with the client every day in order to ensure stakeholders were up to speed on our progress. This open communication ensured the client was informed of and comfortable with our actions and how they would be impacted every step along the way. If there were any problems, instead of wasting time going down the wrong path, our iterative approach allowed us to resolve them immediately and continue moving forward.

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