A Big Data strategy that combined internal marketing information with social media helped our Entertainment Industry client create winning marketing strategies. Popcorn was extra.
Our client, a leader in the entertainment industry, needed to define and implement a best of breed marketing program to effectively leverage their investments in content creation.
The client engaged with our big data group, architected and developed a new big data solution, focusing on gathering data from social, marketing sources (e.g. Facebook, Twitter, YouTube, and Google Analytics) using Apache Flume, and Spring Social frameworks and storing the data in HDFS, a cloud solution utilizing Amazon’s EMR platform. We used Apache Hive, Pig, and Mahout for predictive analysis and Python for MapReduce programming, to create sentiment analysis on client’s offerings as well as competitive offerings. The objective of the project was to have a daily social activity report and combine that with marketing report for sentiment analysis and predictive modelling for entertainment consumers.
Our solution allowed clients analysts to create, maintain and measure the effectiveness of their marketing programs in an effective, close to real time manner without expending the effort to assemble and manage datasets for analysis. The program provided for a more effective marketing program while reducing IT processing costs.
- Statistical Analysis
- A/B Campaign Analysis