A global motorcycle manufacturer with headquarters in Australia.
The client wanted a better understanding of consumer sentiments to improve the effectiveness of its marketing initiatives. SG Analytics was tasked with creating a Natural Language Processing (NLP) tool to monitor consumer sentiments based on posts and comments in various social networks including Facebook, Twitter, Vine, Tumblr, Youtube, and Instagram.
SG Analytics followed a 4-step process to deliver a customized, tailor-made solution to the client:
SG Analytics created a tool that leveraged various techniques, including APIs and scraping methodologies to capture relevant social media data from the targeted social networks.
The team automated the cleaning and standardization process to prepare all data for later aggregation with minimal input of manual labor.
SG Analytics' scoring algorithm would assign a sentiment score to each data entry. According to the client's requirement, the data were aggregated bi-weekly in a single database.
SG Analytics created a dashboard which helped the client monitor the consumer sentiment and make informed decisions to improve the effectiveness of its marketing initiatives.
SG Analytics delivered a tool that assessed consumer sentiments based on social media conversations and visualized its findings in an easy-to-access online dashboard.
The client leveraged SG Analytics' tool to increase the effectiveness of its marketing initiatives and take actions to enhance the perception of its brand.